HHPR Spring 2013 Issue by Harvard Health Policy Review

HHPR

Harvard Health Policy Review

2013 Spring Issue; Vol.14, No. 1

P harmaceutical R egulation I nside : Competition, Market Power and Pricing in Brand Name Pharmaceutical Markets (Joel W. Hay) The Rise of Antimicrobial Resistance (Dame Sally Davies, Tom Fowler, Keith Ridge, David Walker) Interview with Jonathon Gruber, PhD, MIT Professor of Economics

And More >>>

Save the DateS for These Two Events Offered in Sequence at the Hyatt Regency Crystal City, Washington, DC — September 2013

Hybrid Conferences & Internet Events See website

THE NATIONAL HEALTHCARE PERfORMANCE AND OUTCOMES ANALYTICS SUMMIT The Leading forum

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September 16 – 18, 2013

September 18 – 20, 2013

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WASHINGTON, DC EDITION The Leading forum on Patient Safety, Quality Enhancement and Medical Error Reduction

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fEATURINg: Carolyn M. Clancy, MD, Director, Agency for Healthcare Research and Quality, Rockville, MD Susan Dentzer, Senior Policy Adviser, Robert Wood Johnson Foundation; Health Policy Analyst, The PBS News Hour, Washington, DC

Jefferson School of Population Health and MedStar Health MeDia PartnerS: Harvard Health Policy Review, Health Affairs, and Patient Safety & Quality Healthcare

richard Gilfillan, MD, Acting Director, Center for Medicare and Medicaid Innovation, Centers for Medicare and Medicaid Services; Former President and Chief Executive Officer, Geisinger Health Plan; Executive Vice President of Insurance Operations, Geisinger Health System, Washington, DC bernadette Loftus, MD, Associate Executive Director, The Permanente Medical Group, Rockville, MD Mark McClellan, MD, PhD, Director, Engelberg Center for Health Care Reform, Brookings Institution; Former CMS Administrator and FDA Commissioner, Washington, DC

David Mayer, MD, Vice President, Quality and Safety, MedStar Health; Founder, Annual Telluride International Patient Safety Roundtable, and Patient Safety Medical Student Summer Camp, Columbia, MD David b. nash, MD, Mba, FaCP, Dean, Jefferson School of Population Health and Dr. Raymond C. and Doris N. Grandon Professor of Health Policy, Thomas Jefferson University, Philadelphia, PA

HARVARD HEALTH POLICY REVIEW FOUNDED IN 1999 / VOL. 14, NO. 1 WWW.HCS.HARVARD.EDU/~HHPR

Editor’s Note 2 Pragya Kakani FEATURES Spending on Pharmaceuticals: How much do we pay 3 William S. Comanor, PhD and and what do we get for what we pay? H.E. Frech III, PhD Competition, Market Power and Pricing 6 Joel W. Hay, PhD in Brand Name Pharmaceutical Markets Pharmaceutical Mergers and Innovation 8 Alexander A. Maglunog Jr. and Stuart O. Schweitzer, PhD Side Effects of Competition 11 Guy David, PhD, Sara Markowitz, PhD, and William Pajerowski Health Insurance Expansions and Pharmaceutical Markets 15 Margaret E. Blume-Kohout, PhD and Neeraj Sood, PhD STUDENT CONTRIBUTIONS Big Pharma’s Lobby: When Public Health and Profit Conflict 18 Jermaine Heath Regulating the Direct to Consumer Genetic Testing Industry 20 Arifeen Rahman, Phebe Hong, Rebekka Depew, and Bernadette Lim Pharmaceutical Pollution of Water in India: 23 Annie Ryu International Market Failure The Role of Epidemiology in the Pharmaceutical Industry: 27 Paul V. Petraro, ScD ‘Real World Data Analytics’ HEALTH HIGHLIGHTS An Interview with Jonathan Gruber, 29 Brandon Jones MIT Professor of Economics The Rise of Antimicrobial Resistance 31 Dame Sally Davies, Tom Fowler, Keith Ridge, and David Walker ObamaCare: The Plot Thickens 34 Michael Cannon, MA, JM

Spring 2013 Volume 14, Issue 1

editor’ s note

Editor’s Note Over the past year, prescription drug costs exceeded $324 billion dollars, representing a full 11% of drug costs. Moreover there has been considerable growth in pharmaceutical spending as the baby boomer generation comes to the age of retirement. While the United States does not stand out as an outlier in pharmaceutical spending as a share of GDP, drug companies are frequently attacked as unethical or price gouging. As a result there has been considerable discourse in the public as well as academic literature surrounding the appropriate behavior by pharmaceutical companies in several different arenas including price, advertising, research practices, and more. Given its relevance to the health policy community, we are proud to dedicate our Spring 2013 issue to Pharmaceutical Industry Policy.

Editor-in-Chief Pragya Kakani Managing Editor Marissa Suchyta Business Manager Bradford McGann Publisher Linda Zhang Design Chair Esther Lim

Inside this issue of HHPR you will first find a wide variety of articles relating to pharmaceutical industry practices by research experts as well as undergraduate and graduate students. Motivated by academic literature, these pieces try to address the “big questions” including “Are drug prices too high?,” “Are current patent protections optimal?,” and “How will the Affordable Care Act (ACA) affect pharmaceutical markets?” In answering these questions, our articles also draw on comparisons with other international markets to compare and contrast efficiencies. In addition to rigorous questions of economics, our pieces also address questions of pharmaceutical ethics including how to deal with pharmaceutical pollution and what constitutes ethical advertising. Finally, you will find a selection of pieces related to other recent developments in health policy including the establishment of health insurance exchanges in the US and dealing with antibiotic-resistance globally.

Senior Editors Allan Hsiao, features Arifeen Rahman, features Sifon Ndon, student contributions Brandon Jones, health highlights Young Kwon, online content

To supplement our print publication, we encourage you to visit us at www.hhpronline.org for more information about HHPR, subscription information, updates about upcoming events. Our website also features additional commentary by Harvard undergraduates year-round on topics including medical sociology, bioethics, drug development, health economics, and more. These pieces can be accessed on our online blog called HHPRTalk. As always, any questions or comments from our readers are warmly welcomed and can be addressed to hhpr. harvard@gmail.com

Associate Editors Sarib Hussain Claire Motyl Katie Rainer Edward Maile

Finally, we’d like to thank our dedicated staff including our senior and associate editors, design chair, business manager, publisher, and managing editor for their time and commitment in preparing this issue of HHPR. We would also like to thank our advisers Warner Slack, MD, David Cutler, PhD, Mary-Jo Good DelVechhio, PhD, Haiden Huskamp, PhD, and Peter Grant, JD for making themselves available to guide us through the publication process. We hope you enjoy this latest issue of HHPR, and thank-you for your readership. Sincerely,

The Harvard Health Policy Review is an undergraduate publication of Harvard College. The Harvard name and Veritas Shield are trademarks of the President and Fellows of Harvard University.

Pragya Kakani Editor-in-Chief Spring 2013

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Harvard University Student Organization Center at Hilles, Box #40 59 Shepard Street Cambridge, Massachusetts 02138 ©2013 by President and Fellows of Harvard University. All rights reserved. No part of this publication may be reproduced in any form without express written consent from the publisher.

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about the cover The cover of this issue was designed by Dennis Rolls of Johannesburg, South Africa. The image is entitled “Do You Feel Better.” Please visit www.denisrolls.blogspot.com for more information.

FEATURES Spending on Pharmaceuticals: How much do we pay, and what do we get for what we pay? >>> William S. Comanor, PhD and H.E. Frech III, PhD

he United States spends less than 15 percent of its health care dollars on pharmaceuticals. Despite this fact, these outlays are the source of considerable controversy. Some have suggested that we spend too much for drugs, which contributes to health care cost inflation.1The drug companies, many believe, sell too many pharmaceuticals of dubious value, and that we would be better off if fewer drugs were introduced and marketed.2 In this paper, we consider these allegations. We offer some direct evidence along with some findings from the economic literature. What we conclude is that the reality is far more complicated and nuanced than suggested in these popular criticisms. Before proceeding, however, we observe that there are actually two pharmaceutical industries, comprised largely of different firms with different business plans and different product and pricing strategies. The firms who produce and market branded pharmaceuticals are not generally the same as those who sell generic pharmaceuticals. For 2010, 78 percent of all prescriptions were filled generically in the United States; on the other hand, the branded industry accounted for fully 83 percent of total pharmaceutical revenues.3 Differences between the two pharmaceutical industries influence our conclusions.

Expenditures on Pharmaceuticals Expenditures depend on both prices and quantities, so our first task is to separate these factors. Reported US prices for branded drugs are higher than elsewhere, although differences across countries depend on the exchange rates employed and the bundle of good used to compute the price indexes.4,5 US prices for generic drugs are lower on average than anywhere else, but not enough lower to offset the higher prices reported for branded drugs.4 While we will have more to say about US prices later, consider first what these differences indicate about the actual quantities of pharmaceuticals consumed. One determines these quantities by adjusting expenditure levels for relative prices using appropriate exchange rates. Market exchange rates are unstable and also inappropriate because they reflect various economic forces besides

relative prices. The alternative is some form of Purchasing Power exchange rate based on the ability to purchase the same goods in different countries. However, even applying broad-based Purchasing Power exchange rates rather than Market exchange rates is not sufficient for these purposes because drug prices can differ so widely among countries. What is required instead are Purchasing Power exchange rates limited to pharmaceuticals. Using OECD data for developed countries, Frech and Miller make such computations, and their findings are not what one expects. When the appropriate calculations are made, US real expenditures are not so very different from those found elsewhere. For the year 1990, US average outlays on pharmaceuticals stood at $236 per person, which place it in 9th place in a list of 23 developed countries.6 In this list, France, Italy and Germany all spend more on drugs per capita, with France in first place spending more than twice that spent in the United States. What leads to higher reported US drug expenditures are therefore prices rather than quantities. Unfortunately, these findings are more than 20 years old and we don’t have more recent data to compare them with. What we have instead are physical measures of pharmaceutical consumption, most recently for 2005. Interestingly, similar patterns are reported with these data. US consumers receive fewer “doses” per capita than most other developed countries, and also fewer grams of active pharmaceutical ingredients.4 At best, such measures of real pharmaceutical consumption are approximations. Important differences across countries are missed, related specifically to different consumption patterns. Such differences can be substantial. In a study of the hundred best selling pharmaceuticals in Italy, Germany, France, and the United Kingdom in 1992, only eight products were common in the top hundred in each country.7 Using more recent data, we also find large differences in consumption patterns across countries.4 In particular, the US uses relatively more recent and more powerful drugs. Since more recent and more powerful drugs invariably cost more, these differences in consumption patterns contribute to the higher prices paid in the United States.

The US Payment System Even while available data indicate that US pharmaceutical prices are higher than elsewhere, many of these differences are overstated in the data. This discrepancy follows from the particular payment system in place for most pharmaceuticals, including especially the pervasive effect of branded drug rebates. The relevant factor here is not only that these rebates can be substantial but also they are generally not included in reported drug prices. As a result, the cash prices of branded drugs observed in the data overstate the actual prices paid for most pharmaceuticals. Although the major drug companies sell their products to pharmacies (typically via drug wholesalers) at established, reasonably uniform prices, that fact does not mean that all buyers pay the same prices. While cash buyers pay the drug company’s price plus a retail margin, insured consumers pay only a co-pay which is not typically set by the drug company but rather by an insurance company or other payer. The essential feature of most pharmaceutical purchases is that an insured consumer’s out-of-pocket price is set by their insurance company rather then by the drug company. That factor is particularly relevant because insured consumers greatly predominate in most pharmaceutical markets. The insurance companies and other payers pay most of the cost of drugs supplied to their subscribers, but they do this in a circuitous manner. The insurer’s payment to the providing pharmacy, plus the co-pay received from the consumer, must at least cover the retailer’s costs and margin for only then can it remain in business. At the same time, payers frequently receive a discount from the drug company to encourage purchase of their products rather than those of their rivals. Those discounts take the form of a rebate paid to the payers’ agent (or Pharmacy Benefit Manager) who may then retain as much as 30 percent of the rebate for itself before remitting the remaining 70 percent to the payer.8 A critical factor is that these rebates are not publicly disclosed nor are they included in available data on drug purchases and sales. As a result, the available data overstate drug company revenues and prices. The essential feature of reported prices is that very few buyers actually pay them. Most pay less. This explanation refers to the prices charged for branded drugs but not to generic drugs. In the latter case, rebates are typically minimal to private buyers. Moreover, since all generic drugs must pass the FDA’s requirement for bio-equivalence with the previous patented and branded product, they are reasonably therapeutically ho-

Spring 2013 Vol. 14, No. 1

FEATURES

mogeneous, and market outcomes reflect that fact. The available evidence indicates that generic drugs are priced lower than the branded innovator’s drugs, and also once five or six generic sellers compete for sales of the same molecule, prices are set substantially below the levels previously set by the branded innovator and approach marginal costs.9 Generic prices can exceed those levels when the number of rival firms is smaller. For drugs with sufficient demand to attract several generic sellers, therefore, prices typically approach production costs. The importance of this factor is evident in some statistics mentioned above. Since generic sellers accounted for 78 percent of all prescriptions but only 17 percent of aggregate drug revenues in 2010, their average revenues per prescription was only about 22 percent of that received by branded sellers. Of course, that figure does not take account of the rebates paid by branded sellers and therefore understates the true percentages. However, it does suggest that generic prices lie well below their branded counterparts. Effects of Pharmaceutical Consumption on Improved Health By focusing so strongly on prices and expenditures, we sometimes forget that the goal here is improved health. Many of us would be quite willing to spend more on pharmaceuticals, and even pay higher taxes to do so, if we could thereby gain longer and healthier lives. We recognize

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that gaining improved health is not costless but requires lower expenditures on other things. That reality exists even if we choose not to permit relative incomes to determine health status. In this context, it is essential to explore the effectiveness of pharmaceutical consumption for improved health. In an important study, Miller and Frech (2004) distinguish the health effects of pharmaceutical and other health care expenditures within OECD countries on various measures of health status for 1995 and 1999. In their analysis, they control for the effects of wealth and some lifestyle variables, which is key to obtaining unbiased estimates of the productivity of pharmaceuticals. They report that a 10 percent increase in pharmaceutical consumption increases a 60 year old person’s disability-adjusted life expectancy by nearly one percent. Greater pharmaceutical consumption is especially effective in lowering circulatory disease mortality. It appears to have less effect on mortality due to cancer and respiratory disease. These findings can also be expressed in terms of the cost of extending life by increasing pharmaceutical use alone. Here Miller and Frech find that the cost on average of adding a year to disability-adjusted life expectancy for Americans (at age 60) is about $12,000 for men and $14,000 for women.10 Since current estimates suggest that the benefit to society of an additional life-year is about $150,000, such outlays are a bargain.11 We would readily spend an additional $12 to $14,000 for something worth

upward of $150,000. Using a similar model over a panel of OECD countries from 1985-2002, Caliskan also finds that greater pharmaceutical consumption leads to increased life expectancy. His estimated effect, however, is smaller than that reported by Miller and Frech. Interestingly, he finds that private spending on pharmaceuticals is more productive than public spending.12 There are two other approaches used to measuring the productivity of pharmaceuticals in producing health. The first focuses on new pharmaceuticals relative to older ones. That approach is used by Lichtenberg (2007) who examines the health gains achieved by spending more on new pharmaceuticals rather than older ones. This factor is relevant, he contends, because new pharmaceuticals are much more productive. He concludes that the cost of extending life expectancy by one year by using newer pharmaceuticals in the US between 1990 and 2003 is only $15,974.13 That result thereby parallels the findings of Miller and Frech. In an earlier study, Lichtenberg (2003) estimates the effect of new drug introductions on reduced mortality. Using a benchmark valuation of $25,000 per additional life-year, much lower than the figure suggested above, he reports a social rate of return from pharmaceutical innovation of 68 percent per annum.14 If additional life-years were valued instead at $10,000, that return would fall to 27 percent. In either case, these figures suggest that society’s returns from pharmaceutical innovations are very large. A second alternative is to examine the “new drug offset” theory, which holds that new drugs are so productive that they reduce overall health care spending in the long-run, even though new drugs are initially more expensive. This approach is generally supported in the economic literature. For example, Santerre applied this approach to both US data between 1960 and 2007 and also to a panel of OECD countries (excluding the US) from 1971 to 2004. He finds from both studies that increased introductions of new drugs are associated with lower total health care spending.15 This result again implies that new drugs are more productive than older ones Conclusions We suggest here some brief answers to the questions posed in the title of this paper. First, US expenditures are not as high as generally reported. Despite the high prices reported for some branded pharmaceuticals, very few consumers actually pay them. To an increasing extent, these drugs are actually purchased by insurance companies, health maintenance orga-

FEATURES nizations, government agencies and other payers; and the prices they pay are often much lower than those reported publicly. In turn, consumers pay only a co-pay which is generally much lower. The share of consumers who pay cash prices for their drugs continues to decline. Furthermore, the share of prescriptions filled with generic products continues to increase. While quicker generic entry leads to further declines in the amounts paid by consumers and payers for pharmaceuticals, it also has the effect of reducing the incentives to invest in pharmaceutical research and development as well as reducing the pool of retained earnings available to support these expenditures. Whether this result is efficiency-enhancing or depressing is a difficult question beyond the scope of this paper. For an interesting discussion of the relation between R&D expenditures and new product introductions, see Munos (2009).16 Furthermore, the low prices charged for generic pharmaceuticals have contributed to the problem of supply disruptions that have plagued the generic industry.17 This issue is important because of the increasingly evident benefits of new pharmaceuticals, most strikingly in the case of cardiovascular disease. In recent decades, mortality rates from this disease have declined sharply, and new drugs have played a major role. Seeing these gains repeated in other disease areas should be our goal, even if that requires greater outlays on pharmaceuticals. The evidence from past studies is that these gains would be worth the additional cost. How to pay for these health improvements would then become the relevant issue. References

1. Emanule, Ezekiel J., “Spending More Doesn’t Make Us Healthier,” New York Times, Oct. 27, 2011, http:// opinionator.blogs.nytimes.com/2011/10/27/spending-more-doesnt-make-us-healthier/ (accessed June 18, 2013). 2. Kessler, David A., Janet L. Rose, Robert J. Temple, Renie Schapiro, and Joseph P. Griffin. “Therapeuticclass wars--drug promotion in a competitive marketplace.” New England Journal of Medicine 331, no. 20 (1994): 1350-1353. 3. IMS Institute for Healthcare Informatics, The Global Use of Medicines: Outlook Through 2016, 2012. 4. Danzon, Patricia M., and Michael F. Furukawa. “International prices and availability of pharmaceuticals in 2005.” Health Affairs 27, no. 1 (2008): 221-233. 5. Schweitzer, Stuart O., and William S. Comanor. “Prices of pharmaceuticals in poor countries are much lower than in wealthy countries.” Health Affairs 30, no. 8 (2011): 1553-1561. 6. Frech, H. E., and Richard D. Miller Jr. The productivity of health care and pharmaceuticals: an international comparison. Aei Press, 1999.

Income, Output, and Prices”, ed. by Alan Heston and Robert E. Lipsey, NBER, University of Chicago Press (1999): 371-416. 8. Langenfeld, James, and Robert Maness. “The Cost of PBM “Self-Dealing” Under a Medicare Prescription Drug Benefit.” Chicago (2003). 9. Reiffen, David, and Michael R. Ward. “Generic drug industry dynamics.” Review of Economics and Statistics 87, no. 1 (2005): 37-49. 10. Miller, Richard D., and H. E. Frech. Health care matters: pharmaceuticals, obesity, and the quality of life. Aei Press, 2004. 11. Murphy, Kevin M., and Robert H. Topel. The value of health and longevity. Journal of Political Economy, 114, no. 5 (2006): 871-904. 12. Caliskan, Zafer. “The relationship between pharmaceutical expenditure and life expectancy: evidence from 21 OECD countries.” Applied Economics Letters 16, no. 16 (2009): 1651-1655. 13. Lichtenberg, Frank R. “The impact of new drugs on US longevity and medical expenditure, 1990-2003: Evidence from longitudinal, disease-level data.” American economic review 97, no. 2 (2007): 438-443. 14. Lichtenberg, Frank R. Pharmaceutical innovation, mortality reduction, and economic growth in Measuring the Gains from Medical Research, an Economic Approach, ed. by Kevin M. Murphy and Robert H. Topel, University of Chicago Press, 2003, 74-109. 15. Santerre, Rexford E. “National and International Tests of the New Drug Offset Theory,” Southern Economic Journal 77, no.4 (2011): 1033-1043 16. Munos, Bernard. “Lessons from 60 years of pharmaceutical innovation.” Nature Reviews Drug Discovery 8, no. 12 (2009): 959-968. 17. Schweitzer, Stuart O. “How the US Food and Drug Administration Can Solve the Prescription Drug Shortage Problem.” American Journal of Public Health (2013): e1-e5. Image courtesy of the Los Angeles Times.

William S. Comanor, PhD is Professor of Economics at UCSB and Professor in the UCLA School of Public Health. He has written 5 books and over 100 professional articles, and was designated a Distinguished Fellow of the Industrial Organization Society. He has served as Special Economic Assistant to the Director of the Antitrust Division in the Department of Justice, and also as Director of the Bureau of Economics at the Federal Trade Commission.

H.E. Frech III, PhD is Professor of Economics at the University of California, Santa Barbara. He has served as visiting faculty at Harvard University, the University of Chicago, Curtin University, Australia, and Sciences Po in Paris. He earned the BSIE at the University of Missouri and his PhD at UCLA. He has written widely on health economics.

7. Danzon, Patricia M. and Allison Percy. “The Effects of Price Regulation on Productivity in Pharmaceuticals,” in International and Inter-area Comparisons of

Spring 2013 Vol. 14, No. 1

FEATURES Competition, Market Power and Pricing in Brand Name Pharmaceutical Markets >>> Joel W. Hay, PhD Branded pharmaceutical innovation has been declining substantially for over 60 years. Drug innovation is dependent on sufficiently high prices and profits to reward risky and costly R&D. In assessing competition in pharmaceutical markets government agencies evaluating potentially anti-competitive behavior can misapply pricing tools developed elsewhere. In other industries measures of cross-price elasticity of demand are crucial for assessing relevant economic markets, but since branded pharmaceuticals often don’t compete on price, these measures lose relevance. Rather than focusing on drug pricing behavior, assessments of anti-competitive conduct in branded pharmaceutical markets should reflect the distinct institutional characteristics of these markets.

room’s Law: Brand Name Drug Innovation and Pricing Pharmaceutical innovation is highly risky, slow and costly. The average costs of bringing a new drug to market exceeds a billion dollars, and the average development time exceeds a decade.1 Over the past six decades there has been an alarming and relentless decline in pharmaceutical research productivity, with the number of new US Food and Drug Administration (FDA)-approved drugs per inflation-adjusted billion dollars of R&D spending dropping in half about every nine years since 1950. This is an industry problem so serious that it has been characterized as Moore’s Law in reverse, or “Eroom’s Law.”2 While the causes of this decline are complex and not fully understood, it is clear that lower branded pharmaceutical prices and profits will only compound the problem. Brand name drug manufacturers are typically granted patent protection or other forms of market exclusivity specifically to encourage and reward them for bringing innovative treatments to market.3 This means that manufacturers can set prices for their branded pharmaceuticals. Branded drugs sell at market prices that are often many times higher than the marginal cost of production. This is not, by itself, evidence that the manufacturer possesses market or monopoly power in the sense that government agencies like the U.S. Department of Justice (DOJ) or the Federal Trade Commission (FTC) use these concepts to gauge illegal anti-competitive or monopolistic market behavior. Typically these prices reflect the legally-sanctioned market-exclusivity reward for innovation. Brand name drug manufacturers compete fiercely in research and development of new experimental pipeline products, and in the acquisition of new products from other organizations (including academic institutions, other biopharmaceutical

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companies, and the National Institutes of Health). They also compete in re-positioning their products with post-approval R&D studies. They devote substantial effort to the marketing and promotion of their brands, since they only have a limited time of market exclusivity before bioequivalent generics can enter the market and wipe out their profits. Prices are often only a minor dimension of branded drug competition. Branded Drugs Typically Don’t Compete on Price In various legal cases government agencies and some economists have proposed a theory of drug price competition that may well apply to other markets, but is totally alien to how branded pharmaceuticals compete. Under this theory competing branded drugs could enhance their market shares with aggressive price discounting. As a result the prices for branded drugs should drop substantially as each company competes away excess profits to gain sales. Contrary evidence of sticky drug prices or price hikes in the face of competitive challenges would be prima facie evidence of anti-competitive market conduct under this view. However, branded drugs compete primarily on their perceived and actual clinical attributes, not their prices.4,5,6 This is particularly the case when the drugs are used in life-threatening situations, or when drug choice can lead to fatal or permanent health consequences. If a doctor makes the wrong choice on a drug to treat minor heartburn, the patient may experience some short-term discomfort but typically the worst outcome will be a return visit to the doctor to switch to an alternative medication. For lifethreatening conditions such as HIV/AIDS, metastatic cancer, myocardial infarction or end-stage COPD the wrong medication choice could lead to progressive disease, irreversible patient health deterioration, or even death. The last thing on the doc-

tor’s mind in those situations is saving a few dollars by using Drug A rather than Drug B. They will choose the drug that they personally believe is the most likely to produce the best clinical outcomes for their patients. This is especially true when, as is typical for such patients, neither the physician, nor the patient nor the patient’s family bear any of the differences in drug prices because of health insurance or government health care program coverage. In this regard it makes little difference whether there is consensus in the clinical literature about which drug is actually better. Even if there were clear clinical evidence that Drug A is superior, no price discount would be sufficient to get doctors to choose Drug B. Conversely, if the clinical evidence favors Drug B, than no doctor would choose Drug A, regardless of its price. American doctors are trained to save lives, not dollars. If, as is often the case, there are no definitive studies showing superiority for Drug A or Drug B, clinicians will band into alternative treatment camps. Absent clear findings from a head-to-head comparative effectiveness trial of A versus B, clinicians using treatments with potentially fatal or serious health consequences are not going to alter their prescribing in response to drug price changes. Considered from a cognitive dissonance perspective,7 it is perfectly natural that a doctor who routinely makes life-saving decisions will have strong idiosyncratic treatment preferences precisely in those situations where the clinical evidence is ambivalent. It would be hard for doctors to live with themselves thinking that all the patients they’d treated with Drug A (including some who have died) would have actually done better with Drug B. It’s inconceivable that well-meaning doctors would alter these critical decisions based on relative drug prices, whether the clinical evidence is ambiguous or not. Moreover, in most cases drug companies selling FDA-approved medications are unlikely to risk their existing market shares by conducting headto-head clinical trials to test whether their drugs are actually superior to their competitors. This has been tried a couple of times with high-profile negative consequences for the sponsoring manufacturer, such as when Bristol-Meyers Squibb ran a trial of their drug, Pravachol, against the leading statin, Lipitor and lost in the PROVE-IT trial.8 Similarly, Merck’s ENHANCE trial found their drug Vytorin to be no better than generic simvastatin.9 An easy path to unemployment for a pharmaceutical executive is to conduct a clinical trial against their competitors and lose. This private market failure to provide socially-valuable drug information is one reason why the Patient-Centered Outcomes Research Institute (PCORI.org) was established under the Affordable Care Act.10 If the SSNIP Don’t Fit You Must Acquit Government agencies routinely evaluate in-

