HHPR Fall 2015 Issue

HHPR Harvard Health Policy Review Volume 15 Issue 1

PRECISION MEDICINE

FEATURES

HEALTH HIGHLIGHTS STUDENT CONTRIBUTIONS

Beyond the Initiative Improving Mental Health Policy

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Precision Medicine: Unraveling the Debate

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HARVARD HEALTH POLICY REVIEW VOL. 15, ISSUE 1 WWW.HHPRONLINE.ORG

Editor’s Note

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Eunah Lee

FEATURES The Real Power of Precision: Redefining the Precision Medicine Initiative

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Spencer Nam, MBA

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Richard Simon, D.Sc.

Precision Medicine in Cancer Diagnosis and Treatment

Million Veteran Project: A Large Cohort 13 John Gaziano, MD, MPH and John Concato, MD, MS, MPH Nested in a Health Care System HEALTH HIGHLIGHTS 18 Michael B. Friedman, LMSW Improving American Mental Health Policy: No Simple Answers Immigrants Face Barriers Both as Health 22 Leighton Ku, PhD, MPH Care Patients and Providers Lessons from Indiana: The Case for 25 Monica S. Ruiz, PhD, MPH, Sean T. Allen, MPH, DrPH Broader Implementation of Syringe and Allison O’Rourke, MPH Exchange Programs The Fallacy of U.S. and China Hospital 28 Garry Choy, MD, MBA, Julianne Ip, MD, Collaborations – Are We Able to Bridge and Dicken S. C. Ko, MD, FRCSC, FACS Ideals With Realities?

Simulating the Impact of an Urban Farm 30 Joel Gittelsohn, PhD, Yeeli Mui, MPH, Sen Lin, MS, Bruce Y Lee, MD, MBA, Andrew Seiden, Tax Credit Policy in a Low Income Urban MPH, Arielle Gorstein, MPH, Pete Welch, Setting Sara Bleich, PhD, Takeru Igusa, PhD STUDENT CONTRIBUTIONS 34 Priya Vedula Precision Medicine: Unraveling the Debate From Cells to Systems: The Application of 37 Jonathan M Clarke, MA(Cantab.), MB, BChir MRCS Precision Medicine to Improve Healthcare Delivery

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editor’ s note In his 2015 State of the Union Address, President Obama announced the launch of the Precision Medicine Initiative, a research effort to discover and support individualized treatments for patients. Backed by a large investment of $215 million, the initiative reflects high hopes in precision medicine and represents a strong start to catalyze a future in which healthcare more demonstrably acknowledges patient diversity. The challenge this initiative presents for healthcare is to carefully consider individual patient differences – including differences in a patient’s genetic and microbiome constitution, health and psychiatric history, environment, and lifestyle – to provide the best possible care for each patient.

We at HHPR selected this timely and important Precision Medicine Initiative as our issue theme, around which our Features and Student Contributions sections converge.

Editor-in-Chief Eunah Lee Managing Editor Melinda Song Senior Design Editor Hueyjong Shih Senior Business Manager Eric Li Senior Publishing Editor Kamran Jamil Internal Relations Chair Risham Dhillon Web Design & Technology Jiahui Huang Senior Editors Edna Wang, editorials Patric Cao, online content Raghu Dhara, online content Associate Editors Marcus Gutierrez, business Anna Valuev, business Benjamin Zheng, business Antonia Chan, design Courtney Lewis, design Apoorva Rangan, design Anjali Chandra, features Henna Hundal, features Neil Davey, health highlights Apoorva Rangan, health highlights Scott Xiao, health highlights Jesper Ke, online content Samuel Oh, online content Antonia Chan, student contributions Michael Liu, student contributions Bovey Rao, student contributions Risham Dhillon, web design Marcia Soviak, web design 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.

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Harvard University Student Organization Center at Hilles Box #40 59 Shepard Street Cambridge, Massachusetts 02138

Our Features section begins with a piece that points out a paradox in that this initiative, which aims to lower costs, is costly in and of itself. The piece argues that a greater focus within the initiative onto precise diagnostics can introduce a beneficial disruptive force in the healthcare market. Our second article focuses specifically on precision medicine in cancer care, delineating its current status in oncology and describing challenges for the future. To close this section, the last article examines the operations of the Million Veteran Program, a longitudinal cohort study involving expansive data collection and integration.

The article regards the program as a model for the Precision Medicine Initiative since they share similar goals.

Our Student Contributions section opens with a piece that advocates careful questioning of the reasonableness, scope, and aims of the Precision Medicine Initiative’s supported research. Our second article calls for application of precision medicine techniques not only to individual patient care but also to health systems improvement to benefit a wider population.

In our Health Highlights section, we diverge from the theme of precision medicine and shine light on a variety of other important topics in healthcare today. We begin with a piece that analyzes the complexity of American mental health policy as it is enmeshed with policy questions in other areas including social welfare policy, disability policy, and criminal justice policy. This piece examines multiple sources of these difficulties and notes that they represent opportunities for change. Our second article expounds on the paradox of limited access to care faced by immigrants yet the important role of immigrant providers in U.S. healthcare, and discusses the healthcare barriers that immigrant groups face. Our third article focuses on the first HIV outbreak in three decades in the U.S. that recently took place in Indiana. The article advocates for more syringe exchange programs to prevent the spread of HIV. Our fourth article notes an increasing interest in investing in the Chinese healthcare market, but cautions about risks and barriers that organizations may face if they venture into this new market. Finally, this section closes with a study that modeled the potential impact of the conversion of privately owned vacant lots in low-income areas of Baltimore City into community produce farms. Its promising predictions spurred the passage of city council legislation for these farm conversions.