FEATURES dustry conduct and enforce anti-competition laws. To assess whether a company has market power subject to potential abuse one first has to determine which products compete against each other in the relevant market. As described in the DOJ and FTC Merger Guidelines, relevant economic markets are typically identified using the “SSNIP” (small but significant and non-transitory increase in price) test.11 This means that if a small price increase (e.g., 5-10%) for Product A cannot be permanently sustained without losing customers and net revenue to Product B, then Product A and Product B are in the same relevant economic market. Yet often, as with the famous glove in the OJ Simpson trial, applying the ‘square peg’ theory of SSNIP test pricing conduct to the ‘round hole’ of pharmaceutical products to assess relevant economic markets simply doesn’t fit. When brand name pharmaceutical products don’t compete on price, demand elasticity estimates and SSNIP tests typically aren’t very useful in assessing market conduct. Branded drugs routinely sustain their sales volumes despite significant price increases. Naïve application of the SSNIP test to pharmaceuticals could imply nonsensical conclusions such as every brand name drug is alone in its own relevant market without competitors. For example, application of the SSNIP test could lead to the conclusion that generic bioequivalently identical versions of a branded drug are not in the same relevant economic market, since the branded drug can raise its price by more than 5% and yet lose no further customers to the generic competitors after the initial brand defections.12 What happens in situations for life-saving drugs (e.g., for cancer, HIV/AIDS, congestive heart failure, cystic fibrosis, etc.) is that the demand curves are so inelastic that small permanent price changes are irrelevant to physician prescribing decisions. In these circumstances drug prices are not constrained by economic market forces, but rather by external political and social pressures. The manufacturer of life-saving drugs can often increase revenue by charging substantially more than they actually do and get away with it in the market, but possibly not in the political or public relations arenas. It is possible that at some much higher price than they actually charge the SSNIP test would show some cross-price demand elasticity. In fact, oncology and other specialty drug manufacturers now routinely charge $10,000 to $250,000 per patient for new drugs that add only a few months of life.13, 14 Only at these stratospheric specialty drug prices are we starting to see some nascent price sensitivity.15 To assess anti-competitive conduct in branded pharmaceutical markets, rather than SSNIP tests, the FTC and other government antitrust agencies should be using nontraditional tools that reflect the institutional realities of the pharmaceutical marketplace. They should carefully consider how

corporate conduct would differ under alternative hypothetical drug divestiture scenarios. The best evidence on this will generally not be based on econometric demand estimates. It will include evidence from clinical researchers, physicians, pharmacists, third party payers, drug company officials and others to define relevant markets and assess product substitutability along with real-world and hypothetical “but for” market behavior. Branded drugs inevitably will be perceived to have some level of market power precisely because drug patents are granted to encourage and reward drug product innovation by allowing prices to exceed marginal cost. Society needs to balance goals of efficient competitive markets against goals of ensuring that pharmaceutical manufacturers are rewarded to keep innovating. It is certainly hypothetically possible for a branded pharmaceutical company to achieve dangerous monopoly power and engage in harmful anti-competitive behavior. But pricing patterns alone are insufficient to assess this behavior. Pricing conduct is often a red herring in assessing pharmaceutical market conduct. Nonetheless it can make the media headlines and Senate floor speeches. In many cases drug manufacturers are so sensitive to the political blowback that they set branded drug prices well below levels that can be justified on the basis of actual drug value. This may be one of the reasons why drug innovation has been declining for decades. In any case, drug prices should not trigger antitrust litigation unless tangible anti-competitive market conduct is occurring. Rather than focusing exclusively on pricing behavior, we should look for such conduct in all possible dimensions of drug company behavior including; engagement in clinical research, product promotion and marketing, product quality and innovation, customer satisfaction and barriers to competitor market entry.

petition in the United States drug industry.” The Journal of Industrial Economics 26, no. 3 (1978): 223-237. 7. Festinger, Leon. A theory of cognitive dissonance. Vol. 2. Stanford University Press, 1962. 8. Cannon, Christopher P., Eugene Braunwald, Carolyn H. McCabe, Daniel J. Rader, Jean L. Rouleau, Rene Belder, Steven V. Joyal, Karen A. Hill, Marc A. Pfeffer, and Allan M. Skene. “Intensive versus moderate lipid lowering with statins after acute coronary syndromes.” New England Journal of Medicine 350, no. 15 (2004): 1495-1504. 9. Sue Hughes. “ENHANCE results yield disappointment for ezetimibe.” Heartwire. January 14, 2008. http://www.theheart. org/article/837243.do (accessed April 7, 2013). 10. Michael F. Cannon. A Better Way to Generate and Use Comparative-Effectiveness Research. Policy Analysis. No. 632 February 6, 2009. http:// www.cato.org/publications/policy-analysis/betterway-generate-use-comparativeeffectiveness-research (accessed April 7, 2013). 11. U.S. Department of Justice and the Federal Trade Commission. Horizontal Merger Guidelines. 2010. http://www.justice.gov/atr/public/guidelines/hmg-2010.pdf (accessed March 30, 2013). 12. Regan, Tracy L. “Generic entry, price competition, and market segmentation in the prescription drug market.” International Journal of Industrial Organization 26, no. 4 (2008): 930-948. 13. Appleby, Julie. “Specialty drugs offer hope, but can carry big price tags.” USA Today. August 22, 2011. http://usatoday30. usatoday.com/money/industries/health/drugs/story/2011/08/Specialty-drugs-offer-hope-but-can-carry-bigprice-tags/50090368/1 (accessed March 30, 2013). 14. Hay, J. W. “Using pharmacoeconomics to value pharmacotherapy.” Clinical Pharmacology & Therapeutics 84, no. 2 (2008): 197-200. 15. Incredible Prices for Cancer Drugs,” New York Times. November 12, 2012. http://www.nytimes.com/2012/11/13/ opinion/incredible-prices-for-cancer-drugs.html?ref=mem orialsloanketteringcancercenter&_r=0 (accessed March 31, 2013).

References

1. DiMasi, Joseph A., and Henry G. Grabowski. “The cost of biopharmaceutical R&D: is biotech different?.” Managerial and Decision Economics 28, no. 4‐5 (2007): 469-479. 2. Scannell, Jack W., Alex Blanckley, Helen Boldon, and Brian Warrington. “Diagnosing the decline in pharmaceutical R&D efficiency.” Nature Reviews Drug Discovery 11, no. 3 (2012): 191-200. 3. Hay, Joel W. “Application of Cost Effectiveness and Cost Benefit Analysis to Pharmaceuticals.” In The Grand Bargain: Ethics and the Pharmaceutical Industry in the 21st Century, ed. Santoro M. Gorrie, 225 -248. (New York: Cambridge University Press, 2005). 4. Lu, Z. John, and William S. Comanor. “Strategic pricing of new pharmaceuticals.” Review of Economics and Statistics 80, no. 1 (1998): 108-118. 5. Berndt, Ernst R., Linda Bui, David R. Reiley, and Glen L. Urban. “Information, marketing, and pricing in the US antiulcer drug market.” The American Economic Review 85, no. 2 (1995): 100105. 6. Reekie, W. Duncan. “Price and quality com-

Joel Hay received his B.A. summa cum laude from Amherst College and Ph.D. in economics from Yale University. He is a founding Executive Board member of the American Society for Health Economics (ASHEcon) and also a founding Executive Board member of the International Society for Pharmaceutical Economics and Outcomes Research (ISPOR). He is a professor at the USC School of Pharmacy and can be contacted at jhay@usc.edu.

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FEATURES Pharmaceutical Mergers and Innovation >>> Alexander A. Maglunog Jr. and Stuart O. Schweitzer, PhD Pharmaceutical firms have merged frequently in the past 20 years. Participants have justified these moves for multiple reasons: the need to enlarge their product “pipeline,” to reduce the uncertainties and risk of drug development, and to create economies of scale in research or production. Critics, however, argue that mergers reduce competition, raise prices, and may negatively impact research productivity and innovation. The evidence on economies of scale’s effect on merger’s research productivity is mixed. We studied 27 mergers that took place between 1988 and 2004 and compared firms’ levels of innovation pre- and post-merger. We consistently noted that product innovation of pharmaceutical firms after a merger appeared no greater than it was before and in some cases actually fell. Our findings suggest that pharmaceutical firms and regulators should exercise caution when considering a pharmaceutical merger, especially when the proposed merger is rationalized on the grounds of greater research productivity. .

everal previous studies have analyzed the relationship between innovation and mergers in the pharmaceutical industry, albeit with mixed results. Graves and Langowitz analyze the relationship between firm size and innovation, defined as the production of new chemical entities (NCEs), and conclude that larger firms tended to produce a smaller proportion of NCEs relative to their R&D spending.1 While they did not study mergers and acquisitions (M&As) specifically, their conclusions do suggest that mergers, which by definition lead to larger firms, do not necessarily result in the increased innovation that is anticipated. In contrast, a similar study by DiMasi finds a positive correlation between the size of the firm and the number of NCEs submitted for Food and Drug Administration approval.2 However, the author credits larger firms that merge for NCEs developed by the antecedent acquirer or target. This tends to inflate the productivity of the merger by assigning research gains to the merger despite the fact that these gains occurred previously. A study by Ornaghi shows that companies that merge have poorer innovation performance than non-merging firms.3 The study defines innovation as a function of the ratio of patents to R&D expenditures and finds that M&As negatively impact firm performance. However, it is important to note that the study does not attempt to control for inherent differences among the compared firms, and thus it is difficult to identify the degree to which changes in productivity are due to the merger itself or individual characteristics of the firms that are already established. Furthermore, Ornaghi measures innovation by

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R&D expenditures, which is problematic because expenditures are better seen as an input rather than an output. In contrast, Prabhu, Chandy, and Ellis demonstrate in their study that acquisitions augment innovation, depending upon the knowledge of the acquirer and target firms.4 They reject patents as a measure of innovation because patents do not necessarily result in new drugs. They also decide against counting new drugs as a measure of innovation because of the time lag between the initiation of R&D and final FDA approval. Instead, they measure research output as the number of products in Phase I trials by each firm per year and find a positive association between Phase I drug trials and merger activity. However, the study does not control for a firm’s productivity prior to M&A, which allows one to argue that the most productive firms are the most likely to be acquired, thus overstating the effect of the M&A itself. A recent study by Comanor and Scherer provides novel insights into why it is that mergers do not generally raise research productivity.5 The authors find that firms frequently pursue innovation along multiple research paths simultaneously, and when firms merge, the number of these research paths is reduced. It is as if merged firms decide that a larger firm does not need so

much redundancy. Further simulation analysis by the authors shows that as redundancy falls, so does final innovative output. Methodology We define innovation according to the FDA’s seven-point classification scale of new drug applications (NDAs), which range from the highest innovation category of “new molecular entity” (NME) – a novel compound in the market – to the lowest category consisting of new formulations or uses of old drugs. We divide NDAs dichotomously into two categories – NME and non-NMEs. In other words, all drugs in the first category are NMEs, and all others (in categories 2-7) are non-NMEs. These products are composed of new esters or salts, new formulations or combinations, or new manufacturers of previously marketed approved drugs. We consider NMEs innovative and non-NMEs not innovative because they are not completely novel compounds and incorporate previously approved active drug formulations. Since the development of drugs often draws upon previous research and knowledge, we attribute credit for a new drug to the company that submits the drug to the FDA for approval. We compare innovation levels of pre- and post-merger firms by comparing pre-merger drug output of the acquirer and target firms, with postmerger entities (the merged firms). We analyze innovation between pre- and post-M&A firms during a five-year period of NDA data for both groups. For pre-M&A firms, this period consists of the five full years before the year of the merger. For post- M&A firms, it is the five-year period after the first three years, which includes the year of the merger. We impose a three-year lag for our analysis to allow merged companies time for organizational changes, particularly the consolidation of research and development efforts. Since it takes

FEATURES time to develop and test drugs, the lag permits our analysis to focus on a period when post- M&A firms are stabilized and fully operational as one entity. We measure innovative productivity based on two valuations. First, we examine the number of NMEs per NDA to reveal the fraction of drugs deemed innovative according to our scheme discussed above (Category 1 versus all others). Second, we examine the number of NMEs per year, which measures productivity not as a proportion, but in terms of the sheer number of “innovative” drugs a firm produces per year. We also compare individual firm output against industry averages for all pre-M&A and post-M&A firms respectively. We analyze time trends in innovation during the five-year periods, in order to see if firm productivity might have increased over time, thereby making the five-year average less meaningful as a measure of post-merger research productivity. A positive slope would suggest that firms increase efficiency as they “get to know each other” after a merger, while a flat slope would suggest more a case of “love at first sight!” Due to varying pharmaceutical firm size, we use NME per NDA as the productivity variable, given that the number of new molecular entities produced in a single year (NME/Year) can be misleading because it is secondary to differences in firm size and R&D budgets. We elect to use one-way repeated measures ANOVA to compare innovative productivity of merged pharmaceutical firms year to year for each of the five post-merger years. We noted that repeated measure ANOVA more accurately fit the model we present when we pooled individual firm data. We simultaneously compare innovation measures (NME per NDA and NME per year) for each of the five post-merger years, testing the equality of their means for significant differences in innovation as the merged pharmaceutical firm “matures.” In this way, we treat each year following a merger event as a unique observation. Data We obtain our data from data sets available from the FDA. “The Drug Approval Reports,” which contains information for original new drug approvals from 1984-2010 on the drug name, application number, firm applicant, chemical type, review classification, and approval date.6 “Drugs Approved Between 1981-2003” provided information on generic drug approvals and discontinued drugs. As the 1981-2003 data set includes all applications, we exclude those without the designation of chemical type or review classification as they are not new to the market and offer no significant modification from existing products. In the cases in which we find NDAs in the 1981-2003 data set without a corresponding item on the for-

mer data set, we elect to include them to create an accurate picture of the approvals in the past. These discrepancies are likely due to the FDA’s revision of the lists to provide the latest content on the FDA’s website and the omission of newly discontinued drugs. We verify that these NDAs are not in error by confirming their existence with previous volumes of the Orange Book: Approved Drug Products with Therapeutic Equivalence Evaluations.7 We cross-reference all firm applicants for each NDA with previous volumes of the Orange Book: Approved Drug Products with Therapeutic Equivalence Evaluations,8 Physician’s Desk Reference,9 Billups American Drug Index,10 and the Merck Drug Index.11 We also make adjustments where necessary to ensure that proper credit is attributed to the original firm that produce the application instead of later firms who purchase the rights to market a drug or acquire the originating firm. We obtain information on the M&As in the pharmaceutical industry from Ornaghi’s study, which covers the period 1988-2004 and draws upon The Merger Yearbook.12 There are 27 M&As in the period 1988-2004 as described by Ornaghi; thus, our sample consists of 54 pre-M&A firms and 27 post-M&A firms. In the FDA datasets, we frequently encounter drugs with the same NDA number but a different product number. This occurs when the same drug comes in different dosages or has other minor modifications. We allow for the appearance of a NDA number only once and therefore a company only receives “credit” for the development of a drug once. We apply this rule across an M&A (for acquirer, target, and merged firms) as well as within individual firms. We make two additional adjustments to the above design. We assign each drug to the appropriate pre-M&A firm in situations in which the data lists the post-M&A as the applicant or the rights of the drug were sold to another firm or subsidiary. For example, Zofran is classified as “Glaxosmithkline” under the FDA’s record, despite the fact that Glaxosmithkline did not exist until 2000 and the application was submitted in 1992. Thus, we assign credit to the original maker of the drug, in this case “Glaxo.” We obtain this information from previous volumes

of the Orange Book: Approved Drug Products with Therapeutic Equivalence Evaluations, Physician’s Desk Reference, Billups Drug Index, and the Merck Drug Index. Secondly, we account for situations in which evaluation of a 5-year span is not possible. Some companies merged in succession within a short span of time. For example, Roche and Syntex merged in 1994, and only 3 years later, the resulting company merged with Corange. Post-merger data is not included for those situations because the effect of the “latter” merger cannot be distinguished from that of the first merger.13 Additionally, some mergers have occurred so recently that we are restricted in gathering post-merger data for these relatively recent mergers.14 Results We produce measures of innovation for all pre-M&A and post-M&A firms, determining the NME/NDA and the NME/year over a fiveyear period prior to M&A and a five-year period post M&A (with a few exceptions as described earlier). Since a post-M&A firm is theoretically composed of two precursor firms, we assume a post-M&A firm should produce on average twice as many NMEs (per firm) for the same time period as a pre-M&A firm if the merger had no effect on productivity. Therefore we divide the “NME/Year” measure by two to create a measure of productivity per company-year for postmerger firms. Table 1 presents the firm average for our two measures of innovation as well as the industry values for these measures in the pre- and post-M&A worlds. NME/NDA increases from pre-M&A to post-M&A firms, rising from 0.320 to 0.332 NME/NDA. This increase is not statistically sig-

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FEATURES nificant. There is insufficient evidence to declare a significant difference in NME/NDA in postM&A firms. Our second measure of innovation, “NME/ year,” declines from pre-M&A to post-M&A firms, falling from 0.437 to 0.277 NME/year. The t-statistic of 2.028 is greater than the critical value of 1.994 (α=0.05) and thus we reject the null hypothesis that there is no difference in the NME/ year for pre- and post-merger firms. This demonstrates that the total number of NMEs that firms produce falls post merger, below what would be expected for the aggregate of the two firms if they had not merged. To examine the entire industry, we aggregate the collective performance of all of the pharmaceutical firms in the pre-M&A and post-M&A worlds. Similar to firm average results, NME/ NDA increase while NME/year declines. For our analysis of innovation among approved drugs, we aggregate all NMEs and NDAs produced by all firms in the pre-M&A and post-M&A status respectively and calculated net NME/ net NDA. Productivity among drugs increases from 0.359 to 0.382 NME/NDA. For NME/year, we observe that productivity per year declines from 0.437 to 0.302 NME/year. Due to the aggregated nature of our figures, we are unable to perform a t-test for significance. Collectively, while we observe that the fraction of NMEs among NDAs increases, the output of NMEs per year falls. We next analyze the time trend of the research output of the pooled post-merger firms, to see if innovation might have risen over the five years, suggesting that the 5-year mean would misstate rising (or falling) research productivity. The bestfit line of relationship between NME/NDA and time was NME/NDA = -0.0049*year + 0.3234 with an R2 value of 0.0003. The slope coefficient is close to zero and the low R2 value reinforces the observation that it was the case of “love at first sight” for these mergers. Innovative productivity does not increase with time after a merger. Conclusion This study explores the dynamics between Mergers and Acqisitions in the pharmaceutical industry and the innovation of these firms. If M&As create economies of scale in research, through increased efficiency and output, one would expect to see rising research productivity in newly-merged firms. However, examination of firm innovation in its most straightforward form – the development of an NME – before and after a M&A finds no statistically significant evidence to support this claim. Our testing of the two measures of innovative productivity suggests that on average pharmaceutical firms do not increase their research output after merging with another firm.

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In addition, examining the industry as a whole in the pre- and post-M&A worlds, we observe that both measures of innovative productivity decrease for the post-merger period. These findings suggest that M&A in the pharmaceutical industry do not improve R&D performance. The authors benefitted from the excellent research assistance of Brian J. Raffetto References

1. Graves, Samuel B., and Nan S. Langowitz. “Innovative productivity and returns to scale in the pharmaceutical industry.” Strategic Management Journal 14, no. 8 (1993): 593-605. 2. Dimassi, Joseph A, “New Drug Innovation and Pharmaceutical Industry Structure: Trends in the Output of Pharmaceutical Firms.” Drug Information Journal, 34 (2000): 1169–1194. 3. Ornaghi, Carmine, “Mergers and Innovation: The Case of the Pharmaceutical Industry.” Discussion Papers in Economics and Econometrics, No. 0605 (2006). Available at http://www.socsci. soton.ac.uk/economics/Research/Discussion_Papers. Last accessed 27 April 2013. 4. Prabhu, Jaideep C., Rajesh K. Chandy, and Mark E. Ellis. “The impact of acquisitions on innovation: poison pill, placebo, or tonic?.” Journal of Marketing (2005): 114-130. 5. Comanor, William S., and F. M. Scherer. “Mergers and innovation in the pharmaceutical industry,” Journal of Health Economics 32 (2013):106-113. 6. United States Food and Drug Administration, Drug Approval Reports, http://www. accessdata.fda.gov/scripts/cder/drugsatfda/index. cfm?fuseaction=Reports.ReportsMenu (accessed on January 1, 2008) 7. United States Food and Drug Administration, Orange Book: Approved Drug Products with Therapeutic Equivalence Evaluations, available at http://www.accessdata.fda.gov/scripts/cder/ob/ default.cfm (last accessed 17 March 2013). 8. Ibid. 9. Physician’s Desk Reference. 42nd – 56th ed. (1988-2002) (Oradell: Medical Economics Company, Inc., and Montvale, NJ: Thompson Medical Economics Company, Inc.) 10. Billups (various years, 1988-2003) (St. Louis: Facts and Comparisons Division of Wolters Kluwer Co, (Philadelphia: J.B. Lippincott Company). 11. Merck Drug Index (various years, 1988-2002) Rahway and Whitehouse Station, Merck & Co., Inc. 12. The Merger Yearbook (2004). New York: Securities Data Co. 13. The following mergers occurred in such quick succession such that the full 5 years of post-merger data could not to be obtained for the first merger(s) described: American Home Products - Robins (1989) followed by American Home Products - Lederle (1994); Roche – Syntex (1994) followed by Roche Syntex – Corange (1997); Glaxo - Wellcome (1994) followed by Glaxo - SmithKlineBeecham (2000); Pharmacia - Upjohn (1995) followed by Pharmacia Upjohn - Searle (2000); Hoechst - Marion Roussel (1995) and Rhone Poulenc - Fisons (1995) followed by their merger together into Aventis (2000); Sanofi

- Synthelabo (1999) and Aventis (2000) followed by their merger into Sanofi - Aventis (2004); Pfizer - Warner Lambert (2000) and Pharmacia Upjohn - Searle (2000) followed by their merger together into Pfizer - Pharmacia (2002). We obtained as many years of post-merger data as possible given the restriction of the latter merger. For example, in the American Home Products – Robins merger of 1989, after the 3 year lag, 2 years of post-merger data was obtained until the American-Home Products – Lederle merger that occurred the following year 1994. Two additional mergers occurred so recently that the full 5 years of post-merger data was not available as of the date of this study: Sanofi-Aventis (2004), Yamanouchi-Fujisawa (2004), and UCB-Celltech (2004). 14. The following mergers have occurred so recently that that the full 5 years of post-merger data was not available as of the date of this study: Sanofi-Aventis (2004), Yamanouchi-Fujisawa (2004), and UCB-Celltech (2004). Image courtesy of Gerd Altmann via Pixabay

Alexander A. Maglunog received his bachelor’s degree in business economics from UCLA and is now studying medicine at the College of Medicine at SUNY Downstate Medical Center.

Stuart O. Schweitzer, Ph.D. is professor of Health Economics in the Department of Health Policy and Management of the UCLA Fielding School of Public Health. His research interests include pharmaceutical economics and policy, and industrial policy. In addition to his appointment at UCLA, he holds visiting appointments at the University of Ferrara (Italy) and Fudan University (Shanghai).

FEATURES Side Effects of Competition >>>Guy David, PhD, Sara Markowitz, PhD, and William Pajerowski The extent of pharmaceutical promotion can be characterized by a balancing act between profitable demand expansions and potentially unfavorable regulatory actions due to increased adverse drug reactions. However, this balance also depends on the nature of competition. In this paper we model the firm’s choice of promotion expenditures under different competitive scenarios and test the model’s predictions using a novel combination of sales, promotion, advertising, and adverse event reports data. We find that both own and competitors’ directto-consumer advertising expenditures may increase the incumbent firm’s share and number of adverse drug reactions, thus increasing the likelihood of unfavorable regulatory action.

he market for pharmaceuticals is one of the most highly regulated markets in the nation.1,2 The U.S. Food and Drug Administration’s (FDA) efforts to ensure their safety and efficacy in the pre-approval stage are frequently researched. However, very few studies have examined the effects of competition and promotion on patients’ demand and safety post-approval.3 In this paper we develop a model in which profit-maximizing pharmaceutical manufacturers choose the level of promotion (or advertising) expenditures, knowing that higher promotion (or advertising) expenditures raise sales but may trigger unfavorable regulatory actions against the firm. Regulatory action results when the expansion of prescriptions to users, who are poor matches for the drugs, leads to adverse health events. The model prediction regarding optimal levels of advertising is sensitive to the competitive situation at hand (monopoly versus oligopoly). The growth of pharmaceutical direct-to-consumer advertising (DTCA), along with recent regulatory interventions, motivates study of the relationship between competition, the promotion of drugs, and safety. This paper examines the market for erectile dysfunction (ED) drugs, a case which allows for tracking the dynamics of promotion and adverse event reporting as the market becomes more competitive. The market for ED drugs includes three competitors: Viagra (Pfizer), Levitra (Bayer) and Cialis (Lilly). Viagra was introduced in March 1998 and held monopoly position for five years, while Levitra and Cialis were introduced in August and November of 2003, respectively. There are several advantages for studying the market for ED drugs. Importantly, all three producers have extensive advertising and

promotion.4 In addition, it is not uncommon for consumers to experience adverse health events from ED drugs.5 Moreover, a long time series spanning 1998 through 2008 (five years pre-entry and five years post entry of Cialis and Levitra), the absence of competition from generic drugs, and the absence of brand-specific regulatory actions reduces the potential confounders and allows for a more credible identification of the effect of competition on safety. Patient safety represents an unexplored dimension of consumer welfare that is assumed away in standard welfare analysis in economics. Put differently, competition may have implications beyond the commonly known benefit on consumer surplus. Aggressive promotion of a pharmaceutical product may expand demand by attracting patients who are not a good match for the drug and are more likely to experience adverse drug reactions. This, in turn, may raise the likelihood of regulatory intervention by the FDA or litigation and internalization of the full costs of actions by pharmaceutical companies.6,7,8,9 Theory In this section we present a model where profit maximizing pharmaceutical manufacturers choose the level of advertising expenditures, knowing that higher advertising expenditures raise sales but may trigger unfavorable regulatory actions against the firm.a The model’s prediction regarding optimal levels of advertising is sensitive to the competitive situation at hand (monopoly versus oligopoly). In the case of oligopoly, it has long been recognized that advertising can have two types of effects on demand, either increasing general demand for the product or altering the distribution of consumers across brands within the

product category.10 The relative importance of these two effects depends on the marketing channel. DTCA is associated with increasing demand for the entire class, while promotion to physicians is associated with increased market share.11,12,13,b However, the effect of competition, advertising, and promotion on patient safety has received much less attention. Similar to the classic Dorfman and Steiner (1954) model of advertising, pharmaceutical firms in our model choose price and advertising expenditure simultaneously.16 Advertising expenditures operates as a demand shifter affecting quantity and its cost is deducted from the firm’s operational surplus. The firm maximizes the following expected profit function: where Q represents the quantity demanded as a function of own price P, own advertising expenditures A, as well as the vector of prices and advertising expenditures chosen by competitors, P-1 and A-1 respectively. Similar to Horowitz (1970), Dehez and Jacquemin (1975), and Brick and Jagpal (1981), who introduced uncertainty to the advertising framework, the pharmaceutical firm in our model maximizes expected profit by choosing price and promotion expenditures.17,18,19 However, the existing literature assumes that firms face exogenous uncertainty in the form of different states of demand, which the firm cannot influence. Following David et al. (2010) we relax this assumption by modeling w(A,A-1) as the probability of unfavorable regulatory action – an increasing function of both the firm’s advertising expenditures, A, and that of its competitors, A-1.9 For example, when a drug is withdrawn from the market, w=1 and the firm’s surplus is lost but the advertising expenditures are sunk. Thus, the firm faces uncertainty which it can mitigate or reinforce with its choice of promotion level. The resulting modified Dorfman-Steiner rule given by: Note that instead of advertising-to-sales

ratio on the left-hand side we have advertising-to-expected sales ratio. The first term on the right-hand side (in square brackets) is the Lerner Index, a measure for market power which for the case of monopoly is also inversely related to the price elasticity of demand, multiplied by the elasticity of advertising. In the case of monopoly, the Lerner Index equals 1 over the elasticity of demand, hencethis first term can be viewed as the ratio of

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FEATURES the elasticity of advertising to the elasticity of demand. The second bracketed term on the right-hand side is subtracted from the ratio of elasticities and is the product of three terms: (1) an increasing function in the probability of regulatory action, w (2) the elasticity of advertising to regulatory action, and (3) the profit-to-sales ratio. This expression includes the indirect effect of promotion on profits via the probability of regulatory action. In essence, increasing promotional activities trades off higher likelihood of profit-lowering regulatory actions with higher profits in the event that such regulatory action is not taken. Advertising-driven market expansion may have a negative effect on the quality of the match between the drug and its users and, in turn, can lead to regulatory actions against the firm.9 Advertising strategies are sensitive to competition because of the direct and negative impact that a competitor’s advertising can have on a company’s market share and sales.20 In our model, a rival’s advertising strategy may also affect the likelihood of regulatory action against the firm.c A monopoly can fully appropriate its advertising expenditures, but would also fully “appropriate” all regulatory actions that stem from advertising expenditure. On the other hand, firms operating under oligopoly are expected to strategically anticipate their competitors’ actions and incorporate these strategic responses when maximizing expected profits. Given the offsetting effect that advertising has on demand and regulatory action, advertising expenditures by rival firms may be strategic substitutes or strategic complements. Therefore, the effect that a switch from monopoly to oligopoly has on the advertising-to-sales ratio and ADRs remains an empirical question. Empirical Estimation We analyze the market for ED drugs to empirically examine the effects of advertising and promotion on Viagra’s number and share of reported adverse drug reactions (ADRs). We focus on Viagra’s outcomes since Viagra appears in both a monopoly (1998-July 2003) and a competitive (post-August 2003) setting. In analyzing the ADRs, we study current and lagged spending on own and competitors’ advertising and promotion. To estimate the effects of spending on ADRs, we use a monthly time series of data spanning 2002 to 2008. We test a simple equation where the outcomes are determined by current and lagged spending on DTCA and promotion and year and month dummies are used to capture unobserved trends.

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Total prescriptions are also included in the regression models to adjust for the market size where appropriate. We use ordinary least squares to estimate the coefficients. Current spending pertains to the current month, and lagged spending pertains to the remaining eleven months in the current year (months t-1 to t-11). The dependent variables used in the models below are measures of adverse drug reactions involving Viagra, Levitra, and Cialis. These data come from the FDA’s Adverse Event Reporting System (AERS), which was designed for postmarket drug safety surveillance. We use monthly counts of all adverse events ranging from very serious events (including death) to those that are far less severe. The AERS data suffer from some drawbacks including recall bias, poor case documentation, and underreporting.22 This is of concern only if the error is correlated with our independent variables of interest—dollars spent on advertising and promotion. Such measurement error is not likely to be correlated with dollars spent. We model ADRs as a function of dollars spent on DTCA and promotion, controlling for the number of prescriptions. Prescription data come from the IMS Health’s National Prescription Audit (NPA) database. Data on DTCA was collected by the TMS Media Ad$pender database (formerly Competitive Media Reports) beginning in 2002. We use total dollars spent per month on television, magazines, billboards, and internet advertising for the three drugs under consideration. Monthly data on professional promotion comes from IMS’s Integrated Promotion Ser-

vice (IPS). We use total dollars spent on professional promotion, which includes the cost of direct contact with physicians, journal advertising, and the retail value of samples. All spending is reported in real dollars. For advertising and promotion expenditures, we consider current month expenditures as a flow measure and the sum of expenditures for the previous eleven months (t-1 to t-11) as a measure of the existing stock of expenditures. The choice of number of months to use for the current period is not obvious since ADRs are reported throughout the month. It is therefore not clear that current month’s expenditures are appropriately matched to all observations. We tested models in which the flow measure includes both current and a one month lag, and results are similar. For the stock values we do not specify a depreciation rate, letting coefficients on the stock reflect the product of the marginal effect and the depreciation rate. We will interpret these coefficients accordingly. Results Table 1 (available in supplementary data on hhpronline.org) presents summary statistics by drug for the key variables. We report these for Viagra before and after entry by Cialis and Levitra. Viagra entered the market in March 1998, and by the end of the first quarter in 2000 had 2.7 million prescriptions filled. By the third quarter of 2003, immediately before entry by Levitra and Cialis, Viagra had 4.2 million prescriptions filled. The number of Viagra prescriptions fell after 2003. By 2008, Viagra’s market share was only 52 percent. Figure 1 shows total expenditures on

FEATURES DTCA and professional promotion by the three competitors. Our promotion data begins in 2002. Pfizer outspends its competitors in almost all periods shown, with the bulk of this spending going towards professional promotion. Spending on Cialis and Levitra tends to move together and is marked by a high initial promotional effort at entry, subsequent fall, and then moderate increase in 2006. Viagra’s spending falls during the early competitive years, and levels off or falls slightly for 2005 and beyond. While more volatile, the magnitude of expenditures on DTCA and professional promotion across drugs corresponds to their market share. Figure 2 shows the number of all reported adverse drug reports by year. While Viagra experiences the highest number of ADRs, all three drugs generally experience the same trends in ADR reports. There were two significant labeling changes made for all three drugs as the market grew more competitive: warning of the risks of sudden vision loss in July 2005 and warning of the risks of hearing loss in October 2007. A large decline in reported ADRs occurred after the first labeling change but not the second. Figure 2 shows the number of all reported adverse drug reports by year. While Viagra experiences the highest number of ADRs, all three drugs generally experience the same trends in ADR reports. There were two significant labeling changes made for all three drugs as the market grew more competitive: warning of the risks of sudden vision loss in July 2005 and warning of the risks of hearing loss in October 2007. A large decline in reported ADRs occurred after the first labeling change but not the second. Column 1 of Table 2 (available in supplementary data on hhpronline.org) presents empirical results for Viagra’s share of reported ADRs and uses data from August 2003 - December 2008 when all three drugs are on the market. The results show that Pfizer’s expenditures on professional promotion of Viagra is not associated with increases in its share of ADRs, while the stock of own expenditures on DTCA have a positive and statistically significant effect (column 1). Results in column 1 of Table 2 show that combined current month spending on professional promotion expenditures by Levitra and Cialis are positively associated with Viagra’s share of reported ADRs, but the effect is not significant at conventional levels. However, in models not shown, an increase in the stock of spending by Levitra alone is statistically associated with an increase in Viagra’s share of ADRs. The coefficients for combined DTCA by the competitors are also statistically insignificant and

reflect an average of a significant positive effect for Cialis and significant negative effect for Levitra reviewed in additional specifications. It is not clear why DTCA by Levitra would induce the opposite effect on patients’ match with the drug compared with DTCA by Cialis. The specification in column 1 is informative regarding the distribution of ADRs across the three ED drugs, but does not speak to the effects of advertising and promotion on the total number of ADRs reported. We address this in the rest of Table 2, where the dependent variable is the number of all Viagra ADRs mentioned as a primary or secondary suspect drug. We use a simple count rather than the rate since advertising and promotion can affect both the count of ADRs and the total number of prescriptions (the denominator in the rate). We do, however, include the number of prescriptions as a right-hand side variable in order to control for the prevalence of the drug in the population. The second column of Table 2 contains the same sample size (n=62) and variables as in the share estimates in column 1. We then increase the sample period to include the months before the competitors enter the market. The available data allows us to bring the series back to 2002, resulting in a sample size of 73 months. We present two different models using this expanded sample. In the first (column 3), Viagra’s own spending effect is assumed to be constant across the time series. In the second (column 4), we allow Viagra’s own spending effect to vary with the introduction of the competitors. That is, these models include variables representing current month spending, along with interactions between this spending and 1) an indicator variable for all months prior to August 2003 when Viagra had no competitors and 2) an indicator for August, September, and October of 2003 when Levitra was the only competitor. The current

spending variable can therefore be interpreted as the effects of Viagra’s own spending in the competitive market. This should be comparable to the restricted time sample in the second column. Current expenditures on professional promotion and DTCA for Viagra are both associated with increases in the number of ADRs, holding constant the number of prescriptions, but these results are not significant at conventional levels. Surprisingly, the magnitude of the current spending effects do not vary much between the models with and without the interactions (comparing columns 3 and 4), and the interaction terms themselves are statistically insignificant. This suggests that the own spending effects are constant throughout the changes in the market structure. Columns 2 through 4 of Table 2 also suggests that spending on promotion by competitors may influence the number of Viagra’s ADRs, however, the direction of the effects are a bit unclear as the current and stock values have opposite signs, and none are statistically significant. Considering that the stock value is likely subject to a discount rate resulting in a larger true effect and the magnitudes of the coefficients, the stock and current values are fairly close to each other and it is difficult to tell which will dominate. The effects of competitors’ DTCA show that an increase in the stock of DTCA increases Viagra’s number of ADRs. However, the negative coefficients on the current value of Levitra and Cialis’ DTCA may diminish the stock effect. But to dominate, this would require almost no discounting of the stock effect. We therefore conclude that competitors’ DTCA has deleterious effects on Viagra’s ADRs. Discussion This paper provides both the theoretical foundation and an empirical test comparing the

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FEATURES relationship between promotion activity and adverse events under monopoly and oligopoly. The theoretical predictions of the optimal level of advertising and related effects on ADRs depend on the market structure, and may change dramatically when entry occurs. Advertising under oligopoly treats each competitor as anticipating its rivals’ choices. Advertising in this setting is thus designed to achieve both increases in market size and in market share while decreasing risk of regulatory action. Our empirical analysis shows that spending on DTCA and promotion can result in increased adverse drug reactions, which has been shown to increase the probability of regulatory actions.9 In particular, DTCA by the incumbent brand (Viagra) increases its share and the number of ADRs, and the own spending effects appear to be constant throughout the changes in the market structure. Spending on DTCA and promotion by entrants may also increase the incumbent’s share and count of ADRs. In summary, since regulatory agencies are sensitive to post-marketing safety indicators, firms choose the level of advertising and promotional expenditures strategically. Like the drugs themselves, competition in the pharmaceutical industry has side effects. Beyond the well documented strategic interactions, like opportunities for free riding on rivals’ advertising and promotional campaigns, there is a potential spillover effect from rivals’ inappropriate market expansion in the form of increased reporting of adverse drug reactions. Notes

a. In the text “advertising” refers to all avenues of promotion and marketing available to the firm, including: direct-to-consumer advertising, direct-to-physician advertising (detailing), professional magazines ads, etc. b. The theoretical foundations consistent with these results can be found in 14,15. c. It is common in the pharmaceutical space that FDA actions stemming from an investigation of a specific drug are taken against the entire drug category.21

References

1. Towse, Adrian and Patricia Danzon. “Regulation of the Pharmaceutical Industry” in Handbook on Regulation, ed. Martin Cave. (Oxford: Oxford University Press, 2010). 2. Danzon, Patricia. “Regulation of the BioPharmaceutical Industry” in Encyclopedia of Law and Economics, ed. Edward Elgar. (2011). 3. Scherer, F.M. “The Pharmaceutical Industry” in Handbook of Health Economics, Vol. 1., ed. Joseph P. Newhouse. (Amsterdam: Elsevier, 2000). 4. Kim, Minki. “Physician Learning and New Drug Diffusion” Working Paper, University of Chicago, (2011). 5. Mayo Foundation for Medical Education and Research (MFMER). “Erectile dysfunction: Viagra and other oral medications.” June 6, 2012. http://www.mayoclinic.com/ health/erectile-dysfunction/MC00029. (accessed June 18,

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2013). 6. Chan, Tat, Chakravarthi Narasimhan, and Ying Xie. “Impact of treatment effectiveness and side-effects on prescription decisions: The Role of Patient Heterogeneity and Learning.” Available at SSRN 998324 (2007) 7. Narayanan, Sridhar and Puneet Manchanda. “Heterogeneous Learning and the Targeting of Marketing Communication for New Products.” Marketing Science 28(2009), 424-441. 8. Ching, Andrew and Masakazu Ishihara. “The Effects of Detailing on Prescribing Decisions under Quality Uncertainty.” Quantitative Marketing and Economics 8 (2010): 123-165. 9. David, Guy, Sara Markowitz, and Seth Richards-Shubik. “The Effects of Pharmaceutical Marketing and Promotion on Adverse Drug Events and Regulation.” American Economic Journal – Economic Policy 2 (2010): 1-25. 10. Waldman, Don E. and Elizabeth J. Jensen. Industrial Organization: Theory and Practice. 3rd edition. Prentice Hall, 2007. 11. Rosenthal, Meredith B., Ernst R. Berndt, Julie M. Donohue, Arnold M. Epstein, and Richard G. Frank. “Demand Effects of Recent Changes in Prescription Drug Promotion.” Forum for Health Economics & Policy: Frontiers in Health Policy Research 6 (2003): Article 2. 12. Iizuka, Toshiaki, and Ginger Z. Jin. “The Effect of Prescription Drug Advertising on Doctor Visits.” Journal of Economics & Management Strategy 14 (2005): 701 - 727. 13. Meyerhofer, Chad D and Samuel H Zuvekas. “The Shape of Demand: What Does It Tell Us about Direct-toConsumer Marketing of Anti-Depressants?” B.E. Journal of Economic Analysis and Policy: Advances 8 (2008). 14. Brekke, Kurt R and Michael Kuhn. “Direct to Consumer Advertising in Pharmaceutical Markets.” Journal of Health Economics 25 (2005): 102 - 130. 15. Linnosmaa, Ismo Erkii. “Advertising, Free-Riding, and Price Differences in the Market for Prescription Drugs.” B.E. Journal of Economic Analysis and Policy 8 (2008): Article 8. 16. Dorfman, Robert and Peter O. Steiner “Optimal Advertising and Optimal Quality.” American Economic Review 44 (1954): 826-836. 17. Horowitz, Ira “A Note on Advertising and Uncertainty.” Journal of Industrial Economics 18 (1970): 151-160. 18. Dehez, Pierre and Alex Jacquemin. “A Note on Advertising Policy under Uncertainty and Dynamic Conditions.” Journal of Industrial Economics 24 (1975): 73-78. 19. Brick, Ivan E. and Harsharanjeet S. Jagpal. “Monopoly Price-Advertising Decision-Making under Uncertainty.” Journal of Industrial Economics 29 (1981): 279-285. 20. Erickson, Gary M. “Advertising Strategies in a Dynamic Oligopoly.” Journal of Marketing Research 32 (1995): 233-237. 21. U.S. Food and Drug Administration (FDA). Center for Drug Evaluation and Research and Center for Biologics Evaluation and Research. Guidance for industry. Warnings and precautions, contraindications, and boxed warning sections of labeling for human prescription drug and biological products—content and format, 2011. 22. Institute of Medicine. The Future Of Drug Safety: Promoting And Protecting The Health Of The Public. Eds. Alina Baciu, Kathleen Stratton, Sheila P. Burke. Washington: The National Academies Press, 2007. 23. Newey, Whitney K; West, Kenneth D. “A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix.” Econometrica 55 (1987): 703–708.

Guy David, PhD is an Associate Professor in the Department of Health Care Management at the Wharton School, University of Pennsylvania, a Faculty Research Fellow at the National Bureau of Economic Research, and a Senior Fellow at the Leonard Davis Institute of Health Economics, University of Pennsylvania.

Sara Markowitz, PhD is an Associate Professor of Economics at Emory University and a Research Associate at the National Bureau of Economic Research. Dr. Markowitz’s research interests focus on the economics of healthy and unhealthy behaviors, with an emphasis on the health of children and adolescents.

William Pajerowski is a doctoral student in the Department of Health Care Management at the Wharton School, University of Pennsylvania. He received his BA in Economics from Tufts University in 2009 and previously worked as a research associate for L&M Policy Research.

FEATURES Health Insurance Expansions and Pharmaceutical Markets >>>Margaret E. Blume-Kohout, PhD and Neeraj Sood, PhD The Affordable Care Act (ACA) is expected to dramatically increase health insurance coverage in America. In this article, we draw lessons from another recent expansion of insurance – the Medicare Part D program that provides prescription drug insurance to Medicare beneficiaries – to examine how the expansion of health insurance under ACA will likely affect pharmaceutical markets. We consider the effects of insurance on pharmaceutical spending, innovation and marketing. We also highlight how the effects of ACA might differ from the effects of Medicare Part D due to differences in the demographics of the affected populations and specific provisions in the ACA.

he Affordable Care Act (ACA) is expected to dramatically increase health insurance coverage in America, providing coverage for some 27 million uninsured Americans. This increase in coverage will occur via three mechanisms. First, unmarried young adults will be eligible for health insurance as dependents on their parents’ health insurance policy until age 26. Thanks to this increase in the maximum age for eligibility, approximately three million young adults ages 19 to 25 are now covered.1 Second, in 2014 residents in some states – that is, states cooperating with Federal law – will become newly eligible for Medicaid coverage, due to higher income limits. Finally, the ACA will also provide subsidies for lower-income individuals and families to purchase insurance. The Congressional

Budget Office predicts that by 2022, as a result of these measures, about 12 million non-elderly individuals will be newly covered under public health insurance plans, and another 15 million will be newly covered under private insurance.2 In this article, we consider how this expansion in health insurance coverage is likely to affect markets for prescription drugs. We expect that, in the short run, the quantity of prescription drugs sold will increase, as newly insured consumers are likely to have lower out-of-pocket costs for both prescriber office visits and the prescription drugs themselves. However, this increase in use of prescription drugs may also have important long-term consequences for population health, government and total health care expenditures, and future medical innovations.

America’s recent experience with expansion of prescription drug insurance to Medicare beneficiaries – Medicare Part D – offers some insight. Reduction in hospital and outpatient spending Lower out of pocket expenses for prescription drugs and office visits can improve patients’ adherence to medication regimens and can also increase the number of patients initiating treatment. These changes in use of prescription drugs may improve health, consequently lowering medical spending. For example, better adherence to statin medications can lower patients’ cholesterol levels and prevent costly heart attacks and strokes in the future. Several recent studies have investigated whether the expansion of prescription drug coverage under Medicare Part D reduced medical expenditures by Medicare beneficiaries. One study compared changes in probability of hospitalization before and after implementation of Medicare Part D for persons aged 65 years and older (thus eligible for Medicare) versus individuals 60 to 64 years of age, and found the implementation of Medicare Part D reduced hospitalization rates by 4.1 percent.3 However, a similar study using individuals 55 to 63 as the comparison group found no significant reduction in emergency department usage or hospitalizations.4 Two other studies compared changes in medical spending before and after Medicare Part D among beneficiaries who had limited versus generous prescription drug coverage prior to implementation of Medicare Part D. These studies found that, among patients who started with little or no prescription drug coverage, their increase in prescription drug spending was essentially offset by reductions in other medical spending.5, 6 Similarly, among previously uninsured low-income individuals, expansion of health insurance appears to decrease both emergency department visits and inpatient admissions.7 Increase in pharmaceutical R&D In addition to affecting hospital spending, changes in prescription drug insurance can also profoundly affect the behavior of pharmaceutical firms. As before, the experience with Medicare Part D offers some insights into these “supply side” effects of insurance. Prior research shows that the implementation of Medicare Part D was associated both with increased utilization and expenditures for prescription drugs.8 This increase in demand for prescription drugs due to expansion of insurance might influence pharmaceutical firms’ R&D decisions through two pathways. First, increases in revenues for pharmaceutical firms imply increased cash flows, and prior re-

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FEATURES search indicates that increases in pharmaceutical firms’ short-run cash flows yield proportional increases in their R&D expenditures.9 Second, the expansion of insurance coverage under Part D combined with an aging population yields an expectation of greater use of pharmaceuticals in the future. This expectation of larger markets in the future could also encourage the pharmaceutical industry to increase its overall R&D expenditures, as larger markets imply greater expected returns to investment in developing and marketing new products. Blume-Kohout and Sood (2013) examine the effects of Medicare Part D on pharmaceutical R&D. In particular, they examine changes in firms’ R&D efforts before and after Medicare Part D for drug classes with higher versus lower Medicare market shares, expecting larger increases in R&D for drug classes with higher Medicare market shares.10 Indeed, they find that the passage and implementation of Medicare Part D yielded a significant increase in firms’ R&D activities for higher Medicare share drug classes, as measured by the number of drugs entering clinical trials. In addition, they find significantly stronger effects of Part D for “protected” drug classes. For protected classes – for example, antidepressants and antipsychotics – insurers generally must provide coverage for any marketed prescription drug, so they cannot use threats of exclusion from formularies to negotiate lower prices. This categorical protection, combined with the shift in coverage for “dual eligible” low-income beneficiaries from Medicaid to private Part D prescription drug plans, provided a windfall gain for firms manufacturing these drugs, as firms’ revenues from sales to these individuals were no longer subject to Medicaid price negotiations. Increase in pharmaceutical advertising Just like firms’ incentives to invest in R&D, incentives to invest in promoting or advertising pharmaceutical products might also be influenced by expansion of insurance coverage. Lakdawalla, Sood and Gu (2013) explore how and to what extent Medicare Part D influenced pharmaceutical advertising.11 Advertising can increase the number of persons using a pharmaceutical product through two channels. First, advertising can expand the size of the market by encouraging people to initiate treatment. Second, advertising can steal market share by switching treatment from a competitor’s product to one’s own product. Direct to consumer advertising expands sales primarily through

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encouraging consumers to initiate treatment and promotion to physicians, in the form of detailing visits, free drug samples and advertising in medical journals, increases sales by convincing physicians to switch prescriptions from a competitor product. Medicare Part D increased incentives for both of these forms of advertising as insured consumers provided greater profit, due both to their higher rates of brand-name drug utilization and better adherence to prescribed therapy. Thus firms’ expected returns from advertising are higher when there are more insured consumers in the market. In addition, insurance might increase incentives for direct to consumer advertising more than incentives for advertising to physicians. Consumers might be more likely to try a new drug after being exposed to advertising if they are insured and thus face lower out of pocket costs. Finally, the advertising effect of insurance is likely to be stronger in less competitive markets as returns to expanding the size of the market through advertising are larger when one faces fewer competitors. The empirical analysis by Lakdawalla, Sood and Gu (2013) confirms and quantifies these predicted relationships. They find that the implementation of Part D generated a 14% to 19% increase in total advertising expenditures, and consistent with economic

theory, this effect is concentrated in the least competitive drug classes. They also find relatively larger increases in direct to consumer advertising versus promotion to physicians. Why might the effects of the ACA differ from Part D? These recent empirical analyses of the effects of Medicare Part D on pharmaceutical markets are instructive, but there are several reasons that effects of the ACA might differ, due both to differences in the demographic distributions of the affected populations and due to specific cost-saving provisions in the ACA legislation. First, since much of the impact of the ACA is directed towards providing health insurance to previously uninsured individuals, we might anticipate significant reductions in hospitalizations and related inpatient medical costs, including reduced expenditures on medications that are typically used only in hospital inpatient settings. However, these cost offsets might be smaller for the younger and healthier populations covered by the ACA, as compared to the older population covered by the Medicare Part D expansion. Second, because – on average – the uninsured population is both younger and healthier than typical Medicare beneficia-

FEATURES ries, even under full insurance their use of prescription drugs would likely be much lower. As a result, the increase in firms’ expected revenues per capita would also be lower, and consequently should yield relatively smaller changes in firms’ spending on R&D and advertising. In addition, the ACA imposes new fees on manufacturers of branded pharmaceuticals, further reducing the impact of the insurance expansion on the bottom line of pharmaceutical firms. Third, the ACA is expected to lower pharmaceutical firms’ revenues from individuals and families covered under Medicaid, due to the mandated increase in rebates, or discounts, pharmaceutical firms must offer. Prior to the ACA legislation, pharmaceutical firms were required to offer discounts equal to at least 15.1% of the average price received for their branded or innovator drugs. The ACA increased this minimum rebate to 23.1%, and also expanded the rebate program to include drugs used by enrollees in Medicaid managed care organizations. In addition, to the extent that the ACA’s Medicaid expansion “crowds-out” or replaces existing employer-based health insurance coverage, firms’ revenues for individuals who switch from private insurance to Medicaid will also decline due to Medicaid’s mandated rebates and lower prices. This suggests the ACA may have the opposite effect from Part D for classes most heavily used by lowerincome individuals. That is, by increasing the number of people covered by Medicaid and decreasing the revenues firms receive for products used by Medicaid patients, the ACA may decrease R&D efforts for drug classes most heavily used by lowerincome individuals. If this occurs, it could potentially exacerbate health disparities in the long run. In conclusion, America’s experience with Medicare Part D suggests that insurance expansions can have important effects on the behavior of consumers and the behavior of private firms. In the short term, we expect the newly insured under the ACA will consume more health care, and this may prove a net benefit for society. However, in the long run, consumers’ and firms’ behavioral responses to their changed incentives under the ACA may have profound effects that resonate across the health care system, affecting not only the newly insured but all current and future users of health care. For example, changes in firms’ advertising strategies, such as an

increase in reliance on direct-to-consumer marketing nominally targeted at newly insured individuals, may spill over to affect drug utilization patterns across the entire health care system. Similarly, changes in firms’ expected returns on their investments in both R&D and advertising along with new fees tagged to innovator firms’ market shares, may impact both the industry’s distribution of R&D efforts across therapeutic classes and the overall level of R&D investment. Thus, the long-term effects of insurance expansions on health and health care costs might be quite different than the short term effects, and both ought to be considered in benefit-cost analysis of the ACA legislation.