Our carefully curated Fall 2015 issue examines the recently launched Precision Medicine Initiative and discusses developments in health care policy. This exciting project would not have been possible without the dedication and hard work of our contributors, our advisers, our managing editor, and the rest of our diligent staff on our editorial review, design, technology, publishing and business boards.

We hope you enjoy this latest issue of our journal.

Sincerely, Eunah Lee Editor-in-Chief 2015-2016

about the cover

acknowledgements

Cover illustration modified from stock image via Shutterstock by Antonia Chan.

The Harvard Health Policy Review would like to thank the Harvard Undergraduate Council and The Institute of Politics at Harvard University for their generous support of this publication.

©2015 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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FEATURES

The Real Power of Precision: Redefining the Precision Medicine Initiative Spencer H. Nam, Clayton M. Christensen

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The primary value of precision medicine rests in its ability to lower the cost of healthcare. Although the Obama Administration’s recently launched Precision Medicine Initiative has raised much expectation, it appears to be a costly program.

A truly transformative initiative must lower the cost of care by improving the diagnostics of diseases. Precise diagnostics lead to standardized treatments that can devolve to lower-cost venues primarily staffed by lower-cost caregivers.

While these processes may take decades to complete, if history is any guide, they will save substantial amounts of time and resources compared to the current initiative’s approach of refining what we already know.

The Importance of Disruptive Innovation in Healthcare Innovations of all types can typically be classified into one of two categories: sustaining or disruptive (Figure 1).

Sustaining innovations, which improve performance of existing products or services, have been instrumental in raising care standards and clinical outcomes, particularly in the last century. The Precision medicine that is standardized acts as a disruptive force that can impact evolution of optical microscopes is an the business models of healthcare organizations by 1) simplifying “solution shop” example of a sustaining innovation. hospitals, 2) transferring more responsibilities from hospitals to value-adding The early optical microscopes, aided by process clinics, and 3) delivering greater efficiency via facilitated networks. advances in technology, underwent a series of upgrades to give rise to much more powerful but also more expensive electron and fluorescence microscopes.7 he Obama Administration’s recently unveiled Precision

Disruptive innovations, on the other hand, exhibit Medicine Initiative (PMI) is an ambitious project aimed characteristics that are quite different from sustaining innovations. at developing individualized treatment and prevention First, they are simpler and more affordable than the existing, strategies for diseases based on each person’s genetic, environmental, or incumbent, solutions. Second, they are often based on new and lifestyle characteristics.1 For diseases such as cancer, in which technologies that are initially not as good as those of the incumbent some of the best in-class drugs are effective in just twenty to thirty solutions. Finally, they target customers who are currently not percent of all cases, and five-year survival rates for most metastasized adopting or consuming any of the incumbent solutions. Over time, cases are less than ten percent 2,3, the potential value of personalized the disruptive solutions improve in performance and functionalities, treatment and prevention could be significant. and more customers gravitate towards these new, more affordable The core value of precision medicine, however, rests on solutions to satisfy their needs. Eventually, the disruptive products lowering the cost of healthcare by first understanding the causes and services that perform just as well as the incumbent options but of the disease. Once understood, we can then standardize specific at lower prices replace existing solutions. diagnostic and treatment methods to deliver better clinical outcomes Personal computers, digital cameras, transistor radios, and smart for each person. Personalized medicine via customization turns out phones are all well-known examples of disruptive innovations. In to be a mere byproduct of such standardization. To that end, cost healthcare, percutaneous cardiac intervention (PCI) is a great example remains a key challenge for the PMI. For example, despite the lack of of disruption. Initially introduced as angioplasty, PCI began as a improvement in drug efficacy, cancer drug prices have sharply risen minimally invasive way to open up limited types of blocked coronary over the past ten years.4 Without a concerted effort to define the arteries for patients ineligible for open heart coronary artery bypass problems up front and standardize the solutions, any improvement grafting (CABG). Today, PCI has become the standard of care for in clinical outcomes from the initiative will likely come with a hefty treating most types of coronary artery diseases (CAD). With the price tag. With the Administration calling for a sustained national introduction of drug-eluting stents, PCI has not only lowered the effort in supporting the initiative, initial funding of more than $200 total cost of treating serious CAD but also has substantially expanded million will be the beginning of a stream of major government the patient population eligible for treatment. investments in the coming decade.5 Despite its admirable intentions, the PMI appears to provide little relief to our growing cost problems, Precision Medicine as a Disruptive Force is About Standardization which are soon to reach twenty percent of the annual GDP.6 For a healthcare system seeking to reduce the total cost of care, To be truly transformative, an initiative of this kind must first disruptive innovations can play a crucial role in driving down the invest in improving the diagnostics. Precisely understanding the cost of care without compromising quality and outcomes. Precision causes and progression of a disease is the fastest and the most medicine is a disruptive force that delivers innovations to replace economical way to deliver more effective and individualized therapies high cost treatments with simple rules-based approaches, which to each person. Once causes are clearly understood, we can develop become broadly accessible and affordable. We define precision standardized treatment methods, which should then devolve to lower- medicine as the provision of care for diseases that can be precisely cost venues primarily staffed by lower-cost caregivers. Transferring diagnosed, whose causes are understood, and which can be treated more care responsibilities to non-physician clinicians will enable the with rules-based therapies that are predictably effective.8 Investing effective delivery of affordable care to more people. Although these in innovations of diagnostic technology is an important first step processes may take decades to complete, if history is any guide, they will save substantial amounts of time and resources compared to the current approach “For reasons that are still unclear to us, a series of historical decisions have led to reimbursements on diagnostic products as being worth less than of refining what we already know.

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reimbursements on prescription drugs...Supported by this capital influx, the $400 billion U.S. pharmaceutical industry today is approximately eight times larger than the size of the diagnostics industry.”

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towards precision medicine.

Today, there are many chronic diseases that go without proper diagnosis, treatment, and cure. Such diseases include allergies, Alzheimer’s disease, certain forms of cancer, depression, inflammatory diseases, multiple sclerosis, and obesity. We define these diseases to be in the realm of intuitive medicine, as they can be diagnosed only by their symptoms and treated only by therapies whose efficacy is uncertain.9 In order to deal with the onslaught of these new, complex, and intuitive diseases, we need precision medicine to assist us in precisely diagnosing and mapping their causes before seeking the best possible solutions.

The Clinical and Economic Implications of Defining the Problems First

The cost of developing new drugs is so high that some believe prices have reached the breaking point.10 Surprisingly, we have arrived at the edge of the cliff because of an unexplainable historical reimbursement policy that has influenced investment allocations in research over the past fifty years. For reasons that are still unclear to us, a series of historical decisions have led to reimbursements on diagnostic products as being worth less than reimbursements on prescription drugs. This divergent policy in favor of drugs has incentivized an increasing amount of companies to invest in new drug development versus new diagnostics development. Supported by this capital influx, the $400 billion U.S. pharmaceutical industry today is approximately eight times larger than the size of the diagnostics industry.

What costs have been created by this seemingly simple decision to underreimburse diagnostics and over-reimburse drugs? As new drugs have become increasingly more difficult to find, the scale and cost of clinical trials have greatly expanded. Unfortunately, because of poor diagnostic capabilities, a large portion of the trial population includes those without the disease, leading to efficacy outcomes peaking at around 35%.11 Although these drugs are approved and heavily marketed to everyone, for the 65% of people who do not have the disease, the drugs are wasted. Given the significantly high cost of developing a new drug today, more than a billion dollars per compound, the cost of wasted drugs might be even greater.

Just as the decision to encourage drug development via greater reimbursement

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Figure. 1. New diagnostic technologies do not always sustain the traditional trajectory of improvement but instead may offer solutions with different performance metrics or new value propositions. was simple, we can reverse this trend quite simply and painlessly by giving greater reimbursement for effective diagnostics. The incentives for better diagnostics will lead to more targeted solutions that decrease the waste of drugs being prescribed to people without the disease.

Standardized Care Leads to Lower-Cost Venues and Lower-Cost Caregivers

Today, many infectious diseases can be treated simply, quickly, and cost effectively because our precise understanding of the diseases and low-cost diagnostics have resulted in standardized processes. In fact, non-physician clinicians now routinely treat many of these diseases. The potential impact of precision medicine in the healthcare business model is significant, as repeatable processes streamline care delivery, reduce complexity, and lower costs.

Rules-based precision medicine also allows non-physician clinicians to take on other routine patient care. For example, the development of rapid strep test has not only expedited the diagnosis of the disease but also has allowed nurse practitioners to handle the patient consultation in more cases. With a significant shortage of physicians expected over the next decade, the roles of nonphysician clinicians need to expand more rapidly.12 Business models in the healthcare industry can be segmented into three major functional categories: solution shops, value-adding process (VAP) businesses, and facilitated

network businesses.13 Today, most care facilities can be viewed as “solution shops.”

Solution shops are institutions structured to diagnose and recommend solutions to unstructured problems. For example, when a person exhibits symptoms of a disease, he or she visits a doctor’s office or hospital, where physicians use their expertise, experience, and supporting diagnostic tools to identify the exact causes and the nature of the unknown disease.

Because of their unstructured nature and the variety of problems they face, solution shops have a higher cost burden than entities with repeatable processes. Rules-based precision medicine can help solution shop clinics lower some of this cost burden.

The VAP businesses in the healthcare industry represent those providing products and process-driven services to customers.

VAP businesses transform inputs of resources – people, materials, equipment, information, and capital - into outputs of higher value. Because the VAP businesses leverage repeatable processes to deliver products and services that are already optimized, customers can expect a specific set of standards for products and services they purchase. In healthcare, VAP clinics can reduce the burden on solution shop hospitals by providing drugs in consistent dosage and efficacy, therapeutic and diagnostic products with specified outcome expectations, and routine services with a measurable standard of care.

The recent surge of retail clinics and

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other low-cost venues are reshaping the care delivery landscape. Precision medicine enables certain functions within hospitals to break away into specialized, stand-alone entities where low-cost care is provided.