9. Scherer, F. M. “The Link between Gross Profitability and Pharmaceutical R&D Spending.” Health Affairs 20, no. 5 (2001): 216-20. 10. Blume-Kohout, Margaret E., and Neeraj Sood. “Market Size and Innovation: Effects of Medicare Part D on Pharmaceutical Research and Development.” Journal of Public Economics 97 (January 2013): 327-36. 11. Lakdawalla, Darius, Neeraj Sood, and Qian Gu. “Pharmaceutical Advertising and Medicare Part D.” Journal of Health Economics (forthcoming). Image 1: Image courtesy of Women’s International League of Peace and Freedom. Image 2: Image courtesy of PolicyMed.Com

Sood acknowledges financial support for this work from the National Institute on Aging, Grant Number P01 AG033559 References

1. U.S. Department of Health and Human Services. Office of the Assistant Secretary for Planning and Evaluation. Number of Young Adults Gaining Insurance Due to the Affordable Care Act Now Tops 3 Million. By Benjamin D. Sommers, July 19, 2012, Washington DC. 2. Congressional Budget Office, CBO’s February 2013 Estimate of the Effects of the Affordable Care Act on Health Insurance Coverage, 2013, Washington, DC. 3. Afendulis, Christopher C., Yulei He, Alan M. Zaslavsky, and Michael E. Chernew. “The Impact of Medicare Part D on Hospitalization Rates.” Health Services Research 46, no. 4 (2011): 1022-38. 4. Liu, Frank Xiaoqing, G. Caleb Alexander, Stephanie Y. Crawford, A. Simon Pickard, Donald Hedeker, and Surrey M. Walton. “The Impact of Medicare Part D on out-of-Pocket Costs for Prescription Drugs, Medication Utilization, Health Resource Utilization, and Preference-Based Health Utility.” Health Services Research 46, no. 4 (Aug 2011): 1104-23. 5. Zhang, Yuting, Julie M. Donohue, Judith R. Lave, Gerald O’Donnell, and Joseph P. Newhouse. “The Effect of Medicare Part D on Drug and Medical Spending.” New England Journal of Medicine 361, no. 1 (Jul 2 2009): 52-61. 6. McWilliams, J. Michael, Alan M. Zaslavsky, and Haiden A. Huskamp. “Implementation of Medicare Part D and Nondrug Medical Spending for Elderly Adults with Limited Prior Drug Coverage.” JAMA : Journal of the American Medical Association 306, no. 4 (Jul 27 2011): 402-9. 7. Bradley, Cathy J., Sabina Ohri Gandhi, David Neumark, Sheryl Garland, and Sheldon M. Retchin. “Lessons for Coverage Expansion: A Virginia Primary Care Program for the Uninsured Reduced Utilization and Cut Costs.” Health Affairs 31, no. 2 (Feb 2012): 350-59. 8. Duggan, Mark, and Fiona Scott Morton. “The Effect of Medicare Part D on Pharmaceutical Prices and Utilization.” American Economic Review 100, no. 1 (Mar 2010): 590-607.

Margaret “Meg” Blume-Kohout, PhD is Assistant Professor of Economics and Senior Fellow of the Robert Wood Johnson Foundation Center for Health Policy at the University of New Mexico, and is an Affiliate Researcher of the New Mexico Consortium. Her research focuses at the intersection of science policy, health economics, and innovation.

Neeraj Sood, PhD is Associate Professor of Pharmaceutical Economics and Policy at the University of Southern California and Research Associate at the National Bureau of Economic Research. He is coeditor of the journal Forum for Health Economics and Policy. His research interests include innovation, insurance markets, HIV/AIDS and global health.

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STUDENT CONTRIBUTIONS Big Pharma’s Lobby: When Public Health and Profit Conflict >>>Jermaine Heath With increased political and economic attention being paid to healthcare policy in the United States, it makes sense to examine the role of one of the biggest players in the crafting of health policy - the pharmaceutical industry. Future implications of the relationship between PhRMA and the government are explored in terms of shaping the discourse on health policy, potential common sense regulations on pharmaceuticals, the possible inflation of drug prices and health care spending, as well as preserving the creditability of common diatribes that have long been debunked by many health policy experts.

he outsized and relatively unopposed influence of many large private industries have shaped the way medicine is practiced in the United States and how patients ultimately receive care. Despite the fact that the Affordable Care Act and its path to becoming law received almost non-stop coverage for months, significant changes to Medicare that would fundamentally affect American healthcare were signed into law many years before the Affordable Care Act – even four years before a similar experiment in healthcare became law in Massachusetts. Yet, when discussing the influence of private industry, we seem to focus primarily on the influence of private health insurers on health policy. Yes, the lobbying power of the health insurance industry may have very well killed the possibility of a public option, but some of the most important developments in 21st century health policy have been shaped by interactions with the pharmaceutical industry. So, why doesn’t the lobbying power of large pharmaceutical companies get similar if not more scrutiny? When thinking about how large pharmaceutical companies are able to amass and leverage influence when it comes to health policy, there are a few factors to keep in mind. Among these factors are the large amounts of money dedicated to lobbying government and shaping scientific dialogue, as well the benefit of public opinion being on the side of companies that produce life saving drugs. As alluded to earlier, the influence of “Big Pharma” was by no means unique to the Affordable Care Act. In 2003, as a part of the Medicare Modernization Act signed into law by President George W. Bush, Medicare Part D became law. Also known as the Medicare prescription drug benefit, this federal program was intended to subsidize the costs of prescription drugs for Medicare beneficiaries in the United States. In theory, this was a significant and sorely needed improvement

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in senior health care policy as seniors are more likely to depend on pharmaceutical drugs in order to treat various ailments and chronic diseases. However, while the bill was being drafted and debated in Congress, an interesting change in design was added to the final bill. Under the design of the Medicare Part D program, Medicare is not allowed to negotiate drugs prices with the pharmaceutical companies that make them. This was an especially odd development given the ability of many government agencies and programs to negotiate prices. For example, The Department of Veterans Affairs is allowed to negotiate drug prices and has been estimated to pay between 40%1 and 58%2 less for drugs, on average, than Medicare Part D. When thinking about how much market clout that Medicare would have with over 40 million enrollees and a large segment of the baby boomer population nearing retirement, it is an utterly mind-boggling situation from both a public health and a health economics perspective. According to economist Dean Baker of the Center for Economic and Policy Research in Washington, DC, allowing Medicare to negotiate drug prices could potentially yield a conservative estimate of $332 billion in savings between 2006 and 2013 (approximately $50 billion a year) and a “middle cost scenario” of $563 billion in savings.3 Thus, it would seem that there should be bipartisan opposition to this particular amendment preventing the negotiating of drug prices by Medicare. Looking at the role that the pharmaceutical lobby played in the passage of Medicare Part D can give insight into why the pharmaceutical industry currently wields so much influence in Washington. While the bill that would become the Medicare prescription drug benefit was being discussed in the House of Representatives, the lobbying power of the pharmaceutical industry became even more apparent. Former Republican Congressman Billy Tauzin, a former Deputy majority

whip and chair of the powerful House Committee on Energy and Commerce (which oversees the pharmaceutical industry) was instrumental in steering the bill through Congress with the lack of bargaining power for Medicare. According to fellow Republican representative Walter Jones, Mr. Tauzin used questionable tactics to get a bill through Congress with such a counterintuitive provision in it. In a 2007 interview with 60 Minutes’ Steve Croft, Rep. Jones recounts “The pharmaceutical lobbyists wrote the bill. The bill was over 1,000 pages. And it got to the members of the House that morning, and we voted for it at about 3 a.m. in the morning. I’ve been in politics for 22 years and it was the ugliest night I have ever seen in 22 years.” Rep. Jones and Representative Dan Burton, Republican from Indiana, tell many stories of “ugly arm-twisting” to save a bill that would have surely died at the hands of bipartisan opposition under typical House procedures during typical law-making hours on C-SPAN. Rep. Jones gives some examples: “We had a good friend from Michigan, Nick Smith, and they threatened to work against his son who wanted to run for his seat when he retired…I saw a woman, a member of the House, a lady, crying when they came around her, trying to get her to change her votes. It was ugly.”4 So why would a well respected House committee chair go to such lengths to ensure passage of a bill that many in his own party saw as an overly expensive expansion of a government program and that had Democrats up in arms over a bill that would normally have support from a liberal base? When looking back at the timeline of the bill, Mr. Tauzin retired just a few months after and took a $2 million a year job as president of Pharmaceutical Research and Manufacturers of America (PhRMA), the main pharmaceutical industry lobbying group. In addition, it was widely reported that then Medicare boss Thomas Scully both threatened to fire Medicare Chief Actuary Richard Foster for reporting the true cost of the bill and was simultaneously negotiating for a new job as a pharmaceutical lobbyist during debate of the bill.5 It would be overly simplistic to think that the political clout of the pharmaceutical industry is simply limited to the modern Republican Party. Returning to the impact of corporate lobbying on the final bill that became the Patient Protection and Affordable Care Act, it is also important to understand the importance of the pharmaceutical industry in the 2009 negotiations about the ACA. As Naomi Freundlich of the Century Foundation reminds us, then Senator Obama campaigned on the promise to take on the PhRMA lobby – especially when championing health reform – before succumbing to the

Student Contributions reality of governing as President in a polarized political climate. Freundlich recounts: “While campaigning for the presidency, Obama often spoke about taking on drug companies and allowing Medicare to have bargaining power over prices. He also supported the re-importation of cheaper prescription drugs from Canada as a way to lower healthcare costs. But in order to get Pharma support for the Affordable Care Act, these two measures were taken off the table and left out of the legislation.”6 Peter Baker of the New York Times confirmed last year that email correspondence between President Obama’s health care advisors and PhRMA indicated that the Obama administration would remove these two provisions on prescription drugs in exchange for pharmaceutical companies taking some tough medicine elsewhere in the legislation – with PhRMA lobbyists saying that they “got a good deal”.7 In fairness to both political parties, one could reasonably argue that expansion of prescription drug coverage and increased access to healthcare are significant accomplishments and worth the trade-offs. This could be especially true when considering that those health decisions had to be made in particular political environments as opposed to the theoretical world commonly associated with academia. Both administrations will probably remind health policy wonks of the role PhRMA – especially in terms of public relations - played in the death of the Clinton administration’s attempt at health reform. However, let us also remember that allowing Medicare to negotiate prices and allowing the legal importation of cheaper drugs from Canada are two of the most common and seemingly non-controversial ways to deal with increased healthcare spending. In fact, Gerard Anderson of Johns Hopkins University and Uwe Reinhardt from Princeton in their aptly titled paper, “It’s The Prices, Stupid: Why The United States Is So Different From Other Countries” suggest that the difference in spending is caused mostly by higher prices for health care goods and services in the United States.8 Yet, the influence of Big Pharma may even extend farther than the writing and crafting of legislation - this influence also helps to shape the dialogue around these issues and whether or not they are actually good or bad for the health of consumers. As documented on many occasions, it appears that the Food and Drug Administration, our main regulator dealing with matters of health, often finds itself at odds with Washington policymakers. While there have always been influences from industry on policymaking, it appears that even the regulation of drugs and the release of accurate and independent information has been subject to political winds.9 While the recent Avandia controversy is one of the more

high profile manifestations of this relationship between Big Pharma and the government , Dr. Ben Goldcare of the London School of Hygiene and Tropical Medicine makes it clear that any threat to an independent F.D.A and similar regulatory bodies can endanger public health, as it has been documented that pharmaceutical companies have a record of cherry-picking results and studies that support their products and understate potential risks for various populations.10 This is especially troubling as it becomes more common for the responsibility to run clinical trials and other safety tests to be given to the companies that are producing the drugs themselves. This makes it more likely that potential red flags will be missed before a drug hits the market and more likely that a recall will become necessary after preventable injuries or deaths. In addition to a powerful lobby and an ability to shape scientific dialogue around pharmaceuticals, it appears that large pharmaceutical companies benefit from relative positive public opinion. While some may take exception to the fact that these companies make money off the suffering of others, many others view the mass production of these pharmaceuticals as invaluable, life saving products. Former Congressman and former PhRMA president Billy Tauzin even publicly stated that the main reason that he took his position with PhRMA was the role that pharmaceuticals played in his battle with stomach cancer. Thus, large pharmaceutical companies are able to turn public opinion in their favor when stating their opposition to regulations and other laws that could have significant impact on their bottom line. Common refrains from the pharmaceutical industry is that many of these proposals would make it exorbitantly difficult to create and produce drugs, as well as stifle innovation in drug creation. In many ways, this fear-mongering gets support despite the drawbacks usually being overstated. In fact, other studies have confirmed that truly innovative drugs (especially for conditions that have no or limited treatment regimes on the market) largely come from smaller biotech firms and academic labs, with big Pharma responsible for less than half of those drugs while having a much larger share of the market.11 Thus, it would appear that we should be more critical and willing to scrutinize the positions of the pharmaceutical industry and the politicians they support. It could very well be just as important to human health as the pharmaceuticals themselves. References 1. Frakt, Austin B., Steven D. Pizer, and Roger Feldman. “Should Medicare adopt the Veterans health administration formulary?.” Health Economics

21, no. 5 (2012): 485-495. 2. Families USA. No Bargain: Medicare Drug Plans Deliver High Prices. January 2007. http://www.familiesusa.org/assets/pdfs/no-bargain-medicare-drug. pdf. (accessed June 18, 2013). 3. Stiglitz, Joseph. “The Price of Inequality.” New Perspectives Quarterly 30, no. 1 (2013): 52-53. 4. Singer, Michelle. “Under The Influence: 60 Minutes’ Steve Kroft Reports On Drug Lobbyists’ Role in Passing Bill That Keeps Drug Prices High.” CBS News. February 11, 2009. http://www.cbsnews.com/ stories/2007/03/29/60minutes/main2625305.shtml (accessed June 18, 2013). 5. Krugman, Paul. “The K Street Prescription” New York Times, January 20, 2006. http://query.nytimes. com/gst/fullpage.html?res=9B00E6DC123FF933 A15752C0A9609C8B63 (accessed June 18, 2013). 6. Freundlich, Naomi. “Using Medicare’s Clout to Negotiate Drug Prices—Did Obama Put That Back On The Table?” Health Beat. April 25, 2011. http:// www.healthbeatblog.com/2011/04/using-medicaresclout-to-negotiate-drug-pricesdid-obama-put-thatback-on-the-table/ 7. Baker, Peter. “Obama Was Pushed by Drug Industry, E-Mails Suggest.” New York Times, June 8, 2012. http://www.nytimes.com/2012/06/09/us/politics/emails-reveal-extent-of-obamas-deal-with-industryon-health-care.html?pagewanted=all (accessed June 18, 2013). 8. Anderson, Gerard F., Uwe E. Reinhardt, Peter S. Hussey, and Varduhi Petrosyan. “It’s the prices, stupid: why the United States is so different from other countries.” Health Affairs 22, no. 3 (2003): 89-105. 9. Harris, Gardiner. “White House and FDA often at Odds.” New York Times, April 2, 2012. http:// www.nytimes.com/2012/04/03/health/policy/ white-house-and-fda-at-odds-on-regulatory-issues. html?pagewanted=all (accessed June 18, 2013). 10. Goldcare, Ben. Bad Pharma: How drug companies mislead doctors and harm patients. London: Faber & Faber, 2012. 11. Kneller, Robert. “The importance of new companies for drug discovery: origins of a decade of new drugs.” Nature Reviews Drug Discovery 9, no. 11 (2010): 867-882.

Jermaine Heath is a biomedical engineering concentrator at Harvard College also pursuing a secondary in Global Health and Health Policy. He is interested in the decision-making process in healthcare and the political and financial environments that impact those decisions.

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Student Contributions Regulating the Direct to Consumer Genetic Testing Industry >>>Arifeen Rahman, Phebe Hong, Rebekka DePew, and Bernadette Lim Direct-to-consumer (DTC) genetic tests have been growing with minimal regulatory oversight since their inception. Major concerns for DTC tests include misleading advertising, questionable accuracy, and lack of professional interpretation of test results. In order to encourage the growth of direct-to-consumer testing in a safe environment for consumers and preempt a patchwork of conflicting state regulations, a clear federal regulatory framework should be established.

n June 2008, thirteen California companies received cease-and-desist letters in an attempt to regulate the burgeoning personalized genetic testing industry.1 Some of these companies offering direct-to-consumer (DTC) services, such as 23andMe, provide genetic testing for potentially fatal conditions like cystic fibrosis and breast cancer among over 100 additional diseases. Others, such as HairDX, test for traits as trivial as hair loss. The California investigations were sparked by an increasing inflow of consumer complaints and concerns about lack of physician interpretation of test results. The regulatory discussion surrounding directto-consumer testing reached the national level in 2010 when the Food and Drug Administration effectively halted Pathway Genomics from marketing personal genetic testing kits in Walgreen’s without prior clearance.2 Despite

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similar actions sporadically enacted by the FDA over the last three years, the DTC industry has continued to grow in a functionally unregulated environment. However, both these separate incidents, and the growing literature on the risks of DTC testing, demonstrate the pressing need of a clear regulatory framework for direct-toconsumer genetic testing. Without appropriate professional interpretation of results, patients are in danger of misdiagnosis and overestimation of risk.3 As costs of genetic tests continue to plummet, accessibility of personal genetic tests increase and the impact of these risks multiply. The controversy over direct-to-consumer testing emphasizes the clash of conflicting interests between public health officials, forprofit companies, and concerned consumers. Personalized medicine is still in its infancy, but the days of individual treatment based on one’s own

genes are not far off.4 As the vision of personalized medicine becomes a reality, the growing interest of patients to interpret their genomic identity outside of a clinical setting must be considered. A holistic consideration of the harms, benefits, and regulatory policy is necessary in order to ensure that the field of genetic testing remains safe for both the consumer and patient alike. Benefits of DTC Despite numerous associated concerns, direct-to-consumer genetic testing is a valuable enterprise. One potential benefit of personal genetic testing is that it will motivate patients to enact positive lifestyle changes and improve their overall health.5 Most diseases are influenced not only by genetics, but also by the patient’s environment and the interaction between the environment and the patient’s genes. Due to the importance of the environment, this selfmotivated consciousness for improving diet and exercise, for example, can have a significant impact on the health of consumers. Additionally, individuals should have the right to obtain their genetic information if they so choose, and directto-consumer genetic testing companies offer a means of access.6 Lastly, DTC companies have access to large genetic data sets from the population to conduct privately funded analysis and research.7 For example, 23andme conducted one of the largest genome wide association studies on myopia, using customers’ genetic data and survey responses to find novel genetic associations.8 However, despite these basic benefits, there re-

Student Contributions mains much concern over the potential harm of direct-to-consumer genetic testing. Harms of DTC One of the largest concerns with these tests is that consumers will be misled by false or excessive advertising. Issues in advertising of genetic tests include a lack of thorough information, over-emphasis of the benefits rather than the limitations of genetic tests, and failure of advertisements to promote practices that are most beneficial for the patients.9 In a study of the thirteen companies who offered DTC genetic tests and advertised these tests online, Berg and Fryer-Edwards found that the amount of information available to consumers before they order a genetic test is troubling.10 They concluded that patients are not presented with enough information to fully understand the benefits and limitations of the test. Additionally, ubiquitous oversimplification in genetic testing advertisements for high risk diseases such as cancer could result in significant psychosocial impacts for the consumer.11 Furthermore, advertisements tend to highlight the benefits of the test and gloss over the limitations. For example, one commercially available genetic test claims to predict the likelihood that an individual will develop cardiovascular disease, and fails to mention the heavy influence of environmental factors such as lifestyle and diet.12 Additionally, consumers are often uncertain about the accuracy of their test results. In an investigation by the Government Accountability Office, one consumer sent genetic samples to four different companies and received contradictory results from each, attaining a low, medium and high risk of cancer.13 The clinical validity of genetic tests can be assured if it meets the standard of a ‘medical device’ under the FDA. Currently, the Clinical Laboratory Improvements Act (CLIA) of 1998 regulates all laboratories conducting clinical tests with certain standards for validity and quality. However, not all DTC genetic tests are performed in CLIA certified laboratories, and there is no requirement to do so currently.14 Therefore, the analytical validity of several tests is questionable. Furthermore, the interpretation of the genetic test results absent a health professional’s guidance is concerning. The DTC model inherently circumvents approval from a physician, and could result in patients never consulting their physicians about the results of the tests. Talking to a physician could lower the likelihood of psychological distress upon receiving the results of a genetic test.15 Even more concerning is the lack of referral to genetic counseling to help consumers interpret the results of the tests, in spite of the fact that genetic counseling has been shown to

decrease the amount of anxiety associated with a positive result of a genetic test. 16,17 Genetic counseling services are currently greatly underutilized in the interpretation of DTC tests even though consumers who consult counselors have beneficial experiences.18 Yet, in a survey of members of the National Society of Genetic Counselors, a majority of respondents felt an obligation to be knowledgeable about DTC testing, and a significant proportion perceived a responsibility to help in the interpretation of results.19 Regulatory Policy In order to resolve these concerns, a clear regulatory framework should be implemented for DTC genetic testing on the federal level. Several different agencies will be required to cooperate in such a plan, including the Federal Trade Commission (FTC), the Food and Drug Administration (FDA), and the Center for Medicare and Medicaid Services (CMS). First, advertising issues must be directly addressed by the Federal Trade Commission (FTC) which is largely responsible for protecting consumers against unfair trade practices. It has not yet taken action against misleading advertisements by genetic testing companies.20 Investigation of misleading claims has been empirically proven to be effective in decreasing false advertising.21 The Federal Trade Commission should take a stronger role in enacting strict enforcements on advertising for DTC companies and create clear guidelines for the scope and limitations of DTC tests that currently exist for pharmaceutical drugs.22 By placing an emphasis on the regulation of the misuse of genetic testing, the current negative perception of direct-to-

consumer testing can be dissipated. Second, the analytical validity of personal genetic tests must be established. Although the Clinical Laboratory Improvement Act (CLIA) currently requires proficiency testing for laboratories in order to ensure the analytical validity of complex tests, there is currently no “specialty” for molecular and genetic testing. Therefore, specific proficiency testing is not mandated under the CLIA.23 Though it was proposed in 2000 that the CLIA should implement stricter regulation over genetic testing, no such revision has undergone approval. It is imperative that stricter control of testing is established through a specialty area for genetics that is regulated by CMS, and implemented in order to ensure the accurate interpretation of genetic tests. Additionally, all genetic testing should be required to be conducted in CLIA certified laboratories. Lastly, the interpretation of results should be mediated by health professionals. Specifically for cardiovascular testing and other complex diseases, a physician is best placed to interpret tests due to the contextual importance of family history and current medical factors.24 Some direct-to-consumer testing companies have altered their model to work through physicians, such as Pathway Genomics after it received the 2010 warning from the FDA. However, at minimum, genetic tests should be interpreted by genetic counselors provided by the company. The more complex the disease is, the more crucial it is that the consumer receives counseling. However, currently 95% of all companies offering DTC tests offer neither pre-test nor post-test counseling.25 Therefore, the FDA should mandate that all DTC genetic tests which claim

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Student Contributions to give medically relevant information should be interpreted via genetic counselors. Excluded from this mandate would be “recreational” tests such as finding out ancestry or other traits with no direct relation to health. Discussion A coherent regulatory framework for directto-consumer genetic testing would ensure accurate advertising, accuracy and analytical validity of tests, and professional interpretation of results by a genetic counselor. While proponents of an unregulated DTC genetic testing industry argue that the industry will be limited by federal regulation, the opposite may be true. Currently, companies offering direct-toconsumer genetic tests must comply with a patchwork of state regulations that widely vary. For example, the state of New York requires both direct involvement by a physician and the testing to be conducted by laboratories licensed by the state of New York. Additionally, several states ban direct-to-consumer genetic testing altogether.26 As a result, a stable regulatory environment would provide a coherent basis for direct-to-consumer testing companies to safely expand and grow. Unraveling the genetic basis for disease at the personal level has great promise, but only if pursued with great caution. References

1. Wadman, Meredith. “Gene-testing firms face legal battle.” Nature 453, no. 7199 (2008): 1148. 2. Shur, Natasha. “Hope, Hype, and Genotype: Genetic Testing in Dermatological Diseases” in Dermatoethics,197-204, (London: Springer, 2012) 3. Croyle, Robert T., and Caryn Lerman. “Risk communication in genetic testing for cancer susceptibility.” JNCI Monographs 1999, no. 25 (1999): 59-66. 4. Katsanis, S. H., G. Javitt, and K. Hudson. “Public health. A case study of personalized medicine.” Science 320, no. 5872 (2008): 53-54. 5. Bansback, Nick, Sonia Sizto, Daphne Guh, and Aslam H. Anis. “The Effect of Direct-to-Consumer Genetic Tests on Anticipated Affect and Health-Seeking Behaviors: A Pilot Survey.” Genetic Testing and Molecular Biomarkers 16, no. 10 (2012): 1165-1171. 6. Genetic Alliance. Promotion of Genetic Testing Services Directly to Consumers. http://www.geneticalliance.org/issues.testing.consumers (accessed June 18,2013). 7. Annes, Justin P., Monica A. Giovanni, and Michael F. Murray. “Risks of presymptomatic direct-to-consumer genetic testing.” New England Journal of Medicine 363, no. 12 (2010): 1100-1101. 8. Kiefer, Amy K., Joyce Y. Tung, Chuong B. Do, David A. Hinds, Joanna L. Mountain, Uta Francke, and Nicholas Eriksson. “Genome-wide analysis points to roles for extracellular matrix remodeling, the visual cycle, and neuronal development in myopia.” PLoS genetics 9, no. 2 (2013): e1003299. 9. Gray, Stacy, and Olufunmilayo I. Olopade. “Directto-consumer marketing of genetic tests for cancer: buyer beware.” Journal of Clinical Oncology 21, no. 17 (2003): 3191-3193. 10. Berg, Cheryl, and Kelly Fryer-Edwards. “The ethical challenges of direct-to-consumer genetic testing.” Journal of

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Business Ethics 77, no. 1 (2008): 17-31. 11. Gray, Stacy, and Olufunmilayo I. Olopade. “Directto-consumer marketing of genetic tests for cancer: buyer beware.” Journal of Clinical Oncology 21, no. 17 (2003): 3191-3193. 12. Ibid 13. Direct-to-consumer genetic tests: misleading test results are further complicated by deceptive marketing and other questionable practices. 110th Cong. 2003. (Statement of Gregory Kutz, Managing Director, Forensic Audits and Special Investigations). 14. Wright, Caroline F., Alison Hall, and Ron L. Zimmern. “Regulating direct-to-consumer genetic tests: what is all the fuss about?.” Genetics in Medicine 13, no. 4 (2010): 295300. 15. Berg, Cheryl, and Kelly Fryer-Edwards. “The ethical challenges of direct-to-consumer genetic testing.” Journal of Business Ethics 77, no. 1 (2008): 17-31. 16. Ibid 17. Butow, Phyllis N., Elizabeth A. Lobb, Bettina Meiser, Alexandra Barratt, and Katherine M. Tucker. “Psychological outcomes and risk perception after genetic testing and counselling in breast cancer: a systematic review.” Medical Journal of Australia 178, no. 2 (2003): 77-81. 18. Darst, Burcu F., Lisa Madlensky, Nicholas J. Schork, Eric J. Topol, and Cinnamon S. Bloss. “Perceptions of Genetic Counseling Services in Direct‐to‐Consumer Personal Genomic Testing.” Clinical Genetics (2013). 19. Hock, Kathryn T., Kurt D. Christensen, Beverly M. Yashar, J. Scott Roberts, Sarah E. Gollust, and Wendy R. Uhlmann. “Direct-to-consumer genetic testing: an assessment of genetic counselors’ knowledge and Their beliefs.” Genetics in Medicine 13, no. 4 (2011): 325-332. 20. Williams, Shawna, and Gail Javitt. “Direct-to-Consumer Genetic Testing: Empowering or Endangering the Public?.” (2006). 21. Wright, Caroline F., Alison Hall, and Ron L. Zimmern. “Regulating direct-to-consumer genetic tests: what is all the fuss about?.” Genetics in Medicine 13, no. 4 (2010): 295-300. 22. Gray, Stacy, and Olufunmilayo I. Olopade. “Directto-consumer marketing of genetic tests for cancer: buyer beware.” Journal of Clinical Oncology 21, no. 17 (2003): 3191-3193. 23. Williams, Shawna, and Gale Javitt. “Direct-to-Consumer Genetic Testing: Empowering or Endangering the Public?.” 24. Lockwood, Christina M. “Direct-to-Consumer Cardiac Screening Tests: User Beware.” Clinical Chemistry 58, no. 6 (2012): 1068-1069. 25. Lovett, Kimberly M., Timothy K. Mackey, and Bryan A. Liang. “Evaluating the evidence: direct-to-consumer screening tests advertised online.” Journal of Medical Screening 19, no. 3 (2012): 141-153. 26. Genetics and Public Policy Center. Survey of directto-consumer testing statutes and regulations. Last updated June 2007. http://www.dnapolicy.org/resources/ DTCStateLawChart.pdf (accessed June 18,2013).

Phebe Hong is a rising sophomore at Harvard College in Eliot House. She is interested in health economics, genetics, and the intersection between policy and science.

Rebekka DePew is a rising sophomore in Quincy House concentrating in Engineering. She is interested in studying how policy can address healthcare inequalities.

Bernadette Lim is a freshman hailing from Los Angeles, CA. Her interests in health policy include maternal and child health, biotechnology, and urban health. She is also interested in international healthcare innovation through social entrepreneurship. Ultimately, she hopes to have a future career in both international and domestic health policy and community organizing through a clinical and entrepreneurial perspective.

Image 1:Image courtesy of MIKI Yoshihito via Flickr Image 2: Image courtesy of Caroline Davis via Flikr

Arifeen Rahman is a rising sophomore at Harvard College in Winthrop House. She is a member of the editorial board for the Harvard Health Policy Review.

Student Contributions Pharmaceutical Pollution of Water in India: International Market Failure >>>Annie Ryu

India is the world’s third largest manufacturer of pharmaceuticals; supplying over 65 countries, the industry derives over 50% of its revenues from exports. Pharmaceutical pollution of water in India demonstrates international market failure, as the costs of the pharmaceuticals do not account for the vast environmental and human costs of production. The pollution problem has been scientifically documented internationally and protested locally, but state and national governmental authorities are failing to enforce regulations. Today, impoverished villagers in industrial areas in India are most harmed, yet the potential for the spread of drug resistance is an international threat. Pharmaceutical pollution of water in India demands international attention and policy change.

harmaceutical pollution of water in India rushed to international attention in 2007, when a Swedish research team revealed that pharmaceutical levels in water downstream of a wastewater treatment plant in Patancheru, Andhra Pradesh, India were 150 times the highest levels in the U.S. Environmental and human harms of such pollution are extensive, leading to disease, destitution, disenfranchisement, and, in some cases, protest. Meanwhile, regulatory institutions deny claims and shirk their responsibility to enforce regulations. The international context is crucial for understanding the widespread devastation wrought by pharmaceutical pollution of water in India and how this devastation might be halted. India’s pharmaceutical industry has emerged as the world’s third largest in terms of volume of production.1 As India’s leading science-based industry, the pharmaceutical industry contributes 1% of India’s total GDP.2 International demand drives the continued rapid expansion of the industry: it supplies over 65 countries and derives over 50% of its revenue from exports.3 India is a preferred manufacturing location, primarily because of its comparative cost advantages.2,3 The Indian pharmaceutical industry’s largest customer is the US, which spent $1.4 billion on Indianmade drugs in 2007.4 This article first explains the ways in which pharmaceuticals enter water supplies, the regulations surrounding the treatment of effluents, and the challenges in monitoring this treatment. The article then describes the scientific documentation pharmaceutical pollution, the human harms of the pollution, and the protests that have erupted in Patancheru but have been met with governmental inaction. The final section explores the international im-

plications of pharmaceutical pollution of water in India. How Pharmaceuticals Enter Water Pharmaceuticals enter water through multiple pathways. Pharmaceuticals can enter water supplies and soil after humans and animals excrete the pharmaceutical compounds: compounds in human excretion may pass through sewage treatment plants (STPs) and then enter surface water; compounds in animal excretion may enter surface water by joining agricultural runoff, or enter groundwater by seeping through the soil.5 Pharmaceuticals can also enter water when patients, healthcare organizations, or pharmaceutical companies dispose of unused pharmaceuticals, and when pharmaceuti-

cal companies dispose of toxic wastes generated during production. Pharmaceutical companies in the US and Europe are subject to the most advanced and comprehensive waste-treatment directives in the world.6 The manufacture, use, and disposal of each drug are extensively reviewed to ensure patient and environmental safety. Healthcare facilities and medical waste disposal firms employ incinerators, and sewage treatment plants use thermal processing and technologically advanced water treatment techniques to extract active wastes and detoxify active ingredients.6,7 In contrast, many pharmaceutical companies and other industries in India discharge treated and untreated effluents on open land and into unlined streams.8 Local and State-Level Regulations and Complexities in Monitoring The regulations and regulatory institutions relevant to pharmaceutical pollution in India have existed since the 1970s and 1980s, when India began its rapid industrialization. The 1974 Water Act established the Central Pollution Control Board (CPCB) and the State Pollution Control Boards (SPCBs), and the 1977 Water Cess Act provided these national and state boards with the option to tax water users violating regulations.9 In 1985, the National River Conservation Directorate (NRCD) was established under the national government’s Ministry of Environment and Forest to coordinate river conservation plans, which focused on mitigating pollution through the establishment of Individual and Common Effluent Treatment Plants (CETPs). CETPs are sites for centralized treatment of the combined effluent from many

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Student Contributions

small-scale industries. In 1989, the CPCB issued the Minimum National Acceptable Standards (MINAS) that the SPCBs are required to enforce for the pharmaceutical industry.9,10 The SPCBs have the authority to close companies that fail to comply with the Water Act, to cut the companies’ water and power supplies, or to pursue public interest litigation before the Supreme Court.9 The high degree of fragmentation in India’s pharmaceutical industry and the wide diversity among the pharmaceuticals manufactured complicates effective effluent treatment and monitoring. The industry has approximately 300 large-scale and 8000 small-scale units, producing several thousand formulations of 350 different bulk drugs.2 Big firms typically manage their effluents effectively; small and medium enterprises often resort to dumping effluents on nearby land and water bodies because they do not undertake the proportionally large investment needed for effective effluent treatment.11 Large enterprises contribute to this pollution by hiring small companies for production when anticipating effluent production beyond permissible limits. Meanwhile, the uniqueness of each drug’s manufacturing process compounds the pollution problem by increasing the difficulty

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of effective treatment. Reasons for inefficacy of a treatment plant include use of inappropriate treatment for the nature of the effluent due to change in pharmaceutical production and effluent input characteristics.11 Documentation of the Problem Documentation of the problem of pharmaceutical pollution of water has been scarce relative to the magnitude of the problem. Reporters and publications considering critiquing industry practices face threats from industry and typically remain quiet. Some reporters publish articles anonymously once practices have already become public, as through the recording of a violation. The Patancheru industrial area has been the most popular subject for scientific study of water pollution in India and thus provides a case study. To the knowledge of the author, no research has formally assessed the health impact of pharmaceutical pollution or, more generally, of water pollution in this area. Nonetheless, the results of scientific studies have been clear and astounding. Patancheru is known as one of India’s most water polluted areas.12 In 1989, 110 of the area’s industries jointly established a common effluent treatment plant (CETP), Patancheru Enviro

Tech Ltd. (PETL). Ninety of the industries that the plant currently serves are bulk drug manufacturers.13 PETL currently operates far below its maximum quantity capacity because small and medium firms have been unwilling to pay PETL’s charge per tanker and the transportation and waste pre-treatment costs.11 Meanwhile, the plant is not equipped with the full range of technologies needed to treat the diverse effluents it receives, such that even its incompletely treated products compound the pollution problem.14 Pharmaceutical contamination of Patancheru’s waters received dramatic news coverage internationally when a Swedish research team’s 2007 publication revealed that pharmaceutical levels in water downstream of PETL were 150 times the highest levels in the U.S.4,13-18 Yet, scientific documentation of extensive pollution in Patancheru’s waters dates back to 1995, if not earlier: Shivkumar and Biksham (1995) found total dissolved solids (TDS), biochemical oxygen demand (BOD), chemical oxygen demand (COD), and concentrations of Cu, As, Se, F, and Fe to be 5 to 10 times more than permissible limits.19 A 1999 study conducted by four researchers from the National Geophysical Research Institute, Hyderabad, documented extensive groundwater pollution and over-exploitation of groundwater and called for reduction of effluent concentrations in wastewater released from individual industries and from CETPs.20 Two of these researchers conducted a follow-up study in 2001, noting high concentrations of ions indicating the impact of industrial effluents. They proclaimed that the ground water quality in and around Patancheru, to a depth of thirty meters, “has become hazardous.”21 Their recommendations were the following: “stop all permits for the establishment of new industries,” “require industries to treat the effluents properly,” “limit large-scale groundwater pumping along the river courses in order to minimize the migration of contaminants,” “establish more Common Effluent Treatment Plants designed to treat the specific characteristics of the waste effluents,” “adopt stringent measures for strict adherence to environmental protection laws,” and “conduct programs to inform the rural population of the conditions of environmental pollution.” Yet, eight years after the release of these recommendations, Larsson and colleagues conducted their 2009 follow-up study and found “the previously demonstrated release of pharmaceutical residues still occurring.”22 Human Consequences Studies of the human impacts of pharmaceutical pollution in India are particularly scarce, but the negative consequences for health and

Student Contributions livelihoods are dramatic. More than 21,000 people in twenty-two villages have been directly affected by pharmaceutical firms’ dumping of toxic wastes in Patancheru.2 Pharmaceutical pollution of water directly harms the health of persons who use the polluted water for drinking and washing and indirectly harms health by devastating livelihoods—dramatically reducing the agricultural productivity of the land, harming agricultural infrastructure, and leading to massive death of livestock and fish.12,23 A study conducted by Greenpeace in 2004 recorded that the pollution contributes to respiratory disorders, cancers, reproductive problems, chronic depression, and congenital problems including mental retardation and physical abnormalities.24 A local doctor, A. Kishan Rao, reported “very strange cases,” including a baby born without eyeballs.25 Villagers reported human morbidity, crop declines, and livestock deaths, and attributed these impacts to local industrialization.24 Of a village downstream of PETL, economic development researchers noted, “the entire village” “has been suffering from various diseases arising out of water pollution,” including skin infection, teeth corrosion, joint pain, defective vision, and abdominal pain, and when serious disease strikes a family’s chief income earner, the family’s economic conditions deteriorate.26 In this village, forty-five hectares of cultivable land had become uncultivable by 2005 due to soil pollution caused by irrigation with polluted water.27 In multiple if not all of the villages in the area surrounding PETL, there is not enough municipal water to meet livestock’s needs in addition to humans’ drinking water needs, so livestock depend instead upon polluted local water bodies. In and around the Patancheru area, over 1000 animals have died from consuming toxic water and contaminated grasses, and millions of fish have died due to pollution in fisheries.12 Some cows have lost their reproductive capacities.27 Fearing further cattle deaths, many owners have sold off their cattle at very low prices.27 Persons who are poor, of low education, and of low caste are those most harmed by pharmaceutical pollution. The poor are most spatially proximate to concentrations of polluting industries, as these industries bought land at minimal prices from the poor and persons who could find economic opportunity elsewhere or otherwise afford to move have done so to avoid the harms of pollution. Basic public drinking water services may not extend to these villages in the industrial area. The livelihoods most harmed— those based on agriculture and fishing—are disproportionately the livelihoods of members of low castes who lack access to education.27

Local Protests and Governmental Denial and Inaction As industries keep waste dumping a secret and offer compensation for cattle deaths so that farmers will not further pursue cases,2 widespread repression of information about these events prevents the many who have suffered harm from recognizing the power in their numbers. The isolated protests that have taken place against industrial pollution have encountered governmental denial and inaction. In the 1980s, an environmental movement emerged to protest the dumping of industrial waste in the Patancheru area.12 With the leadership of a local physician and social activists prominent in the area, the Patancheru Anti Pollution Committee (PAPC) organized hunger strikes and other protests and submitted a memorandum of demands to then Chief Minister Sri N. T. Rama Rao. In response to continuous pressure, the district administration served notice to twenty-two industries. These industries then approached High Court and gained six months’ time to install individual effluent treatment plants (ETPs). However, when the deadline passed, none of the industries had taken any steps to establish an ETP.12 In response to a road blockade organized by PAPC action groups and after five years of deliberation, the Supreme Court ordered the National Environmental Engineering Research Institute (NEERI) Nagpur, to study the impact of industrial pollution in the Patancheru area. The report, released in 1990, suggested a compensation of 32.22 crores rupees ($58.6 million) to be paid to the affected persons over an eight-year period and ordered the immediate stoppage of effluent flow into water bodies, the provision of drinking water to affected villages, the rectification of the CETP, and the provision of medical care to pollution victims. According to activists, a mere 2.13 crores rupees ($0.39 million) have been disbursed to families in ten of the affected villages;24 the other directions of the judiciary have been carried out minimally if at all.12 Today, villagers continue to suffer, and environmentalists say Andhra Pradesh Pollution Control Board (APPCB) simply doesn’t care.27 In 2009, the APPCB counsel submitted an action taken report (ATR) stating that the APPCB had made industries adhere to strict pollution control measures and successfully reduced pollution levels in the area, and a pharmaceutical company was allowed to continue operating units that it had earlier been ordered to close.28 It was also in 2009 that Larsson’s Swedish research team conducted their follow-up study and found that the astoundingly high levels of pharmaceutical contamination in waters down-

stream of PETL remained unchanged. International Implications As countries around the world continue to source cheap pharmaceuticals from India, pharmaceutical pollution of water in India demonstrates international market failure, as the cheap selling prices of the pharmaceuticals do not account for the vast environmental and human costs of production. In extensive online communications with this article’s author, Dr. S. Jeevananda Reddy, Convenor of the Forum For A Sustainable Environment and former Chief Technical Advisor for World Meteorological Organization and the United Nations, presented his views on what it will take to halt the pharmaceutical pollution of water in Patancheru. He asserted that industries found producing in excess of the allowed quantity of wastes must be closed permanently, that officials found collaborating with industries must be dismissed, and that CETPs must be made to treat effluents according to regulations. Yet, topping his list was the following: “As most of the products are produced for export, the buying agencies must stop buying from industries with polluting history.” With similar views, Dr. Larsson has given a TED talk discussing international culpability and responsibility for the damages of pharmaceutical production and pollution in India. Several Swedish County Councils have begun requiring that producers meet certain environmental standards.29 Additional harms not accounted for in pharmaceutical costs may be emerging. Pharmaceutical pollution of water at levels documented in India creates an environment for the development of drug resistance, which can then be spread within and beyond India by travel, posing great risk to populations currently unaware of these potential consequences. Larsson notes that much of the drug resistance that today poses health threats in Europe appears to have come from other continents.30 According to the World Health Organization, the rapid development of drug resistance is one of the largest threats to public health, globally. Thus, pharmaceutical pollution of water in India is an international problem that demands international attention and policy change. Legislating that pharmaceutical manufacturers meet certain environmental standards is a necessary first step; in India and internationally, education and enforcement must follow.

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Student Contributions References

1. Gopakumar, KM, and Santhosh, MR. “An Unhealthy Future for the Indian Pharmaceutical Industry.” Third World Resurgence 259 (2012): 9-14. 2. Vijay, G. “Systemic Failure of Regulation: The Political Economy of Pharmaceutical and Bulk Drug Manufacturing” in The Politics of the Pharmaceutical Industry and Access to Medicines: World Pharmacy and India, ed. Hans Lofgren. (Hyderabad: Social Science Press, 2012). 3. KPMG International, “The Indian Pharmaceutical Industry: Collaboration for Growth.” 2006. http://www.in.kpmg.com/pdf/Indian%20pharma%20outlook.pdf (accessed October 16, 2012). 4. Mason, M. “World’s Highest Drug Pollution Levels Found in Indian Stream.” 2009. http:// www.huffingtonpost.com/2009/01/26/worldshighest-drug-pollu_n_160867.html (accessed October 16, 2012). 5. World Health Organization, “Pharmaceuticals in Drinking-Water.” 2011. http://www.who.int/water_sanitation_health/publications/2011/pharmaceuticals_20110601.pdf (accessed October 20, 2012). 6. Beachey, M. “A Pharmaceutical Hazard.” 2008. Pharmaceutical Technology. http://www.pharmaceutical-technology.com/features/feature45434 (accessed October 20, 2012). 7. Smith, C.A. “Managing Pharmaceutical Waste – What Pharmacists Should Know.” Journal of the Pharmacy Society of Wisconsin (2002): 17-22. 8. Govil, P.K., G. L. N. Reddy, and A. K. Krishna, “Contamination of Soil due to Heavy Metals in the Patancheru Industrial Development Area, Andhra Pradesh, India.” Environmental Geology 41 (2001): 461-469. 9. Maria, A. “The Costs of Water Pollution in India.” (Paris: CERNA, 2003). 10. Central Pollution Control Board, “Minimal National Standards: Pharmaceutical Manufacturing and Formulation Industry.” (New Delhi: CPCB, 1989). 11. Vijayalakshmi, M.S.R. and B. S. Deepa, “Impact of Industrial Effluent Treatment on Profitability of Small and Medium Enterprises: A Case Study of Hyderabad Bulk Drug Industry,” in Entrepreneurship and SMEs: Building Competencies, eds. R. R. Thakur, S. Thukral, N. Sahu, and V. Gupta. (New Delhi: Macmillan Publishers, 2011). 12. Sahu, G., “People’s Participation in environmental Protection: A Case Study of Patancheru.” Institute for Social and Economic Change (2007): 1-28. 13. Larsson, D. G. J., C. D. Pedro, and N. Paxeus, “Effluent from Drug Manufactures Contains Extremely High Levels of Pharmaceuticals.” Journal of Hazardous Materials 148 (2007): 751-755. 14. Reddy, A. G. S., B. Saibaba, and G. Sudarshan, “Hydrogeochemical Characterization of Contaminated Groundwater in Patancheru Industrial Area, Southern India.” Environmental Monitoring and Assessment 184 (2012): 1357-1576. 15. Mathew, G. and M. K. Unnikrishnan, “The Emerging Environmental Burden from Pharmaceuticals.” Economic and Political Weekly 157 (2012): 31-34. 16. Adams, M. “India’s Waterways A Toxic Stew of Pharmaceutical Chemicals Dumped from Big Pharma Factories.” 2009. http://www.naturalnews.