According to the Centers for Disease Control and Prevention (CDC), nearly half of the U.S. adult population is estimated to suffer from one or more chronic diseases.14 And with the U.S. elderly population set to double in the next two decades, that number will likely soar. A proliferation of precision medicine-driven VAP entities that continue to off-load burdens on solution shops might be the best solution to control rising costs.

The potential impact of precision medicine in the facilitated network environment is also significant. Facilitated network entities are the institutions that operate systems in which customers transact products and services with other parties in the network. The standardization of electronic health records soon will redefine privacy, ownership, and transaction of personal medical data. Because precision medicine will make personal health data more portable, significant cost efficiency could be achieved by not only eliminating redundancy but also by contributing to more effective medical assessments.

Precision Medicine is the Fastest Way to Reduce Healthcare Costs First described by physicians in 1857, the stomach ulcer was one of the most puzzling diseases for more than 100 years.15 An inability to find the causative agent, combined with the overwhelming belief that germs could not survive a stomach’s acidity, led scientists to blame psychological and environmental issues for the disease. The lack of pattern between ulcer formation and these indirect factors only intensified the debate among researchers. It wasn’t until 1983 that J Robin Warren and Barry Marshall, two Australian doctors, shocked the world by announcing that the Helicobacter pylori bacterium (H. pylori) was responsible for stomach ulcers. Unfortunately, it took Drs. Warren and Marshall over three decades to convince the medical community of their discovery. This effort included the daring act of Marshall drinking a H. pylori cocktail to demonstrate that it was indeed the causative agent. Today, more than forty years after their announcement, stomach ulcers are generally treated by precisely diagnosing for H. pylori and then delivering a standard regimen of antibiotics – a highly predictable, affordable, and effective solution.16

The direct and indirect costs of not spending more time and resources in finding the real cause of stomach ulcers turned out to be quite significant. For decades, a disease that could have been managed with simple antibiotics received expensive but ineffective intuitive care. Although it took over three decades for the correct approach to be broadly adopted, we wasted more than a century focusing on wrong solutions.

In our current environment of accelerating healthcare spending, investing in discovering the causes of diseases has become the most important and necessary task. A precise discovery of causes requires effective diagnostics, towards which we must make significant investments. If we focus on solutions before we can define the problem, solving the same problem will take much longer than we can imagine. We have neither the time nor the resources to support such a journey. Let’s begin our earnest march towards precisely defining the causes of the diseases of our generation.

1. The White House. Precision Medicine Initiative [Internet]. 2015 [cited 2015 Jul 31]. Available from: https://www.whitehouse.gov/precision-medicine 2. Kantarjian H, Fojo T, Mathisen M, Zwelling L. Cancer Drugs in the United States: Justum Pretium - The Just Price. Journal of Clinical Oncology.

2013;31(28):3600-3604.

3. National Cancer Institute. Cancer Types [Internet].

2015 [cited 2015 Jul 31]. Available from: http://www. cancer.gov/types 4. Mailankody S, Prasad V. Five Years of Cancer Drug Approvals. JAMA Oncology. 2015;1(4):539.

5. The White House. Precision Medicine Initiative [Internet]. 2015 [cited 2015 Jul 31]. Available from: https://www.whitehouse.gov/precision-medicine 6. Centers for Medicare & Medicaid Services. National Health Expenditure Accounts: Methodology Paper, 2013 [Internet]. 2015 [cited 2015 Jul 31]. Available from: https://www.cms.gov/Research-StatisticsData-and-Systems/Statistics-Trends-and-Reports/ NationalHealthExpendData/downloads/dsm-13. pdf 7. Els.net. History of the Optical Microscope in Cell Biology and Medicine [Internet]. 2015 [cited 2015 Aug 1]. Available from: http://www.els.net/ WileyCDA/ElsArticle/refId-a0003082.html 8. Christensen C, Grossman J, Hwang J. The Innovator’s Prescription: A Disruptive Solution for Health Care.

New York: McGraw-Hill; 2009.

9. Christensen C, Grossman J, Hwang J. The Innovator’s Prescription: A Disruptive Solution for Health Care.

New York: McGraw-Hill; 2009.

10. Herper M. ‘60 Minutes’ Just Attacked High Drug Prices. Here’s What You Should Know.

[Internet]. Forbes. 2014 [cited 2015 Aug 1].

Available from: http://www.forbes.com/sites/ matthewherper/2014/10/05/60-minutes-justattacked-high-drug-prices-heres-what-you-shouldknow/ 11. Center for Evidence-based Medicine [Internet].

Toronto: Glossary of EBM terms – more details on NNT; 2015 [Cited 2015 Jul 31]. Available from: http://ktclearinghouse.ca/cebm/glossary/nnt 12. The National Association of Health Community

Spencer Nam

Spencer H. Nam is Senior Research Fellow at The Clayton Christensen Institute for Disruptive Innovation. He has been an equity analyst covering both public and private medical technology companies and has advised senior management of Fortune 500 companies.

Clayton Christensen

Clayton M. Christensen is the Kim B. Clark Professor of Business Administration at the Harvard Business School. He is regarded as one of the world’s top experts on innovation and growth and is the best-selling author of nine books and more than a hundred articles.