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com/025415.html (accessed October 15, 2012). 17 Schertow, J. A., “India’s Waterways Used as Dumping Grounds for Big Pharma.” 2009. http:// intercontinentalcry.org/indias-waterways-used-asdumping-grounds-for-big-pharma/ (accessed October 20, 2012). 18. Associated Press, “Indian Stream a Cocktail of Drugs.” CBS News. 2009. http://www.cbsnews. com/2100-202_162-4752641.html (accessed October 31, 2012). 19. Shivkumar, K., and G. Biksham, “Statistical Approach for the Assessment of Water Pollution around Industrial Areas: A Case Study from Patancheru, Medak District, India.” Environmental Monitoring and Assessment 36 (1995): 229-249. 20. Rao, V., K. Subrahmanyam, P. Yadiah, and R. Dhar, “Assessment of Groundwater Pollution in the Patancheru Industrial Development Area and Its Environs, Medak District, Andhra Pradesh, India.” Impacts of Urban Growth on Surface Water and Groundwater Quality, Proceedings of IUGG 99 Symposium HS5, Birmingham. IAHS Publ. no. 259 (1999). 21. Subrahmanyam, K. and P. Yadiah, “Assessment of the Impact of Industrial Effluents on Water Quality in Patancheru and Environs, Medak District, Andhra Pradesh, India.” Hydrogeology Journal 9 (2001): 297-312. 22. Fick, J., H. Söderström, R. H. Lindberg, C. Phan, M. Tysklind, and D. G. Larsson. “Contamination of surface, ground, and drinking water from pharmaceutical production.” Environmental Toxicology and Chemistry 28, no. 12 (2009): 25222527. 23. Dhara, T., and A. Cherukupalli, “The Cost of Cheap Medicines: Antibiotic Pollution in Patancheru.” 2010. http://anilcherukupalli.com/thecost-of-cheap-medicines-antibiotic-pollution-inpatancheru/ (accessed October 15, 2012). 24. Greenpeace, “State of Community Health at Medak District.” 2004. http://www.greenpeace. org/india/Global/india/report/2004/10/state-ofcommunity-health-at-m.pdf (accessed November 10, 2012). 25. Sridhar, D., and P. Reddy, “Save Hyderabad – Pollution Free Hyderabad. Telangana Pharma and Chemical Employees Association.” N.d. http:// xa.yimg.com/kq/groups/20246497/102191789/ name/Telangana (accessed November 3, 2012). 26. Reddy, R., and B. Behera, “Impact of Water Pollution on Rural Communities: An Economic Analysis.” Ecological Economics 58 (2005): 520537. 27. Kolanu, M., “Officials Sleep as Pollution Sinks: Patancheru Greens to Step Up Anti-Pollution Drive.” Times of India, January 29, 2009. http:// articles.timesofindia.indiatimes.com/2009-01-29/ hyderabad/27998155_1_patancheru-effluents-water-bodies (accessed November 3, 2012). 28. TNN, “Patancheru Pollution Checked: PCB.” Times of India, July 26, 2009. http://articles. timesofindia.indiatimes.com/2009-07-26/hyderabad/28174757_1_industrial-pollution-effluentspollution-norms (accessed November 12, 2012). 29. Westergard, P., “The Market Cannot Solve This Problem.” Sustainability (2012). http://sustainability.formas.se/en/Issues/Issue-3-November-2012/ Content/Focus-articles/The-Market-cannot-solvethis-problem/ (accessed April 1, 2013). 30. University of Gothenburg, “Prof Joakim Lars-

son: Summary of Funded Projects.” 2013. http:// www.neurophys.gu.se/sektioner/fysiologi/endo/ joakim_larsson/ (accessed April 1, 2013). Image 1: Image courtesy of Wikimedia Commons Image 2: Image courtesy of Freedigitalphotos.net

Annie Ryu is a Harvard senior and serial social entrepreneur. She concentrated in Social Anthropology with a secondary field in Global Health and Health Policy. She has spent four months in India adapting and implementing a maternal and child health program she co-founded and building agricultural supply chains for underutilized fruits.

Student Contributions The Role of Epidemiology in the Pharmaceutical Industry: ‘Real World Data Analytics’ >>>Paul V Petraro, ScD The pharmaceutical industry is expected to closely monitor their products safety. In recent years, regulatory authorities such as the United States (US) Food and Drug Administration (FDA) and the European Medicines Agency (EMA) have become stricter with the guidelines for monitoring and reporting a drug’s risk management profile. The last decade has seen an explosion in the availability of data from numerous sources including claims data and electronic medical records allowing to improve the monitoring of medicinal products on the market. This has led to the need for advances in pharmacoepidemiologic methods and increased resources to keep up with the current trends. Pharmacoepidemiology is described as the study of the use and (side) effects of drugs in large numbers of people with the purpose of supporting the rational and cost effective use of drugs in the population, thereby improving health outcomes.1 Drug safety, more commonly known as pharmacovigilance, is the collection, detection, assessment, monitoring, and prevention of adverse effects from medicinal products. Before the introduction of risk management planning, drug safety involved a series of steps starting with data collection through signal detection, risk evaluation, action to protect public health, communication, and then evaluation of the effectiveness of the actions.2 The introduction of risk management plans (RMP) ensured greater proactivity to pharmacovigilance and finally, the introduction of systematic evaluation of the effectiveness of risk minimization measures (RMM), thereby demonstrating public health protection.3 The World Health Organization (WHO) states ‘Pharmacovigilance is now firmly based on sound scientific principles and is integral to effective clinical practice. The discipline needs to develop further to meet public expectations and the demands of modern public health.’4 Over the last decade, information has become more readily available electronically. Health claims data, which is administrative data collected by insurance companies, has been utilized more in pharmacoepidemiology. Real world data is a term used to define multiple sources of information that comes from administrative claims data, electronic medical records, and other sources that can be considered nonconventional data sources. As healthcare facilities continue to move towards electronic medical records, the amount of data available will

continue to grow exponentially. The interest in using this newfound wealth of data for drug safety surveillance is being explored by regulatory agencies. The European Union (EU) has initiated the EU-ADR research project (“Exploring and Understanding Adverse Drug Reactions by integrative mining of clinical records and biomedical knowledge”) which aims to exploit information from eight population-based databases in four European counties for drug safety signal detection.5 The United States (US) Food and Drug Administration (FDA) has the Sentinel Initiative (“Sentinel”), which is a nationwide network of electronic databases that is targeted to capture more than 100 million subjects for active drug safety surveillance. The goal is to assess medical product safety, by enabling near

real-time surveillance of medical products and their outcomes in routine care.6 Pharmacoepidemiology and drug safety (pharmacovigilance) are at the forefront of protecting the public’s health when utilizing medicinal products, both established and newly formulated drugs. Drug Safety The information age has led to the proactive monitoring of drug safety. Both the EU and US have been reassessing the regulations on monitoring medicinal products over the last few years. RMP’s, RMM’s, and Risk Evaluation and Mitigation Strategy (REMS) all have moved to the forefront of drug safety. Risk management is no longer a passive surveillance system that waits for spontaneous reporting and signal detection that may or may not happen in a timely manner. Today, it is necessary to plan risk management measures early, they need to be submitted to the regulatory agencies when a drug is approved for use in a country or region, in order to have systems in place when the medicines reach the masses. The authorities have forced the pharmaceutical industry to plan ahead and proactively monitor their medicines rather than wait for reports and other institutions studies to find possible signals that may have already compromised the patients and general health of the public utilizing these medicines. During drug development, clinical trials do not allow for the long term effects of medicines. The new regulations and changes over recent years take time to implement and in the long run will benefit both the public and the pharmaceutical industry, limiting risk of patients utilizing these medicines as well as pharmaceutical companies avoiding po-

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Student Contributions I would like to thank Jamie Geier and Kosuke Kawai for their invaluable review and input in this brief report on real world data in pharmaceuticals. Image 1: Image courtesy of Freedigitalphotos.net Image 2: Image courtesy of Deecare

References

tential costly lawsuits to unforeseen consequences of unknown adverse events and side effects. Real World Data Typically, epidemiologists and researchers use data from clinical trials, prospective studies, and data specifically collected with the intent to utilize for epidemiological analyses. Contrastingly, real world data, as the name signifies, is data collected for other reasons than epidemiological research. For example, administrative claims are utilized for reimbursements and electronic medical records are used for medical history and treatment of patients. The availability of this data has been a source of drug utilization and health economics research, and more recently it has been used to study drug safety with some major findings over the last few years. The pharmacoepidemiologic methods utilized for these types of observational studies are fairly new, with many in their infancy especially by pharmaceutical companies. It is important to note that epidemiology is a fairly young science, and with electronic data availability increasing exponentially over the last couple of decades, the methods available to analyze this data is developing accordingly. The expertise in these methods is still developing in the pharmaceutical industry. Pharmacoepidemiology Methods There are a number of epidemiologic methods which includes propensity scores, instrumental variables, and marginal structural models to name a few significant statistical methods available to utilize with real world observational research.7 Some of these methods have been developed and utilized for a number of years, but in industry the focus has only more recently become a necessity. And with numerous data sources becoming available, the methods vary based on the availability of information to manage the various limitations of the data sources. The methods used in observational research need to be able to limit possible sources of bias. Observational studies are generally subject to three sources of bias: information bias, selection

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bias, and confounding bias. Information bias is induced by measurement error in any of the variables, but most importantly the drug exposure or the outcome. Selection bias results from the inclusion or exclusion of subjects on the basis of factors associated with both the drug exposure and the outcome under study. Confounding bias results from the imbalances in covariates between the subjects exposed to the drug under study and those in the comparison group. While randomization balances the groups with respect to both measured and unmeasured covariates, observational studies are limited with respect to the latter, making confounding bias an important source of concern.7 These limitations are important when designing and planning drug safety studies and activities. Poor study design will lead to inconsistent results and inaccurate signals from medicines. Conclusions Pharmaceutical companies have had their share of mishaps that have been highly publicized leading to the publics’ concern and skepticism at the underlying motivations of the industry. This, in part, has led the regulatory agencies to focus on and strengthen the responsibility of pharmaceutical companies on monitoring possible long term adverse effects of their products. The focus is to continue to concentrate on improving pharmacovigilance with the purpose of monitoring the public’s health in regards to medicines, which has led to an increased focus on improving pharmacoepidemiologic methods and limiting inconsistent and/or improper use of the methodology. This can be seen by an international group of methodologists, researchers, and journal editors to set guidelines to improve reports of observational studies. The group is known as STROBE (Strengthening the reporting of observational studies in epidemiology).9 Real world data has become an important tool in drug safety and continued energies and focus on epidemiologic methods will further enhance the abilities of real world data on drug safety.

1. Strom BL. Pharmacoepidemiology. West Sussex: John Wiley & Sons, 2005. 2. Prieto, Luis, Almath Spooner, Ana Hidalgo‐Simon, Annalisa Rubino, Xavier Kurz, and Peter Arlett. “Evaluation of the effectiveness of risk minimization measures.” Pharmacoepidemiology and Drug Safety 21, no. 8 (2012): 896-899. 3. Waller, Patrick C., and Stephen JW Evans. “A model for the future conduct of pharmacovigilance.” Pharmacoepidemiology and Drug Safety 12, no. 1 (2003): 17-29. 4. World Health Organization. Centre for International Drug Monitoring. The Importance of Pharmacovigilence: Safety monitoring of medicinal products. 2002. 5. Schuemie, Martijn J. “Methods for drug safety signal detection in longitudinal observational databases: LGPS and LEOPARD.” Pharmacoepidemiology and Drug Safety 20, no. 3 (2011): 292-299. 6. Gagne, Joshua J., Jeremy A. Rassen, Alexander M. Walker, Robert J. Glynn, and Sebastian Schneeweiss. “Active safety monitoring of new medical products using electronic healthcare data: selecting alerting rules.” Epidemiology 23, no. 2 (2012): 238. 7. “Statistical methods in pharmacoepidemiology: advances and challenges” in Statistical Methods in Medical Research, 3-6. (Wiley Blackwell, 2009). 8. The Public Agenda Archives. Half of Americans say there is not enough government regulation of drug safety. http://publicagendaarchives.org/charts/half-americans-say-theres-not-enough-government-regulationdrug-safety (acccessed April 24, 2013) 9. von Elm, Erik, Douglas G. Altman, Matthias Egger, Stuart J. Pocock, Peter C. Gøtzsche, and Jan P. Vandenbroucke. “The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.” Preventive Medicine 45, no. 4 (2007): 247-251.

Paul has a MPH from Emory University; his previous experience includes the CDC and as a research specialist for HSPH’s Department of Nutrition’s projects in Dar es Salaam, Tanzania. Paul spent 2 summers working with epidemiology groups at Merck and Bayer where he worked on claims, EMR database analyses, and Risk Management Plans. Paul spent the last year at Pfizer as an epidemiology lead where he worked on risk management plans, orphan drug applications, and assisted on a feasibility assessment.

Health Highlights

Health Care Reform >>> An interview with Dr. Jonathan Gruber, PhD MIT Professor of Economics

H research?

HPR: Could you tell us about your background? Why did you decide to become involved with health policy

JG: I was in graduate school in the early 1990s, which was some of the last big round of excitement around health policy before the last few years. So I was looking for a topic to work on that was policy relevant, and health care seemed a natural area. I did a lot of “ivory tower” basic research in health economics. Then I went and worked in Washington for a year and got very interested in direct policy making. Upon returning from that in the late 1990s, I started trying to work more directly in making health policy. HHPR: You’ve been deeply involved with modeling health care reform policies across the states, from California to Massachusetts, and at the national level. Governors, members of Congress, presidential candidates, and politicians from both parties have sought out your modeling expertise. Please tell us about this modeling process and how you go about testing various policies? JG: When I left Washington, I realized what was really missing in policy debates was an objective source of numbers. That is – outside experts, like myself, that were “objective” would give broad opinions about policy, but would never provide actual numbers. So I went about building a model where I could literally say to policy makers, “Hey, if you do this policy, this will happen. This many people will gain insurance, you’ll spend this much, etc.”. This is what objective academics hadn’t really been doing. I started to work on that model in 1999 and developed it slowly over the years. Its most important use was in 2004, when I helped Mitt Romney put together the numbers behind his health care plan. That same model became the basis for the Obama administration and Congress in thinking about setting up the details of the ACA. HHPR: Within your models, what type of assumptions do you make? What type of time horizons do you use? JG: Well, there are a huge number of assumptions. That’s the important thing to recognize; that any of these modeling exercises – anytime you see revenue estimate come out of CBO or any place like that, its important to recognize that there’s a huge amount of uncertainty, because there’s huge numbers of assumptions that go in. I base my evidence

– my model on the best research that we have in the field of Health Economics to help understand the key assumptions. The timeline varies; I can base my model on anything from what happens next year to what happens 10 years from now. HHPR: What was it like working with the policymakers in Washington? Did anything surprise you about the process of drafting and creating the Affordable Care Act or legislation in general? JG: Really, the key in Congress is working with the staff. The politicians are smart, good guys, but they don’t have time for the details. So really, the key work happens at the staff level, and the staff are fantastic to work with. They’re very thoughtful, but everybody recognizes that there are political constraints on what you can do. I would say that there were not many huge surprises. I think that I was sort of surprised that the law passed, because its pretty hard to get major legislation passed in today’s political environment. But, you know, about the process, I think it was pretty much what I expected, which is this tradeoff between achieving policy goals and doing some of this politically come to pass (???) HHPR: In your opinion, why is universal health insurance coverage important and do you view think this issue has a moral or ethical dimension in addition to being relevant to economics? JG: I think that it is – I’m not a person that can speak on ethics, but I think the case in Economics is ethical, in the sense that we talk about universal health coverage in terms of improving people’s health, but that’s actually not the most important contribution here. The most important contribution is the financial security that this law provides. Basically, it’s outrageous that, in a nation as wealthy as ours, if someone walking across the street gets hit by a car, they could be bankrupted by that event. That’s crazy and it makes no sense that people are uninsured against the enormous financial health risks that they face. In every other developed nation, they are insured against those health risks; we’re the only one – despite the fact that we’re the wealthiest one. We’re the only one were people can be uninsured against major health risks and that just makes no sense at all. So it really just is sort of a social contract case. We should feel that in a nation as wealthy as ours that a fundamental component of the social contract is the promise that you won’t just be one bad gene, or one bad traffic accident away from bankruptcy. I think that’s the most important case.

HHPR: Right, and I think this really segues quite well into the next question. You spoke about the “social contract” and how the Affordable Care Act kind of fulfills that, in making sure that in a country as wealthy as our own, people aren’t bankrupted by adverse medical events. As you now, the United States is unique among its advanced, industrialized peers in its system of health care insurance and delivery. Do you think that the individual mandate was the best way of attaining universal insurance coverage compared to other options including singlepayer insurance? JG: It was the best politically feasible way. Let’s put it this way –the ACA is the best possible y to get widespread insurance coverage within the private insurance system, and single payer just wasn’t politically feasible. So I think, you know, this is a key important point. When you talk about best, it’s relative to what’s attainable and single payer was not attainable. So relative to what was attainable, which is a private insurance based reform, this was the best we could do. HHPR: Do you think then that its maybe a little ironic that opponents of the ACA are vehemently against the individual mandate, even though it is the best way to attain universal insurance coverage while maintaining a private-based insurance system? JG: Its incredibly ironic. The individual mandate was a Republican idea developed as a tool to oppose Clinton’s health reform in the 1990s. As recently as a year before the ACA, Republicans were touting the benefits of the individual mandate. Suddenly. Obama signs the law, and it’s a terrible idea. I think it was really partisan politics at its ugliest, because this was clearly a Republican idea that they supported very recently. HHPR: Let me move on to the next question here. Texas, South Carolina, Florida, and nearly a dozen other states are likely to reject the Medicaid expansion. Is this simply a matter of politics? Why are these governors and legislatures turning down federal dollars to expand Medicaid? JG: This is absolutely, pure politics. If you think about it, if they turn down the Medicaid expansion, the law provides no help for their citizens below the poverty line. So what they’re saying if the turn this down is that A: I’m uninterested in providing free insurance, paid for almost fully by

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Health Highlights the federal government, to my poorest citizens and B: I’m uninterested in having an incredible federal stimulus to my state, whereby the federal government is going to send in 100% of the money for the first 3 years, and 90% of the money thereafter. I mean, this is an enormous disturbance to all the citizens of these states and its incredibly ugly politics. HHPR: What affect will this rejection of the Medicaid expansion have on low-income residents that might depend on Medicaid for vital health care services? JG: They’ll be screwed. Basically, if you’re below poverty, you get nothing out of the law if the state doesn’t expand Medicaid. HHPR: Along the lines of implementation of the law within the states, in March of this year Arkansas announced that it reached an agreement with the Department of Health and Human Services allowing it to use the federal funds for the Medicaid expansion to purchase private insurance. Do you think this is a good idea? In your opinion, what affect will this have on efficiency, benefits, and coverage of the Medicaid program? JG: I think there are pros and cons, but what’s indisputable is that it’s much, much more expensive, because Medicaid pays providers a lot lower than private insurance. If you do this private alternative, there’s no way you can do it without spending more money. There simply isn’t. I haven’t made up some numbers, but there’s no way to do a private alternative without spending more money. So whether, you know, I can see arguments pro and con, except this makes the law a lot more expensive, and that’s not what Congress approved. Congress approved the law and it was going to cost a certain amount. If the states go the private route, the law’s going to cost more, and that’s not what Congress approved. HHPR: Ok, also, its been over 2 years since President Obama signed the Affordable Care Act into law and nearly 1 year since the Supreme Court upheld its constitutionality. Are there any unforeseen challenges with the implementation of the law thus far? JG: I wouldn’t say thus far there’s been much, but there’s going to be a huge issues with implementation next year. HHPR: What will those challenges look like next year? JG: Its just an incredibly complicated law, and we’re trying to do major changes to our insurance market, and its going to be hard. The major challenge, I think, is going to be around eligibility determination, which is deciding if you’re

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eligible for Medicaid, or private tax credits, or nothing. That’s going to be a big computer programming issue, and we’re not going to get it right 100%. I mean, we’ll get it right for most people, but we’re not going to get it 100% right. Because, its going to be a complicated process to get people into the right bin. Inevitably, its going to be a somewhat messy process, and we need to be prepared for that. Basically, the core of this law has to explain that we have to be, you know, in the words of Winston Churchill, “Be calm and carry on,”. You know, there’s going to be glitches and there’s going to be mistakes, but we can’t let a few glitches and mistakes overshadow the enormous benefits that the law is delivering. HHPR: I just have a few more questions to finish off here. So, first of all, The CBO recently detailed a sharp slowdown in health care cost growth. In fact, the CBO projected that spending in 2020 would be about 15% lower than its initial estimates. What do you believe is behind this recent slowdown in the growth of health care spending? Do you think the ACA is partly responsible? JG: Yes, the ACA is partly responsible, but we don’t know how much. Its clearly some combination of four factors. One is the recession. Two is the fact that individuals are being moved into plans where they have to pay more of their health care costs, like high deductible plans. Three are private market reforms that would have happened absent the ACA. And four is reforms that were introduced by the ACA. It’s impossible to separate them. I think its clear that the ACA had some effect, but I don’t know how much credit it gets.

rious. I think it really got watered down and I think it’s going to weaken the law a bit, and I’d like to see a more serious mandate penalty. HHPR: Would that entail a higher tax penalty, or would you structure it differently? JG: I think the structure is all fine, I just think the amount should be higher. HHPR: Last question; what direction do you see health care reform going in over the next 25 or 30 years and how do you think the Affordable Care Act will be changed? JG: I think now we’re going to turn our focus to cost control, and over the next 25 to 30 years we will see a lot more emphasis on controlling costs and reforming the way health care is delivered. HHPR: Do you have any ideas about any specific policy changes that we might see in the future? JG: No, at this point I think the main thing is to just let the Affordable Care Act play out and see what it does. So we’ll move from there. HHPR: Thank you, Dr. Gruber, for agreeing to speak with us. This interview was conducted by Health Highlights Senior Editor Brandon Jones.

HHPR: Do you think this slowdown will continue into the future, or do you think its only temporary? JG: Once again, I don’t know. I just don’t know. I really think it’s just too soon to say. HHPR: What is your view on new payment structures such as bundled payment and Accountable Care Organizations? Do you think these new payment structures will improve efficiency and quality of health care provision? JG: I think they definitely have the potential to. The devil is in the details about how you carry it out, but there’s no doubt that moving towards more bundled reimbursement and more coordinated care holds a lot of promise for controlling health care costs. HHPR: If you could change one thing about the ACA, what would it be? JG: If I could change one thing, it would definitely be to make the mandate penalty more se-

Dr. Jonathan Gruber is a Professor of Economics at the Massachusetts Institute of Technology, where he has taught since 1992. He is also the Director of the Health Care Program at the National Bureau of Economic Research, where he is a Research Associate. He is an Associate Editor of both the Journal of Public Economics and the Journal of Health Economics. In 2009 he was elected to the Executive Committee of the American Economic Association. He is also a member of the Institute of Medicine, the American Academy of Arts and Sciences, and the National Academy of Social Insurance.

Health Highlights The Rise of Antimicrobial Resistance >>>Dame Sally C. Davies, Tom Fowler, Keith Ridge, David Walker Antimicrobial resistance is fast emerging as one of the greatest health challenges. Its growth is increasing the threat from classical infectious diseases such as tuberculosis and gonorrhoea. Without action, it will also present a challenge to more mainstream healthcare interventions such routine surgical procedures, many cancer treatments and organ transplantation. No new classes of antibiotics have been discovered since the late 1980s. Better antibiotic stewardship alongside improved global surveillance must be a central priority in all healthcare policy to help prolong the therapeutic life of our existing antibiotics. Antibiotic stewarship, however, will only help to mitigate the problem. The market failure to produce new antibiotics and rapid diagnostics is the key problem and can be considered a societal rather than a medical issue, urgent wider collaborative action on this is needed on an international level.

ntibiotic resistance has been a problem for healthcare since antibiotics were first widely used in the 1940s. While this has led to concerns and warnings of dangers previously, we have always had alternative antibiotics to turn to. However we are now entering a period where this strategy is unlikely to be a viable option. It takes 10-20 years to develop new antibiotics and there have been no new classes of antibiotics discovered since the late 1980s and only a handful of new antibiotics within existing classes1. Gram-negative bacteria (which include E.coli) are an area of particular concern. Recent European data suggests that the mortality rate for septicemia (blood stream infections) due to multi drug resistant E.coli is 30% compared to 15% in susceptible E.coli 2. Applying this to UK data it is estimated around 5,000 patients die each year of septicemia due to Gram-negative bacteria, half of which are due to multi drug resistant bacteria1. Another area of concern is multi-drug-resistant tuberculosis (MDR-TB), TB that is resistant to the two most powerful anti-TB drugs, and extensively drug-resistant tuberculosis (XDR-TB), TB that is additionally resistant to a number of other antibiotics3. XDR-TB patients can be treated but it takes longer and people are much more likely to die than patients with ordinary TB or even MDR-TB. If XDR-TB became widely spread it is probable that, even in developed countries, we would have to go back to care in sanatoriums. In the UK the number of drug resistant cases continues to rise and while there have only been twenty four XDR-TB cases reported between 1995 -2011, six of these were reported in 20114. Perhaps most worrying is the growing mainstream use of carbapenem antibiotics, these antibiotics were previously ‘reserved’, that is only used in the very sick, immunocompromised, or as a

last resort. Due to growing rates of resistance to other antibiotics they are being used more often.5 In turn this is leading to increasing numbers of organisms that are resistant to these ‘powerful’ antibiotics. Bacteria resistant to carbapenem antibiotics are known as carbapenemase-producers and in the UK central reports of carbapenemaseproducing Enterobacteriaceae (a large family of Gram-negative bacteria) have increased from 3 cases in 2003 to over 500 in 20111. These are not our only remaining antibiotics, but the few existing alternatives are relatively toxic or of limited efficacy. These examples highlight that the problem is growing .One obvious conclusion would be that if we could just improve diagnosis, prescribing practice and adherence to treatment (good antibiotic stewardship) we would solve many of these problems. However, the history of the treatment of Gonorrhoea6 and the subsequent development of resistance suggests that this is not the case. Symptomatic cases of gonorrhoea are generally easy to diagnose, treatment regimens are simple, and guideline compliance is exemplary, in the UK usually in expert centres. However, despite this, there has been increasing resistance seen in the succession of first line therapies used. So, even where antibiotic stewardship is good, resistance still develops over time. Such is the nature of evolution. However good antibiotic stewardship is critical to prolonging the effectiveness of the remaining antibiotics we have, but the analogy of antibiotics as a natural resource is quite apt, the more we use them, the more our reserves for the future are depleted. So where does this leave us? Antibiotics are widely used not only in the treatment of infections, but in preventing infection too, and broadly across agriculture including animal and fish hus-

bandry. Routine operations such as hip replacements rely on antibiotics in case infections occur. Many cancer treatments leave people immunosuppressed and more vulnerable to infections, as do organ transplants. Without effective antibiotics the risks involved in undergoing such treatments would be much higher. While there are many actions that can be taken to prolong the therapeutic life of our current antibiotics, ultimately this is buying time. The long term solution are to: •

reinvigorate the development of new antibiotics or new ways to combat bacterial infections • develop effective affordable rapid diagnostics, and • ensure accurate, timely global surveillance of the problem The under-provision of new antibiotics is a “market failure”, and as such a societal rather than medical issue. Like all private businesses, pharmaceutical companies allocate their own scarce resources to maximise profits. Private investment decisions focus on the private benefit to a company, i.e. their return on investment. These decisions do not factor in any potential social benefits – the “positive externalities” of an investment. The private return on investment for an antibiotic is frequently lower than in other therapeutic categories. This is driven by various factors, including: • high cost and scientific challenges in R&D – especially for antibiotics that are effective against Gram-negative bacteria • antibiotics being typically used in shorter treatment courses compared to other drugs - for example drugs for chronic conditions • robust antibiotic stewardship (rightly) reserving the use of new antibiotics, which truncates their effective patent life, and likely return on investment • antibiotics facing relatively challenging clinical trial requirements before being licensed for use. Trial requirements are also prone to change over time, complicating matters further The true cost of antibiotic resistance is likely to be substantially underestimated7. There is a clear need for mechanisms to value the full societal benefit of a steady ‘pipeline’ of new antibiotics, which balance public health and conservation goals with private financial incentives8. Reinvigorating the market for antibiotics requires collective action, at a national and international level. There is a need for Governments, International Organisations, the Third Sector and Academia, working with the Private Sector,

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Health Highlights to incentivise R&D into new antibiotics. This should be led by the World Health Organisation (WHO). There is an expanding literature on policy methods to reinvigorate the market9,10, for example: • Push incentives – e.g. direct funding of R&D from public resources, which effectively reduce the marginal cost of R&D to private companies. • Pull incentives – e.g. using the lure of financial rewards for achieving particular milestones, such as monetary prizes for specific results, Advance Market Commitments (AMCs), or offering the incentive of patent buyouts. • Lego-regulatory incentives – e.g. use regulatory mechanisms to induce R&D activity, through expediting regulatory reviews (e.g. the US Generating Antibiotic Incentives Now (GAIN) Act (2012), and the US Limited Population Antibacterial Drug (LPAD) Approval Mechanism), extending product patent lives, or adjusting pricing and reimbursement mechanisms • Hybrid push-pull incentives – e.g. use a menu of push and pull methods to induce R&D activity, for example using a public-private partnership model. The European Union (EU) and the European Federation of Pharmaceutical Industries and Associations (EFPIA) are already supporting the antibiotic research through the Innovative Medicines Initiative (IMI), Europe’s largest public-private partnership. It is now urgent to strengthen effective international collaborative action, including priorities for research and development (R&D), as well agreeing a new financial model which supports antibiotic development. Public-private partnerships where lessons can be learnt include the GAVI Alliance and The Global Fund to fight AIDS, Malaria, and Tuberculosis. These have created new markets, delivered drugs for neglected diseases, new vaccines with specific product profiles, and have supported health institution development in developing countries. Part of the success of these partnerships has been the alignment of public and private risks. Growing rates of resistance due to agricultural use of antibiotics is also an issue, both in terms of its potential impact to agriculture and for human health. The extent that non-human use contributes to driving antibiotic resistance in bacteria affecting humans is currently unclear, here global surveillance will be key. Bacteria can transfer down the food chain but also resistance genes that escape to mobile DNA in the gut flora of another animal species can find their way to bacteria that colonise and infect human beings6. In this way resistance that develops in bacteria that

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do not affect humans can be passed to bacteria that does. The World Economic Forum report on global risks, 2013,11 identifies agricultural use as major concern and highlights the need to look again at the incentives that lead to the overuse of antibiotics in this field. This issue is a global problem and needs to be considered within the context of an increasing global population and the market pressure to improve productivity and cut costs. Clearly antibiotics are need to treat infection other factors such as the recent drive to make meat and milk production more efficient (thereby decreasing the impact of production on climate change) also plays a role; where antibiotics are used as growth promoters. Overall, the impact of this pressure can give rise to factors such as suboptimal investment in animal husbandry, which in turn leads to increased risk of disease in herds and flocks with this cost offset by routine use of cheap antibiotics to suppress the disease. In theory, pricing the additional societal costs into antibiotics might change the choice a farmer makes about spending on disease mitigation (such as animal housing, fencing, his own animal movement and trading choices). Action by industry such as a charging scheme that doesn’t encourage bulk buying (or supply in packs that encourage

pricing, but is a hidden future cost7.This, allied with current slow diagnostics leads to a misuse of antibiotics by both patients and clinicians that drives the faster growth of antibiotic resistance. Ultimately, of course, even the appropriate use of antibiotics drives the growth of antibiotic resistance. In health policy this leaves the question of what actions should now be taken. Preserving the therapeutic life of the antibiotics we have is essential. This means good antibiotic stewardship, thereby ensuring the right antibiotics are given at the right time and taken for the right period. This requires local health systems and organisations to have in place robust antimicrobial policies, with implementation and monitoring supported by multiprofessional expertise. Achieving this and effective surveillance should be a priority for all healthcare and agricultural systems including those in developing countries. Effective vaccination programmes and developing new vaccines have a very important role to play. Strong action to prevent counterfeit medicines an inappropriate and self prescribing of antibiotics needs to be put in place at the global level. Alongside this, is a need to reduce overall prescribing of antibiotics and to improve rapid diagnostics. Currently it

individual use) may help. If the whole impact, or at least risks of an impact, of routine use cannot be priced in, this leads to the question of whether regulation, such as the EU Veterinary medicinal products (VMP) Directive, or other steps such as ‘Retail Assurance Schemes’ (voluntary schemes assuring customers of certain production standards) can change current behaviour. However, for any action to be truly effective it needs to impact on a global scale, maybe in the form of an international treaty. The challenge of antimicrobial resistance is great. In the recent annual report of the Chief Medical Officer for England it was likened to climate change in terms of its potential health impact1. The key issue being that the full cost of the use of antibiotics is not reflected in their current

is standard practice to prescribe broad spectrum antibiotics in a number of settings where it is unclear if an illness is bacterial and life threatening or viral or symptoms of a chronic illness1. There are a number of areas where local health economies can help, most notably by encouraging innovation. For example better diagnostics would allow more targeted prescribing and potentially the continued use of antibiotics to which there are high rates of resistance in people with nonresistant infections. Much existing prescribing guidance is based on evidence used to inform licensing and not on research to identify the minimum dose and duration of an effective course of treatment. This would be a fruitful avenue of investigation. Improvements in these areas would enhance quality, reduce local problems such as

Health Highlights healthcare acquired infections due to resistant organisms1 and have an international impact. Currently much of the world is without adequate healthcare and extending access to antibiotics is an important part of addressing this. Yet in many low and middle income countries there is little or no mechanism to ensure good antibiotic stewardship. It would be unethical not to continue to try to extend access to healthcare and central to mitigating the impact of this on antimicrobial resistance is good antibiotic stewardship and effective vaccination programmes. However this once again emphasises the importance of thinking of antibiotics as a limited natural resource which, as the demand is only likely to grow, there is need to find new or alternative resources. Those making health and agricultural policy should place antibiotic stewardship and vaccine development and deployment as a priority in line with the long term costs and risks of antimicrobial resistance rather than immediate costs. This would go a long way to prolonging the therapeutic life of the antibiotics we currently have. However this relies on systems being able to implement stewardship measures and even if they are present, ultimately even the appropriate use of antibiotics drives antibiotic resistance, though at a slower rate6. Addressing the market failure in antibiotics remains the top priority. For this to occur antibiotic resistance needs to considered as a societal rather than just a medical issue.

Enterobacteriaceae in Europe.” Clinical Microbiology and Infection 18, no. 5 (2012): 413-431. 6. Davies S.C., Fowler T., Watson J., Livermore D.M., Walker D., “Annual Report of the Chief Medical Officer: infection and the rise of antimicrobial resistance”. Lancet (2013) doi:pii: S0140-6736(13)60604-2. 10.1016/S01406736(13)60604-2. [Epub ahead of print] 7. Smith, Richard, and Joanna Coast. “The true cost of antimicrobial resistance.”BMJ: British Medical Journal 346 (2013). 8. Kesselheim, Aaron, and Kevin Outterson. “Improving antibiotic markets for long term sustainability.” Yale Journal of Health Policy, Law & Ethics 11 (2011): 10-42. 9. Towse, Adrian, and Priya Sharma. “Incentives for R&D for New Antimicrobial Drugs.” International Journal of the Economics of Business 18, no. 2 (2011): 331-350. 10. Mossialos, Elias, Chantal M. Morel, Suzanne Edwards, Julia Berenson, Marin Gemmill-Toyama, and David Brogan. “Policies and incentives for promoting innovation in antibiotic research.” (2009). www.euro.who.int/__data/assets/pdf_ file/0011/120143/E94241.pdf (accessed June 18, 2013). 11. World Economic Forum. 2013. Global Risk Report 2013, Geneva, Switzerland: World Economic Forum. http://reports.weforum.org/globalrisks-2013 (accessed June 18,2013). Image 1: Image courtesy of Lauren Silverman via Flikr

We would like to thank the UK Chief Veterinary Officer. Nigel Gibbens, and colleagues in the Department for Environment, Food and Rural Affairs (DEFRA), UK, for their helpful advice and comments regarding agricultural use of antibiotics. We would also like to thank Ross Leach, economic adviser, Department of Health.

Dr Tom Fowler is a Locum Consultant in Health Protection and an honorary research fellow in public health in the University of Birmingham. He was editor in chief and co editor of Volumes 1 and 2 of the Chief Medical Officer’s Annual Report, 2011.

Dr Keith Ridge is Chief Pharmaceutical Officer of England and the Government’s principal adviser on pharmacy and medicines use. Keith is head of pharmacy profession across Government and also supports NHS England and Health Education England.

References

1. Davies, Sally C. 2013. Annual Report of the Chief Medical Officer, Volume Two, 2011,Infections and the rise of antimicrobial resistance. London: Department of Health. 2. De Kraker, M. E. A., M. Wolkewitz, P. G. Davey, W. Koller, J. Berger, J. Nagler, C. Icket et al. “Burden of antimicrobial resistance in European hospitals: excess mortality and length of hospital stay associated with bloodstream infections due to Escherichia coli resistant to third-generation cephalosporins.” Journal of Antimicrobial Chemotherapy 66, no. 2 (2011): 398-407. 3. World Health Organization. 2012. Global Tuberculosis Report 2012. Geneva, Switzerland: WHO. 4. Health Protection Agency. 2012. Tuberculosis in the UK: Annual report on tuberculosis surveillance in the UK, 2012. London: Health Protection Agency. 5. Cantón, Rafael, Murat Akóva, Yehuda Carmeli, Christian G. Giske, Youri Glupczynski, Marek Gniadkowski, David M. Livermore et al. “Rapid evolution and spread of carbapenemases among

Professor Dame Sally Davies is the Chief Medical Officer of England, the UK Government’s principal medical adviser and the professional head of England’s Directors of Public Health. Dame Sally is also Chief Scientific Adviser for the UK Department of Health and directs the National Institute for Health Research (NIHR).

Professor David Walker is the Deputy Chief Medical Officer for England. He has held a number of Board level posts in the NHS over the last 12 years and is a Senior Civil Servant in the Department of Health. Prior to his Public Health career in the UK he was a Visiting Scientist at the CDC in Atlanta, Georgia, USA.

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Health Highlights ObamaCare: The Plot Thickens >>>Michael F. Cannon, MA, JM

I. Exposition he Patient Protection and Affordable Care Act (PPACA) has had an interesting ride. Enacted over public opposition,1 it has survived numerous near-death experiences both before and after passage. Most notably, the PPACA lingered on death row for weeks after five Supreme Court justices cast a preliminary vote to strike down the entire law—until Chief Justice John Roberts apparently switched his vote. 2 Amid such high courtroom drama, one could be forgiven for missing a concurrent and equally dramatic storyline that is only now taking center stage. The PPACA authorizes up to $1.2 trillion of health insurance subsidies over 10 years,3 to be distributed through state-established health insurance “exchanges.” Yet two-thirds of the states have declined to establish an Exchange, leaving that task to the federal government..4 This unexpected development has major consequences. The PPACA authorizes those subsidies only through state-established Exchanges, not federally run Exchanges. By refusing to establish Exchanges, states have therefore vetoed some $800 billion of new entitlement spending. Without those subsidies, the PPACA will collapse of its own weight. Indeed, this development makes the Act so vulnerable to repeal that the Obama administration has hatched an audacious plot to rescue it. In broad daylight, the Internal Revenue Service is attempting to tax, borrow, and spend that $800 billion—contrary to both the express language of the PPACA and congressional intent. Thus in addition to other abuses that have recently come to light,5 the IRS is attempting to tax millions of employers and individuals without congressional authorization. A few of those employers and individuals are challenging the IRS’s illegal taxes in federal court. If they succeed, they will also block the full $800 billion of unauthorized spending—which would practically force Congress to reopen, and possibly repeal, the PPACA. Yes, this story has everything, starting with…

II. Inciting Action Our tale begins in Nebraska, whose voters re-elected moderate Democrat Ben Nelson to the U.S. Senate in 2006. As the Senate debated health care reform in 2009, Nelson was leery of a federal takeover of health care, or at least the appearance of it. He demanded that state governments rather

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than the federal government administer the Senate bill’s new regulatory agencies, called health insurance “Exchanges.”6 These agencies would implement or help to enforce the bill’s major provisions, including the ban on discrimination against people with pre-existing conditions and the individual mandate. Crucially, Exchanges were also the conduit for more than $1 trillion in health insurance subsidies the bill would authorize. The Senate leadership needed the support of all 60 Democratic senators to break a Republican filibuster of the Democrats’ health care bill, so Nelson got his way.7 It didn’t hurt that other moderate Democrats made the same demand. While that solution solved Nelson’s political problem, it created another problem. Congress cannot simply command states to implement federal programs like a health insurance Exchange. That’s a constitutional no-no that courts call “commandeering.”8 Fortunately, a law professor named Timothy Jost had a solution. In early 2009, Jost proposed that Congress get around this problem “by offering tax subsidies for insurance only in states that complied with federal requirements.”9 Congress can and does create these sorts of incentives for states all the time.10 The Medicaid program, for example, offers billions of dollars to states but only if they are willing to implement health care programs that meet federal specifications. If not, states get nothing. Senate Democrats liked this idea of creating such incentives for state cooperation so much, they incorporated it into both leading health care bills—one reported by the Finance Committee, the other by the Health, Education, Labor, and Pensions (HELP) Committee.11 The incentives were so large, and supporters were so certain that all states would cooperate,12 no one thought twice about the fact that Jost’s solution to the “commandeering problem” effectively gave each state a veto over the federal subsidies the bills sought to create. Supporters certainly had no incentive to herald the fact that they were giving states veto power over an essential element of the bills’ regulatory scheme. Senate Democrats passed a merged version of Finance and HELP bills—dubbed the Patient Protection and Affordable Care Act—in a pre-dawn vote on Christmas Eve of 2009, without a vote to spare.13 House Democrats had earlier passed a bill would have created a single health insurance

Exchange run by the federal government,14 and they were none too fond of the PPACA’s state-run Exchanges. In a letter to House Speaker Nancy Pelosi and President Obama, eleven Texas Democrats even complained the PPACA’s approach to Exchanges would allow states to block the law’s benefits.15 President Obama reportedly sided with the House negotiators in favor of a single, federally run Exchange.16 But then, a somewhat implausible event triggered... III. Rising Action In January 2010, Massachusetts voters elected Scott Brown (R) to fill the Senate seat vacated by the death of Edward M. Kennedy (D).17 Brown’s victory meant Senate Republicans would have just enough senators—41—to prevent a vote on final passage of any House-Senate compromise. While some observers declared health care reform finished,18 Brown’s election actually left Democrats with two options. The first was failure. If they insisted on forging a compromise between the House and Senate bills through “regular order,” the legislation would have died in the Senate. The second option was for the House to approve the Senate-passed PPACA as-is, while making limited modifications through the “budget reconciliation” process. Passing the PPACA as-is would send it immediately to President Obama’s desk. And under Senate rules, a simple 51-vote majority could approve the changes demanded by House Democrats. Supporters urged reluctant House Democrats to choose the second option. Making his second major contribution to this drama, Prof. Jost organized a letter from dozens of left-leaning academics and activists that described the Senate bill as “imperfect” but implored, “The House of Representatives faces a stark choice. It can enact the Senate bill, and realize the century-old dream of health care reform…Pass the Senate bill, and improve it through reconciliation.”19 Upon receiving assurances that Senate Democrats would approve the House’s modifications through reconciliation, House Democrats passed both the PPACA and the reconciliation bill that amended it on March 21, 2010.20 President Obama signed the PPACA, an achievement Vice President Joe Biden (D) famously described as “a big [expletive] deal,” on March 23.21 Senate Democrats made good on their word by passing the reconciliation bill,22 which President Obama signed into law on March 30.23 At that point, our narrative reaches a… IV. Plateau As a result of the political and constitutional constraints congressional Democrats faced, Jost’s

Health Highlights recommendation that Congress overcome the commandeering problem “by offering tax subsidies for insurance only in states that complied with federal requirements” became law. Here’s how it works, and how we know Congress meant it. The PPACA restricts eligibility for “premium-assistance tax credits” to individuals who purchase health insurance through an Exchange “established by the State under Section 1311” of the Act. If a state fails to establish an Exchange itself, Section 1321 authorizes the federal government to establish one for the state. But the statute nowhere authorizes premium-assistance tax credits through federally run Exchanges. On the contrary, the PPACA explicitly, repeatedly, consistently, and unambiguously restricts eligibility for premium-assistance tax credits to residents of states that establish their own Exchanges.24 That language appeared in Senate Finance Committee chairman Max Baucus’ (D-MT) first draft of his committee’s bill, was approved by the Finance Committee,25 was inserted into the final bill by Senate leaders and White House officials in Senate Majority Leader Harry Reid’s (D-NV) office,26 and garnered 60 votes on the Senate floor. It then traveled to House floor, where House Democrats approved it. When this language landed on President Obama’s desk, he eagerly signed it into law. Prof. Jost’s proposal made the entire journey from the Finance Committee to the U.S. Code without substantive alteration.

The PPACA thus creates a tremendous financial and political incentive for states to implement the law, but also gives states the power to veto major elements of its regulatory scheme. Just in case Prof. Jost’s contributions to the legislative history and the HELP bill’s conceptually identical provision were not enough to establish that Congress meant exactly what it said, we also have the word of the PPACA’s lead author. During a Finance Committee markup of the language on September 23, 2009, Baucus admitted that his bill conditioned premium-assistance tax credits on states implementing an Exchange. Indeed, he admitted his bill had to offer tax credits only to states that established Exchanges and withhold them from states that did not. The power to regulate health insurance resides with the Senate’s HELP Committee; it lies outside the Finance Committee’s jurisdiction. Making each state’s establishment of an Exchange a precondition of residents receiving tax credits was the only way the Finance committee could have jurisdiction to direct states to establish Exchanges in the first place.27 The legislative history further shows House Democrats accepted the Jost language as-is. House Democrats scoured the section of the PPACA containing the tax-credit eligibility rules, amending it no less than seven times via the reconciliation process. Yet despite their dissatisfaction with the PPACA’s approach to Exchanges, the House made no changes to the provisions restricting tax

credits to state-established Exchanges.28 The reconciliation bill did add language providing that Exchanges established by U.S. territories would be treated as state-established Exchanges under the law,29 showing that House Democrats knew how to authorize tax credits in non-state-established Exchanges when they desired. Yet the reconciliation bill did nothing either to authorize tax credits through federal Exchanges, or otherwise to alter the language restricting tax credits to states that establish their own Exchanges. House Democrats—including the eleven Texas Democrats who complained about the Senate’s approach to Exchanges30— approved the PPACA’s language restricting tax credits to states that established Exchanges as-is, and declined to change it through reconciliation. The clear, unambiguous language of the PPACA shows, and the legislative history of the statute confirms, that Congress intentionally restricted tax credits to states that establish their own Exchanges. This feature received little notice amid the ceremony (and other controversies) surrounding President Obama signing such a “big [expletive] deal” into law. Had the PPACA’s architects been correct that states would be eager to establish and operate health insurance Exchanges, this feature would have remained unremarkable. Instead, we saw… IV. More Rising Action Contrary to supporters’ expectations, a total

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Health Highlights of 34 states, representing roughly two thirds of the U.S. population, have opted not to establish an Exchange.31 In those 34 states, the premiumassistance tax credits and related subsidies would, if authorized, carry a total budgetary impact of $800 billion over the next 10 years.32 But under the statute, those subsidies are not available in those states. It is difficult to overstate the threat this poses to the PPACA’s survival. The purpose of the subsidies is to shift the considerable costs of the law’s health insurance regulations from the premium payer to the taxpayer. Without that cost-shift, the full cost of the law would become palpable to consumers, employers, and particularly health insurance carriers. Insurers are the intended recipients of those subsidies. Without them, the PPACA threatens to destroy their business model. In the two-thirds of states that have refused to establish Exchanges, these groups would likely demand that Congress reopen and/or repeal the law. As one trade publication reports: If premium subsidies are not available in federally established exchanges, “No one would go to those exchanges. The whole structure created by the health care reform law starts to fall apart,” said Gretchen Young, senior vice president–health policy at the ERISA Industry Committee in Washington.33 Indeed, we have already seen such a collapse in another part of the PPACA. The PPACA also created a long-term care entitlement program known as the CLASS Act. Congress imposed on this program the same insurance “reforms” it imposed on private health insurance markets—i.e., high-risk enrollees would pay the same premiums as low-risk enrollees— but without subsidies or a mandate to mitigate the resulting adverse selection. Experts warned the CLASS Act would prove unsustainable.34 After its enactment, the Obama administration abandoned any hope of implementing the program, and Congress and President Obama repealed it in January 2013.35 The PPACA’s Exchange-related health insurance-market “reforms” would collapse and be repealed just as—and for the same reason—as the CLASS Act.36 As if that weren’t excitement enough, then came the real… V. Conflict When it became evident that dozens of states would refuse to establish Exchanges, the IRS simply rewrote the law. In August 2011, the IRS announced that it was planning to issue premium-assistance tax credits federal Exchanges, even though the statute expressly forbids it.37 In May

Harvard Health Policy Review

2012 it finalized that policy.38 Amid heavy criticism from think tanks, law professors, and members of Congress,39 the IRS offered only perfunctory and post-hoc rationalizations for its rewriting.40 The agency failed to cite any part of the statute in support of its interpretation of the law until October 2012, fourteen months after announcing it.41 Even then, the provisions the IRS cited failed to support the agency’s position, or even to cast ambiguity on the clear language of the statute. The sole piece of legislative history the IRS has offered to support its position—i.e., the Congressional Budget Office score of the PPACA—crumbled when the CBO admitted it had not done a legal analysis of the relevant provision.42 The IRS’s position reduces to the absurdity that an Exchange established by the federal government is the same thing as an Exchange established by a state. It is little wonder that the agency and its defenders—most notably and ironically, Prof. Jost—have flailed about for nearly two years trying to square that circle.43 The IRS’s attempt to spend some $800 billion without statutory authority turns out not to be a victimless crime. Due to interactions with other provisions of the PPACA, the IRS’s illegal tax credits will trigger illegal taxes against millions of employers under the employer mandate, as well as millions of individuals under the individual mandate.44 Those victims are fighting back. In Pruitt v. Sebelius, Oklahoma attorney general Scott Pruitt filed the first legal challenge to the IRS’s illegal tax credits in federal court.45 First, Oklahoma claims the issuance of illegal tax credits will trigger illegal taxes against the state under the employer mandate. Second, Oklahoma claims that Congress gave states the exclusive power to decide whether to embrace the taxes and subsidies that come with establishing an Exchange, yet the IRS is usurping that power and therefore infringing Oklahoma’s sovereignty.46 In a separate lawsuit, Halbig v. Sebelius, several private employers and individual citizens have asked the U.S. District Court for the District of Columbia for relief from the IRS’s illegal taxes and other injuries.47 Legislators in Ohio and Missouri have introduced legislation that would effectively block both the IRS’ illegal tax credits and illegal taxes on employers in those states.48 Those court cases and that legislation are still in the early stages, which leaves observers wondering when will we arrive at the… V. Climax The IRS stands a very real chance of a rebuke from the federal courts. The non-partisan Congressional Research Service writes: a strictly textual analysis of the

plain meaning of the provision would likely lead to the conclusion that the IRS’s authority to issue the premium tax credits is limited only to situations in which the taxpayer is enrolled in a state-established exchange. Therefore, an IRS interpretation that extended tax credits to those enrolled in federally facilitated exchanges would be contrary to clear congressional intent…and likely be deemed invalid.49 No less an authority than Harvard Law Review has urged the Supreme Court to clarify whether the IRS’s decision is the sort of “major question” that courts should not allow agencies answer themselves: In each of the major questions cases, the Court was skeptical that Congress would implicitly delegate a significant determination. Viewed in this light, a reviewing court may have difficulty believing that Congress, without a clear directive, intended to delegate the determination of whether millions of Americans may receive billions of dollars to purchase health insurance.50 It’s actually hundreds of billions of dollars, but you get the point. These legal challenges, and the outcome of the Ohio and Missouri legislation, will unfold at the same time the federal government is implementing the PPACA’s major provisions. The Act provides that its trillion-plus dollars of tax credits and subsidies, as well as the penalties under the employer and individual mandates, will begin to take effect on January 1, 2014. The health insurance Exchanges must be open for business even sooner, by October 1, 2013. There is considerable doubt whether the Exchanges will be operational by that date, and able to offer Americans the health insurance they will be legally required to purchase. Baucus predicts “a huge train wreck.”51 A ruling against the IRS—whether a final judgment or even a preliminary injunction— would reveal the full cost of the PPACA to consumers, employers, and insurance carriers, and could generate to a groundswell of support for delaying, reopening, or even repealing the statute.52 The consequences could be so catastrophic that vulnerable Democratic Senators and even President Obama could come to view repeal as the face-saving option. It bears stressing that such a catastrophe would be the result of implementing the PPACA exactly as Congress intended. The lawsuits do not seek to undermine the PPACA. They seek to force the Obama administration to obey the statute,

Health Highlights

and to prevent the administration from taxing, borrowing, and spending $800 billion in clear violation of the law. If implementing the PPACA as Congress intended would lead to catastrophic results, the fault lies with the PPACA itself. Nevertheless, the outcome of those lawsuits is where the real action is. Their effect on the PPACA is merely… VI. Denouement If federal courts uphold the clear, unambiguously expressed will of Congress, it is difficult to see how the PPACA could survive. Sure, health insurers and the health care industry would pressure those 34 states to establish Exchanges and thereby lift the vetoes they have exercised over major provisions of the law. Yet one of those provisions is the employer-mandate penalties. Thus employers would likely exert countervailing pressure, and urge those 34 states not to establish Exchanges. Employers may even press the 16 states that have established Exchanges to un-establish them. Few Washington-based groups would be content to wait for the states to act. Some groups, most notably insurers, would no doubt press Congress to authorize tax credits through federal Exchanges. But the chances of the Republicancontrolled House of Representatives rescuing the PPACA by expanding its scope are slim. The only real question would be how much of the law House Republicans would demand be jettisoned in return for their support of a legislative fix. Given their unanimous support for full repeal,53 they may demand no less than that.