Centers. Expanding Access to Primary Care: The Role of Nurse Practitioners, Physician Assistants, and Certified Nurse Midwives in the Health Center Workforce [Internet]. 2015 [cited 2015 Aug 1].

Available from:https://www.nachc.com/client/ documents/Workforce_FS_013.pdf 13. Christensen C, Grossman J, Hwang J. The Innovator’s Prescription: A Disruptive Solution for Health Care. New York: McGraw-Hill; 2009.

14. Cdc.gov. Chronic Disease Overview | Publications | Chronic Disease Prevention and Health Promotion | CDC [Internet]. 2015 [cited 2015 Aug 1]. Available from: http://www.cdc.gov/chronicdisease/ overview/ 15. Tanenbaum J. Delayed gratification: why it took everybody so long to acknowledge that bacteria cause ulcers. J Young Investigators [Internet]. 2005 Feb [Cited 2015 Jul 31]. Available from: http:// www.jyi.org/issue/delayed-gratification-why-it-tookeverybody-so-long-to-acknowledge-that16. Mayo Clinic [Internet]. Minneapolis: Diseases and conditions – peptic ulcer [Cited 2015 Jul 31]. Available from: http://www.mayoclinic.org/ diseases-conditions/peptic-ulcer/basics/causes/ con-20028643

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Photo from Flickr, Creative Commons Public Domain Dedication.

FEATURES

Precision Medicine in Cancer Diagnosis and Treatment By: Richard Simon, D.Sc. Precision or Personalized Medicine is today an integral part of modern cancer therapy. It does not involve tailoring treatment to a person’s specific genome sequence but rather tailoring treatment to mutations found in a patient’s tumor. Much of the buzz about the nature of personalized medicine is based on speculations in areas of medicine where personalized medicine has not yet arrived. My purpose here will be to describe what precision medicine involves today in oncology, how publicly funded genomics research has gotten us this far, and what some of the key challenges for the future are.

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he Human Genome Project (HGP) was a large initiative to determine the sequence of DNA that constitutes the human genome. The DNA is the program which describes how each protein is built. Proteins do the work of cells and the protein molecules present in a cell determine the tissue “phenotype” of the cell and how the cell will interact with other cells. Proteins also interact with chemicals entering the cell and with the DNA itself, influencing further protein production.

During and subsequent to the completion of the HGP, new technologies for DNA sequencing were developed and the cost of sequencing has dropped dramatically. The cost of the HGP was about $2.7 billion in 1991 dollars. Today a human genome can be sequenced for about $1000 to $5000. This dramatic reduction in the cost of genome sequencing has led to two new kinds of large genomics projects in the field of cancer.

Whole Genome Association Studies The first type of new project is the whole

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genome association study (WGA) which aims to find inherited genetic changes associated with cancer. WGA’s involve genotyping the DNA in blood cells for a large number of patients with a particular kind of cancer and an equal control group. Genotyping involves determining the DNA code through specific “polymorphic” genomic locations that vary among individuals.

Although there are many associations between polymorphisms and cancer incidence, usually the associations have been too weak to use for counseling individuals on their disease risk.1 These studies have also so far not led to personalizing treatment for patients with an inherited risk polymorphism.

Tumor Sequencing Studies The other type of large genomic studies that followed the HGP are tumor sequencing The Tumor Cell Genomic Atlas (TCGA) project sponsored by the National Cancer Institute that has attempted to sequence the DNA of at least 200 tumors of each of

the major types of cancer.5 An international consortium has conducted similar studies.6 These studies have generally sequenced the DNA of the approximately 25,000 genes.

The portion of the genome consisting of genes is called the “exome”. The exome consists of less than 1% of the genome, with the remainder consisting of regulatory regions and sequence of unknown function.

With new methods of sequencing called next generation sequencing (NGS), whole exomes of tumors can be sequenced very economically. The exome contains the sequence of all the genes and the genes contain the DNA code for all of the human proteins.

Tumors can result from protein malformations caused by mutations in key genes. The development of a tumor is considered a multi-stage process with each stage being triggered by a mutation in a somatic cell. A somatic cell is a cell of a tissue in the body other than the egg cells or sperm cells. A mutation in a somatic cell such as a lung cell may provide a growth advantage to that cell. Somatic cells can divide and the mutations they contain are inherited by their daughter cells. Additional mutations can occur in a member of the descendant cells of those containing the original mutation providing additional growth advantage.7 All Tumors are Unique The tumor sequencing studies have been

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rich in new discoveries. It was found that in many cases, tumors of the same primary site (e.g. lung cancer) are heterogeneous with regard to the somatic mutations that they contain. However most of the mutations do not change the protein structure.

Consequently, most of the differences among tumors are not functional or exploitable therapeutically.

As a tumor population expands from a single cell to about 1011 cells, the size needed for clinical diagnosis, it may undergo an enormous number of total cell divisions. For any position in the genome, the probability of a mutation for normal mammalian cells is approximately one mutation in 109 cell divisions. These mutations result from the thermodynamics of cell division and are what drive species evolution. In an expanding tumor population which may have undergone 1013 mutations by the time of clinical diagnosis, every location in the genome is likely to have undergone one or more mutations. These neutral mutations have been called “passenger mutations” because they are not driving the development or progression of the tumor. Many of the tumor sequencing studies have identified hundreds of mutations per tumor and one of the challenges is to distinguish the “driver” mutations from the “passenger” mutations.

Development of Drugs for Inhibiting Driver Mutations Some genes have been found to be mutated in many tumors of the same primary site. For example, the BRAF gene is mutated in about 50% of melanoma tumors, the KRAS gene is mutated in about 55% of pancreatic cancer, and the P53 gene is mutated in over 50% of all cancers.

Some types of cancer are characterized by the presence of a specific mutation. For example, Chronic Myelogenous Leukemia is characterized by the presence of a translocation bringing together the ABL gene with the regulatory region of the BCR gene and Burkitt’s lymphoma is characterized by a mutation in the MYC gene.

There was some personalization of treatment based on biological characterization of the tumor even before the HGP. For example, breast tumors that expressed estrogen receptors on their surface were treated with anti-estrogen drugs such as Tamoxifen which block those receptors.

On the other hand, treating an estrogen

receptor negative tumor with Tamoxifen has no effect. The selective effect of Tamoxifen was an early form of precision medicine For breast cancer, prior to the HGP it was discovered that about 25% of the tumors have lots of HER2 protein receptors on the cell surface and that the patients with these HER2 positive tumors had somewhat shorter survival than other breast cancer patients.

The over-expression of HER2 appears to be caused by amplification of the HER2 gene in the tumor genome. The development of an HER2 receptor antibody, Herceptin that blocked the activation of the protein, was a landmark in cancer therapeutics.8 This was unlike the earlier development in CML where all patients had a specific gene translocation.

Today breast cancer patients are classified with regard to their stage of disease (how far it has spread) and with regard to whether the tumor expresses estrogen receptors, progesterone receptors, HER2 or is “triple negative.” Hence actionable tumor genomics which influences treatment decisions is firmly established in current practice guidelines.

The tumor sequencing studies have played a prominent role in cancer drug development. As mentioned above, a single point mutation in the BRAF gene was found in about 50% of melanomas. BRAF is also a kinase gene and the mutation was at a location that put the protein in a permanently “on” position. That on switch stuck in the on position propagated a signal to activate cell division which drove tumor proliferation.

Medicinal chemists know how to design kinase inhibitors, but in this case a young biotech company, Plexicon, used innovative structural methods to design an inhibitor with inhibitory effects that were relatively specific for the mutated form of the protein.10 All drug treatment involves a trade-off between killing the target cancer cells without killing essential normal cells. Antibiotics are very effective because bacterial cells are very different from our mammalian cells and we can use molecular drug targets which are crucial for bacterial proliferation but do not even exist in human cells. Hence, very high doses of antibiotics can be used without causing undue toxicity and the bacterial cells can be eliminated before resistant clones are selected for. Such selectivity rarely exists with cancer treatment; resistance is common because the tumor cannot be safely treated with a high enough dose. The Plexicon drug was able to be administered at a dose that shut-down oncogenic signaling because of

its selectivity. Their drug was highly effective, a real breakthrough for melanoma (EGFR) which is considered one of the most drug unresponsive of tumors. Unfortunately, in treating patients with advanced metastatic disease, resistance often develops eventually and the drug, although prolonging survival, is not curative.

Other examples of precision medicine in oncology are the use of drugs to block mutated and constituatively activated epidermoid growth factor receptors in lung cancer and the determination that antiEGFR antibodies were only effective in colorectal cancer if the KRAS protein was not mutated.11 As a final example, a translocation in the ALK gene was found in approximately 4% of patients with non-small cell lung cancer (NSCLC). ALK is another kinase and an effective inhibitor, Crezotinib, was developed to turn off the ALK switch, providing extended survival for these patients.12 It used to be conventional wisdom that pharmaceutical companies wanted only blockbuster treatments and hence would not be interested in treatments for small subsets of traditionally defined diseases.

Now however, these corporations appear increasingly interested in tapping into the relatively new and alluring field of personalized treatment.

Challenges While precision has made its debut into the field of oncology, it is mostly based on genomics of the tumor, not the inherited genetics of the patient The new paradigm of drug development over the past decade has been to develop drugs with companion diagnostics to inhibit mutated oncogenes.

This has led to an expansion of the number of diagnostic tests that patients should undergo in order to properly diagnose their disease. This increased complexity is causing problems for some payers in their decisions of what drugs and what tests to reimburse under what clinical circumstance.

The expansion of the number of diagnostic tests used for guiding drug selection has also created an industry for testing for somatic alterations in tumors with regard to a panel of actionable mutations.

This is a highly regulated area as the DNA

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testing must be very accurate and because some genomic alterations in a gene may be actionable while others may not. The panels may involve sequencing some or all of up to several hundreds of genes.

In many cases the treatments that have been developed in this way are much more effective than previous chemotherapy, but in most cases they are not curative. It is hoped that by combining such molecularly targeted drugs in clever ways, cures can be achieved.

The ability to design effective combination regimens rationally is currently limited by understandings of basic tumor biology.

Another challenge to precision oncology is the scarcity of treatments for many commonly occurring mutations. For example, the family of RAS proteins are frequently mutated in multiple types of cancer. These proteins are not kinases, however, and in spite of great investments by the pharmaceutical industry, effective blockage of constitutive RAS activation in tumors is not yet possible.