Were the IRS to prevail, the PPACA may survive yet the catastrophe would be greater. An IRS victory would mean the executive branch of the U.S. government will have succeeded in taxing, borrowing, and spending roughly $1 trillion dollars not only without congressional authorization, but contrary to the clear, unambiguously expressed will of Congress. An IRS victory would mean that The Law is not the statutes that Congress enacts, but the arbitrary decrees of unelected government officials. The Law will be neither legitimate nor predictable, but discretionary and arbitrary. Whatever legal pretext allows the IRS to prevail will not confine itself to this case, or to health care. It will be applied in other areas by government officials of all political ideologies. A court ruling that allows the IRS to tax and borrow and spend where it is explicitly forbidden to do so by statute would lend credence to both the perception that the government is no longer bound by the law and the corollary conclusion that therefore neither are the people.54 Which brings us to our… VII. Theme Our tale, though scripted and set in America’s ongoing health care debate, is not actually about health care at all. It is about whether government officials are subject to democratic constraints. In this still-unfolding narrative, the Obama administration’s actions are triply anti-democratic. First, the IRS is violating a direct constraint that popularly elected legislators placed on the executive branch. Second, it is violating that duly enacted statute for the purpose of denying popu-

larly elected state officials the vetoes Congress gave them over certain provisions of the statute. And third, it is violating the statute because administration officials either cannot fathom or will not accept that Congress meant to do what it clearly did.55 Obama administration officials continually emphasize that the PPACA is “the law of the land.”56 That remains to be seen, in more ways than one. The author would like to thank Meinan Goto and Pragya Kakani for their assistance with this article.

References

1.“Obama Health Care Law: Favor/Oppose,” Huffington Post, March 2013, http://elections.huffingtonpost.com/ pollster/us-health-bill#!selectedpoll=17177 ( a c cessed June 6, 2013). 2. Jan Crawford, “Roberts Switched Views to Uphold Health Care Law,” CBS News, July 1, 2012, http:// www.cbsnews.com/8301-3460_162-57464549/robertsswitched-views-to-uphold-health-care-law/. (accessed June 6, 2013) 3. Congressional Budget Office, CBO’s February 2013 Estimate of the Effects of the Affordable Care Act on Health Insurance Coverage, 2013, Washington, DC; p. 2 4. “State Decisions For Creating Health Insurance Exchanges, as of May 28, 2013,” Kaiser Family Foundation, http://kff.org/health-reform/state-indicator/health-insurance-exchanges/ (accessed May 29, 2013).; “To Date, 23 States & DC Plan to Expand Medicaid Eligibility in 2014, 19 Will Not Expand, and the Remainder Are Undecided,” Avalere Health, http://www.avalerehealth. net/news/spotlight/20130524_Medicaid_Expansion. pdf (accessed May 29, 2013); “Where the States Stand, May 24, 2013; 26 Governors Support Medicaid Expansion,” The Advisory Board Company, http://dl.ebmcdn. net/~advisoryboard/infographics/Where-the-States-

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Health Highlights Stand71/story.html (accessed May 29, 2013). 5. Daniel Strauss, “Republican Lawmakers Hear Complaints about Wider Abuses from IRS,” The Hill, May 24, 2013, http://thehill.com/blogs/on-the-money/domestictaxes/301911-gop-lawmakers-hear-complaints-aboutwider-abuses-from-irs (accessed June 6, 2013). 6. Carrie Budoff Brown, “Nelson: National Exchange a Dealbreaker,” Politico, January 25, 2010, http:// www.politico.com/livepulse/0110/Nelson_National_ exchange_a_dealbreaker.html (accessed June 6, 2013).; Patrick O’Connor & Carrie Budoff Brown, “Nancy Pelosi’s Uphill Health Bill Battle,” Politico, January 9, 2010, http://www.politico.com/news/stories/0110/31294.html (accessed June 6, 2013). 7. Patrick O’Connor & Carrie Budoff Brown, “Nancy Pelosi’s Uphill Health Bill Battle,” Politico, January 9, 2010, http://www.politico.com/news/stories/0110/31294.html (accessed June 6, 2013). 8. Printz v. United States, 521 U.S. 898, 925 (1997) (“the Federal Government may not compel the states to implement, by legislation or executive action, federal regulatory programs”). 9. Timothy S. Jost, “Health Insurance Exchanges: Legal Issues,” O’Neill Institute For National and Global Health Law at Georgetown University, April 27, 2009, http://scholarship.law.georgetown.edu/cgi/viewcontent. cgi?article=1022&context=ois_papers (accessed June 6, 2013). 10. See Jonathan H. Adler, “Cooperation, Commandeering or Crowding Out? Federal Intervention and State Choices in Health Care Policy,” Kansas Journal of Law and Public Policy, 20 (2011), http://papers.ssrn.com/sol3/papers.cfm?abstractid=1791834 (accessed June 6, 2013). 11. America’s Healthy Future Act of 2009, S. 1796, 111th Cong. (2009); Affordable Health Choices Act, S. 1679, 111th Cong. (2009). 12. Robert Pear, “U.S. Officials Brace for Huge Task of Operating Health Exchanges,” New York Times, Aug. 4, 2012, A17, http://www.nytimes.com/2012/08/05/ us/us-officials-brace-for-huge-task-of-running-healthexchanges.html?pagewanted=all&_r=0 (accessed June 18, 2013). (“When Congress passed legislation to expand coverage two years ago, Mr. Obama and lawmakers assumed that every state would set up its own exchange.”); Elise Viebeck, “Obama Faces Huge Challenge in Setting Up Health Insurance Exchanges,” The Hill, Nov. 25, 2012, http://www.thehill.com/blogs/healthwatch/healthreform-implementation/269137-obama-faces-hugechallenge-in-setting-up-health-exchanges (accessed June 6, 2013). (“It’s a situation no one anticipated when the Affordable Care Act was written. The law assumed states would create and operate their own exchanges…”). Statement of Kathleen Sebelius, Departments of Labor, Health and Human Services, Education, and Related Agencies Appropriations for 2011, Hearing Before the H. Comm. on Appropriations, 111th Cong. 170–171, Apr. 21, 2010, http://www.gpo.gov/fdsys/pkg/CHRG-111hhrg58233/ pdf/CHRG-111hhrg58233.pdf (accessed June 6, 2013). (“We have already had lots of positive discussions, and States are very eager to do this. And I think it will very much be a State-based program.”).; Barack Obama, “Remarks on Health Insurance Reform in Portland, Maine,” White House, April 1, 2010, http://www.whitehouse. gov/the-press-office/remarks-president-health-insurancereform-portland-maine (accessed June 18,2013) (“[B]y 2014, each state will set up what we’re calling a health insurance exchange.”). 13. United States Senate, “Vote Summary: On Passage of the Bill (H.R. 3590 as Amended ),” December 24, 2009, http://www.senate.gov/legislative/LIS/roll_call_lists/ roll_call_vote_cfm.cfm?congress=111&session=1&vo te=00396 (accessed June 6, 2013).

Harvard Health Policy Review

14. Affordable Health Care for America Act, H.R. 3962, 111th Cong. (2009); House of Representatives, Office of the Clerk, “Final Vote Results for Roll Call 887,” November 7, 2009, http://clerk.house.gov/evs/2009/roll887.xml (accessed June 6, 2013). 15. “U.S. Rep. Doggett: Settling for Second-Rate Health Care Doesn’t Serve Texans,” My Harlingen News, January 11, 2010, http://www.myharlingennews.com/?p=6426. (accessed June 6, 2013). 16. Lori Montgomery and Michael D. Shear, “White House Nears Deal on Health Care,” Washington Post, January 14, 2010, http://www.washingtonpost.com/wpdyn/content/article/2010/01/14/AR2010011404837. html?sid=ST2010021904088 (accessed June 6, 2013). 17. Stephanie Condon, “Scott Brown Win Shakes Up Health Care Fight,” CBS News, January 20, 2010, http://www.cbsnews.com/8301-503544_162-6119035503544/scott-brown-win-shakes-up-health-care-fight/ (accessed June 6, 2013). 18. Andrew Malcolm, “Does Scott Brown’s Election Doom Healthcare?” Los Angeles Times, January 20, 2010, http://latimesblogs.latimes.com/washington/2010/01/ does-scott-browns-election-doom-health-care.html (accessed June 6, 2013).; Robert Laszewski, “Stick a Fork in It! The Democratic Effort to Pass a Health Bill is Dead,” Health Care Policy and Marketplace Review, January 19, 2010, http://healthpolicyandmarket.blogspot. com/2010/01/stick-fork-in-it-democratic-effort-to.html (accessed June 6, 2013). 19. Henry J. Aaron et al., “Letter to Speaker of the House Nancy Pelosi et al.,” January 22, 2010, http:// graphics8.nytimes.com/images/2010/01/22/health/ adopt_senate_bill_final.2.pdf (accessed June 6, 2013). 20. Greg Hitt and Janet Adamy, “House Passes Historic Health Bill,” Wall Street Journal, March 22, 2010, http:// online.wsj.com/article/SB10001424052748703775504 575135440191025592.html (accessed June 6, 2013). 21. Sheryl Gay Stolberg and Robert Pear, “Obama Signs Health Care Overhaul Bill, With a Flourish,” New York Times, March 23, 2010, http://www.nytimes. com/2010/03/24/health/policy/24health.html (accessed June 6, 2013). 22. David M. Herszenhorn and Robert Pear, “Final Votes in Congress Cap Battle on Health Bill,” New York Times, March 25, 2009, http://www.nytimes.com/2010/03/26/ health/policy/26health.html (accessed June 6, 2013). 23. Peter Baker and David M. Herszenhorn, “Obama Signs Bill on Student Loans and Health Care,” New York Times, March 30, 2010, http://thecaucus.blogs.nytimes. com/2010/03/30/obama-signs-bill-on-student-loanshealth-care/ (June 6, 2013). 24. Jonathan H. Adler and Michael F. Cannon, “Taxation without Representation: The Illegal IRS Rule to Expand Tax Credits under the PPACA,” Health Matrix 23, No. 1 (2013): 119-195, http://law.case.edu/journals/ HealthMatrix/Documents/23HealthMatrix1.5.Article. AdlerFINAL.pdf (accessed June 6, 2013). 25. America’s Healthy Future Act of 2009, S. 1796, 111th Cong., Sec. 1205 (2009); Carrie Budoff Brown, “Senate Finance Committee Approves Health Care Bill,” Politico, October 13, 2009, http://www.politico.com/ news/stories/1009/28235.html (accessed June 6, 2013). 26. David M. Herszenhorn and Robert Pear, “White House Team Joins Talks on Health Care Bill,” New York Times, October 15, 2009, http://www.nytimes. com/2009/10/15/health/policy/15health.html?_r=0 (accessed June 6, 2013). 27. Executive Committee Meeting to Consider Health Care Reform: Before the S. Comm. on Finance, 111th Cong. 326 (2009), http://www.finance.senate.gov/ hearings/hearing/download/?id=c6a0c668-37d9-4955861c-50959b0a8392 (accessed June 6, 2013).; Executive

Committee Meeting to Consider an Original Bill Providing for Health Care Reform: Before the S. Comm. on Finance, C-SPAN (starting at 2:53:21) (Sept. 23, 2009), http:// www.c-spanvideo.org/program/289085-4 (accessed June 6, 2013). 28. Jonathan H. Adler and Michael F. Cannon, “Taxation without Representation: The Illegal IRS Rule to Expand Tax Credits under the PPACA,” Health Matrix 23, No. 1 (2013): 119, 162. 29. Health Care and Education Reconciliation Act, Pub. L. No. 111-152, § 1204, 124 Stat. 1029, 1055 (2010). 30. House of Representatives, Office of the Clerk, “Final Vote Results for Roll Call 165,” March 21, 2010, http:// clerk.house.gov/evs/2010/roll165.xml (accessed June 6, 2013). 31. Kaiser Family Foundation, “State Decisions For Creating Health Insurance Exchanges, as of May 28, 2013,” State Health Facts, http://kff.org/health-reform/stateindicator/health-insurance-exchanges/ (accessed June 21, 2013). 32. Congressional Budget Office, CBO’s February 2013 Estimate of the Effects of the Affordable Care Act on Health Insurance Coverage, 2013, p. 2. 33. Jerry Geisel, “Oklahoma Lawsuit Targets Premium Subsidy Provision of Health Care Reform Law,” Business Insurance, October 28, 2012, http:// www.businessinsurance.com/article/20121028/ NEWS03/310289979#full_story (accessed June 6, 2013). 34. Richard S. Foster, “Estimated Financial Effects of the ‘America’s Affordable Health Choices Act of 2009’ (H.R. 3962), as Passed by the House on November 7, 2009” (2009), p. 11; American Academy of Actuaries, Critical Issues in Health Reform: Community Living Assistance Service and Supports Act (CLASS) (2009); Richard S. Foster, “Estimated Financial Effects of the ‘Patient Protection and Affordable Care Act,’ as Amended,” (2010), p. 15; Dep’t of Health and Human Services, Office of the CLASS Actuary, “Actuarial Report on the Development of CLASS Benefit Plans,” (2011), p. 35. (“It is not a coincidence that many experts have maintained that adverse selection is the major obstacle for the CLASS program. Any workable design must address it in order to receive certification as an actuarially sound plan.”). 35. American Taxpayer Relief Act of 2012, Pub. L. 112240, Sec. 642, 126 Stat. 2313(2013). 36. Julie Appleby and Mary Agnes Carey, “CLASS Dismissed: Obama Administration Pulls Plug On LongTerm Care Program,” Kaiser Health News, October 14, 2011, http://www.kaiserhealthnews.org/stories/2011/ october/14/class-act-implementation-halted-by-obamaadministration.aspx (accessed June 6, 2013).; American Taxpayer Relief Act of 2012, Pub. L. 112-240, Sec. 642, 126 Stat. 2313, 2358 (2013). 37. Internal Revenue Service, “Health Insurance Premium Tax Credit Proposed Rule,” Federal Register 76, No. 159 (August 17, 2011): 50932, http://www.gpo.gov/fdsys/pkg/FR-2011-08-17/pdf/2011-20728.pdf (accessed June 6, 2013). 38. Internal Revenue Service, “Health Insurance Premium Tax Credit,” Federal Register 77, No. 100 (May 23, 2012): 30378, http://www.gpo.gov/fdsys/pkg/FR-201205-23/pdf/2012-12421.pdf (accessed June 6, 2013). 39. David Hogberg, “Oops! No ObamaCare Tax Credit Via Federal Exchanges?” Investors Business Daily, September 7, 2011, http://news.investors.com/090711584085-oops-no-obamacare-tax-credit-via-federalexchanges-.htm?p=1 (accessed June 6, 2013).; Jonathan Adler and Michael F. Cannon, “Another ObamaCare Glitch,” Wall Street Journal, November 16, 2011, http:// online.wsj.com/article/SB1000142405297020368750 4577006322431330662.html (accessed June 6, 2013).;

Health Highlights Rep. David Phil Roe, “Letter to Douglas Shulman, Commissioner, Internal Revenue Service,” November 4, 2011, http://roe.house.gov/UploadedFiles/Letter_ to_IRS_Commissioner_regarding_tax_credits_under_ PPACA_-_11.03.11.pdf (accessed June 6, 2013). ; Sen. Orrin G. Hatch, “Letter to Timothy Geithner, Secretary, Department of the Treasury and Douglas Shulman,” December 1, 2011, http://finance.senate.gov/newsroom/ ranking/download/?id=d8c3f533-132c-4cec-be108008402c21d8 (accessed June 6, 2013). 40. Douglas H. Shulman, Commissioner, Internal Revenue Service, “Letter to Rep. David Phil Roe,” November 29, 2011), http://roe.house.gov/UploadedFiles/IRS_Response_to_letter_on_PPACA_Exchange.pdf (accessed June 6, 2013).; Centers for Medicare and Medicaid Services, “State Exchange Implementation: Questions and Answers,” November 29, 2011, p. 8, http://cciio.cms. gov/resources/files/Files2/11282011/exchange_q_and_a. pdf.pdf (accessed June 6, 2013). 41. Mark J. Mazur, Assistant Secretary for Tax Policy, Treasury Department, “Letter to Rep. Darrell Issa,” October 12, 2012 (on file with authors). 42. Douglas W. Elmendorf, “Letter to Rep. Darrell Issa,” December 6, 2012, http://www.cbo.gov/sites/default/ files/cbofiles/attachments/43752-letterToChairmanIssa. pdf (accessed June 6, 2013).; Michael F. Cannon, “Of States and Health Insurance Exchanges,” Reuters, December 18, 2012, http://blogs.reuters.com/great-debate/2012/12/18/of-states-and-heath-insurance-exchanges/ (accessed June 6, 2013). 43. For example, Michael Cannon and Jonathan Adler, “The Illegal IRS Rule To Expand Tax Credits Under The PPACA: A Response To Timothy Jost,” Health Affairs Blog, August 1, 2012, http://healthaffairs.org/ blog/2012/08/01/the-illegal-irs-rule-to-expand-tax-credits-under-the-ppaca-a-response-to-timothy-jost/ (accessed June 6, 2013). 44. I.R.C. § 4980H(a)(2) and I.R.C. § 5000A(e)(1). 45. Pruitt v. Sebelius, No. CIV-11-30-RAW (E.D. Okla 2012). 46. Response to Motion to Dismiss Amended Complaint, Pruitt v. Sebelius and Geithner, No. CIV-11-30RAW (E.D. Okla 2012). 47. Michael F. Cannon ,”Michael Carvin on Halbig v. Sebelius,” Cato Institute, June 1, 2013. <http://www.cato. org/blog/michael-carvin-halbig-v-sebelius> (accessed June 18, 2013). 48. Michael F. Cannon, “Ohio, Missouri Introduce the Health Care Freedom Act 2.0,” Cato@Liberty, April 9, 2013, http://www.cato.org/blog/ohio-missouri-introduce-health-care-freedom-act-20 (accessed June 6, 2013). 49. Jennifer Staman and Todd Garvey, Congressional Research Service, “Legal Analysis of Availability of Premium Tax Credits in State and Federally Created Exchanges Pursuant to the Affordable Care Act,” July 23, 2012: Washington DC http://www.statereforum.org/ sites/default/files/premium_credits_and_federally_created_exchanges_copy.pdf (accessed June 6, 2013). 50. “Recent Regulation: Statutory Interpretation—Patient Protection and Affordable Care Act—Internal Revenue Service Interprets ACA to Provide Tax Credits for Individuals Purchasing Insurance on Federally Facilitated Exchanges.—Health Insurance Premium Tax Credit, 77 Fed. Reg. 30,377 (May 23, 2012) (to be codified at 26 C.F.R. pt. 1),” Harvard Law Review 126, (2012): 663 (“While the debate surrounding this rule has largely concentrated on whether the text and legislative history support the IRS’s interpretation, the political saliency and economic impact of the rule may provide an opportunity for a reviewing court to clarify the limits of the major questions exception to the doctrine of judicial deference established in Chevron U.S.A. Inc. v. Natural Resources

Defense Council, Inc.”). 51. Jennifer Haberkorn, “Max Baucus Worried About Health Law ‘Train Wreck’,” Politico, April 17, 2013, http://www.politico.com/story/2013/04/max-baucusworried-about-health-law-train-wreck-90215.html (accessed June 6, 2013). 52. See Jerry Geisel, “Oklahoma Lawsuit Targets Premium Subsidy Provision of Health Care Reform Law,” Business Insurance, October. 28, 2012, http://www.businessinsurance.com/article/20121028/NEWS03/310289979 (accessed June 6, 2013). (‘‘If premium subsidies are not available in federally established exchanges, ‘No one would go to those exchanges. The whole structure created by the health care reform law starts to fall apart,’ said Gretchen Young, senior vice president-health policy at the ERISA Industry Committee in Washington.”). 53. Clerk of the U.S. House of Representatives, “Final Vote Results For Roll Call 154, H.R. 45, To Repeal The Patient Protection And Affordable Care Act And Health Care-Related Provisions In The Health Care And Education Reconciliation Act Of 2010,” http://clerk.house.gov/ evs/2013/roll154.xml (accessed June 6, 2013). 54. See Glenn Harlan Reynolds, “A revolution in the works? Column,” USA Today, February 4, 2013, http://www.usatoday.com/story/opinion/2013/02/04/ americans-unhappy-government-convention-column/1887593/ (accessed June 6, 2013). (“According to a Pew poll released last week, more than half of Americans view government as a threat to their freedom. And it’s not just Republicans unhappy with Obama, or gun owners afraid that the government will take their guns: 38% of Democrats, and 45% of non-gun owners, see the government as a threat. Add this to another recent poll in which only 22% of likely voters feel America’s government has the ‘consent of the governed,’ and you’ve got a pretty depressing picture -- and a recipe for potential trouble. Governments operate, to a degree, by force, but ultimately they depend on legitimacy. A government that a majority views as a threat, and that only a small minority sees as enjoying the consent of the governed, is a government with legitimacy problems.”); Glenn Reynolds, interviewed by Russ Roberts, “Glenn Reynolds on Politics, the Constitution, and Technology,” EconTalk, February 13, 2013, http://www.econtalk.org/archives/2013/02/ glenn_reynolds.html (accessed June 6, 2013). (“Guest [Glenn Reynolds]: Here’s the problem with public officials…deciding to ignore the Constitution. If you are the President, if you are a member of Congress, if you are a TSA agent, the only reason why somebody should listen to what you say instead of horse-whipping you out of town for your impertinence is because you exercise power via the Constitution. If the Constitution doesn’t count, you don’t have any legitimate power. You are a thief, a brigand, an officiant busybody, somebody who should be tarred and feathered and run out of town on a rail for trying to exercise power you don’t possess. So…if we are going to start ignoring the Constitution, I’m fine with that; the first part I’m going to start ignoring is I have to do whatever they say. [Host] Russ [Roberts]: But his argument is that we already ignore the Constitution. It’s not really much of a binding document. Guest: Oh, well then I’m free to do whatever I want. And actually, that is a damning admission. Because what that really says is: If you believe [Louis Michael] Seidman’s argument, if you believe that we already ignore the Constitution anyway is that in fact the government rules by sheer naked force and nothing else. If that’s what you believe, all this talk of revolution suddenly doesn’t seem so crazy and seems almost mandatory. ”) 55. Timothy Stoltzfus Jost, “Yes, the Federal Exchange Can Offer Premium Tax Credits,” Health Reform Watch, September 11, 2011, http://www.healthreformwatch.

com/2011/09/11/yes-the-federal-exchange-can-offerpremium-tax-credits/ (accessed June 6, 2013). (“But now we seem to be stuck with the textualists delight: a statute whose words clearly say what Congress clearly did not mean.”). 56. Tom Howell Jr., “Sebelius: ‘Help us Speed up’ Health Care Rollout,” Washington Times, February 4, 2013, http://www.washingtontimes.com/news/2013/ feb/4/sebelius-obamacare-here-stay-needs-states-help/ (accessed June 6, 2013). Image 1: Image courtesy of 401(K) 2013 Image 2: Image courtesy of winifredxoxo via Flikr

Michael F. Cannon is the Cato Institute’s director of health policy studies. Previously, he served as a domestic policy analyst for the U.S. Senate Republican Policy Committee, where he advised the Senate leadership on health, education, labor, welfare, and the Second Amendment. Cannon has appeared on ABC, CBS, CNN, CNBC, C-SPAN, Fox News Channel, and NPR. Cited by the Washington Post as “an influential health-care wonk at the libertarian Cato Institute,” his articles have been featured in The Wall Street Journal, USA Today, the Los Angeles Times, the New York Post, the Chicago Tribune, the Chicago Sun-Times, the San Francisco Chronicle, Huffington Post, Forum for Health Economics & Policy, Health Matrix: Journal of Law-Medicine, and the Yale Journal of Health Policy, Law, and Ethics. Cannon is the co-editor of Replacing Obamacare: The Cato Institute on Health Care Reform and coauthor of Healthy Competition: What’s Holding Back Health Care and How to Free It. He holds a bachelor’s degree in American government (BA) from the University of Virginia, and master’s degrees in economics (MA) and law & economics (JM) from George Mason University.

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