Similarly, the P53, Rb and MYC transcription factors are inactivated by mutation in many tumors. P53 and Rb are important “tumor suppressors” but restoring activity of a tumor suppressor has proved much more difficult that inactivating a kinase stuck in the “on” state. This has been a persistent roadblock because it is too high risk for both academic investigators and industry.

Medical studies of new treatments is one of the few areas where we as a society have the benefit of good randomized experiments to determine what works and what does not. With the finding that tumors of most primary sites are heterogeneous with regard to their driver mutations, however, a new generation of clinical trial designs has come into use.14 These clinical trials focus eligibility on more homogeneous subsets of patients who share a common driver mutation in the gene which is the molecular target of the test drug. This approach has resulted in an improved success rate and larger average treatment effects. For early phase I and II studies, new “basket” designs are being used in which the mutations in the patient’s tumor are matched against the targets of a panel of drugs and the one is tested which provides the greatest likelihood of benefit.15 Although genomic driven precision medicine is bringing about significant changes in the kinds of clinical trials that are being used to develop more effective

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treatments, the situation is far different from proposals that have been made to conduct therapeutic research based on standard medical practice. The proposal is usually to establish large databases of treatments and outcomes for patients treated in standard practice, to characterize the patients by genotyping them and to try to sort out what treatments work for what types of patients.

Clearly this has severe limitations for cancer research. First it is tumor genomics, not germ-line genetics, which generally determines outcome. Secondly, the current generation of cancer drugs is not adequate for the kind of success we seek. New drugs and new drug combinations generally cannot be used in standard medical practice and so electronically collecting the standard practice experience will limit us to learning about how to use existing treatments. Finally, unless treatment effects are large, controlled trials have generally been needed to reliably compare treatment regimens.

The class of diseases called cancer has turned out to be more biologically complex and more difficult to treat effectively than previously imagined. The battle is being waged by scientists and clinical investigators in a mixture of types of organizations: academic investigators with public or charity support, and the pharmaceutical and biotech industries. There are many challenges, both scientifically, which I have elaborated upon, and politically. However, good policy choices require knowledge of the substantive issues by the policymakers, and I hope that this article can contribute to the accumulation of that knowledge.

References: 1. McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JPA, Hirschhorn JN. Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Reviews Genetics. 2008; 9:356-69.

2. King MC, Marks JH, Mandell JB. Breast and ovarian cancer risks due to inherited mutations in BRCA1 and BRCA2. Science. 2003; 302:643-6.

3. Li FP, Fraumeni JF, Mulvihill JJ, Blattner WA, Dreyfus MG, Tucker MA, Miller RW. A cancer family syndrome in twenty-four kindreds.

Cancer Research. 1988; 48:5358-62.

4. Knudson AG. Mutation and cancer: Statistical study of retinoblastoma. Proceedings of the National Academy of Sciences of the U.S.A. 1971; 68:820-23.

5. Thomas RK, Baker AC, DeBiasi RM, et al.

High-throughput oncogene mutation profiling in human cancer. Nature Genetics. 2007; 39:347-51.

6. Stratton MR. Exploring the genomes of cancer

cells: Progress and promise. Science. 2011; 331:1553-58.

7. Hahn WC, Weinberg RA. Modeling the molecular circuitry of cancer. Nature Reviews Cancer. 2002; 2:331-41.

8. Slamon D, Pegram M. Rationale for trastuzumab (Herceptin) in adjuvant breast cancer trials. Seminars in Oncology. 2001; 28:13-19.

9. Druker BJ. ST1571 (Gleevec) as a paradigm for cancer therapy. Trends in Molecular Medicine.

2002; 8:S14-S18.

10. Bollag G, Tsai J, Zhang J, Zhang C, Ibrahim P, Nolop K, Hirth P. Vemurafenib: the first drug approved for BRAF-mutant cancer. Nature Reviews Drug Discovery. 2012; 11:873-86.

11. Lievre A, Bachet JB, Le Corre D, et al. KRAS mutation status is predictive of response to cetuximab therapy of colorectal cancer. Cancer Research. 2002; 66:3992-5.

12. Shaw AT, Kim DW, Nakagawa K, et al.

Crizotinib versus chemotherapy in advanced ALK-positive lung cancer. The New England Journal of Medicine. 2013; 368:2385-94.

13. Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nature Reviews Cancer. 2012; 12: 252-64.

14. Simon R. Genomic Clinical Trials and Predictive Medicine. Cambridge University Press, 2013.

15. Simon R, Polley E. Clinical trials for precision oncology using next-generation sequencing.

Personalized Medicine. 2013; 10:485-95.

Dr. Richard Simon Richard Simon is Chief of the Biometric Research Program at the National Cancer Institute and head of the Computational and Systems Oncology Branch. Dr. Simon holds a doctoral degree in applied mathematics and computer science from Washington University in St. Louis, Mo. He is a fellow of the American Statistical Association and a former member of the Oncologic Drug Advisory Committee of the FDA. He is the architect of BRB Array Tools software and author of Using Genomics in Clinical Trials and Predictive Medicine (Cambridge U. Press 2013). He is the recipient of the 2013 Karl Peace award of the American Statistical Association “for contributions that have played a pivotal role in bridging the gap among statistics, clinical research, and translational medicine to improve human health”.

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VA Flickr Physicians, veterans, and administrators met at the Tampa VA Medical Center in October to discuss the status of veterans’ healthcare.

FEATURES

Million Veteran Project: A Large Cohort Nested in a Health Care System John Gaziano, MD, MPH and John Concato, MD, MS, MPH Sumitra Muralidhar, PhD Timothy J. O’Leary MD, PhD The Million Veteran Program (MVP) was conceived and implemented to promote genomic discoveries and help bring personalized medicine to the forefront of VA health care. MVP has currently enrolled more than 345,000 Veterans, and genotyping of the first 200,000 Veterans is complete. The program is entering the next phase of making these data available to VA investigators for genomic and epidemiological studies that will inform health care delivery. The MVP cohort will enable researchers to capitalize on the wealth of available genetic samples from ongoing or closed out research efforts during which samples appropriate for DNA analysis are collected. Anticipated studies that may use such a large well-characterized cohort include: investigations of gene-environment (lifestyle) interactions, genome-wide associations, pharmacogenomics, and nutrigenomics. Ultimately, this will result in better ways to prevent, detect, and treat disease.

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hen President Obama announced his Precision Medicine Initiative (PMI)1 much attention was focused on the promise that medical information combined with genetic data could enhance the care of and improve the health of all Americans. Several years before the President announced PMI, the VA launched the Million Veteran Program, and now MVP as part of PMI serves as a model in shaping this new effort and in the development of an additional cohort. The Million Veteran Program (MVP) was launched to establish a national, representative, longitudinal study of Veterans that combines data from survey instruments, the electronic health record, and biospecimens with the intent to explore the genetic and nongenetic factors that affect health and disease.

Advances in the biomedical research and computing capability combined with the availability of electronic medical records provided an opportunity to better understand the factors that affect health and disease in novel ways. Low cost ways to assess genes and activities such as the Human Genome Project1, Hap Map project 2,3 and increasing availability of health care data in an electronic format provide a the feasibility for understanding the human genome in large populations at low cost creating the environment for the establishment of large scale databases and biobanks. Over the last decade or so, several groups established large data and biospecimen repositories with hundreds of thousands of participants, including the United Kingdom 6-8, Vanderbilt University9, the Kaiser Permanente 10, China 11 , and others. These efforts provided a background for the development of MVP. These biobanks provide a resource for studying diseases and condition found in the general population, but are not sufficiently large to examine genetic underpinnings of diseases associated specifically with exposures to combat, extreme conditions, and toxic agents seen frequently in the course of military service. These large-scale activities will need to work together in order to understand how genes impact disease.

The Department of Veterans Affairs (VA) is an ideal setting to construct a mega-data repository and biobank. The Veterans Health Administration (VHA) is the largest integrated national health system in the country, and most of the healthcare experience of the Veterans who use the system has been captured electronically for many years. Other strengths of the VA include over 100 research-ready medical

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centers, a state-of-the-art biorepository, a bioinformatics infrastructure to enable secure handling of genetic and medical data, and an intramural clinical research network that is embedded in the health care environment that includes the Cooperative Studies Program (CSP) supporting multi-site clinical research 16. However, perhaps the most valuable asset is the altruistic Veteran population which has seen the opportunity to participate in research a way of serving the country again. In this summary, we described the design and implementation of this innovative new resources.

Design The intent of MVP was to establish a platform for a wide spectrum of genetic and non-genetic research into health and disease imbedded in and taking advantage of a large health care system, with a specific, but not exclusive, focus on diseases and conditions specifically associated with military service.

Veterans who volunteer for MVP give blood for biobanking, responses to questionnaires, consent for access to data from health records and other sources, and permission to be contacted for future studies. A target of up to one million was selected, balancing issues of study size and cost. This sample size enables representativeness across the entire healthcare system and facilitates a broad range of research opportunities.

VA resources supporting cohort development include two Cooperative Studies Program (CSP) coordinating centers in Boston and West Haven, the VA Central IRB, auditing and monitoring activities, a call center, bioabank, informatics and data management groups and the. Other VA MVP assets include a genomic center at Palo Alto, and a VA data resource at Salt Lake City.

Recruitment Process The source population constitutes active users of VA healthcare who are competent to give informed consent.. Recruitment currently occurrs in-person at about 50 selected VA sites. Recruitment begins with identification of potentially eligible participants who use recruitment sites for care. If a Veteran is willing to come to a VA facility for a study visit, an appointment letter is mailed with a brochure describing information from the informed consent document. Efforts are made to schedule a study visit in conjunction with existing VA

This sample size enables representativeness across the entire healthcare system and facilitates a broad range of research opportunities.

clinic appointments.

During the study visit, informed consent and a HIPAA authorization are obtained from volunteering Veterans, in accordance with all VA policies and an IRB-approved protocol. MVP poses minimal participant risk. Local sites ensure participant safety during recruitment. Coordinating Centers monitor participant safety data, evaluate progress of the study, review project management, conduct statistical analyses, assure quality of data collection, and maintain the confidentiality of study data; and report as necessary to the IRB and VA Central Office.

Data Collection The data collected for each enrollee includes survey data, data obtained from the blood specimen, the data accessed under HIPAA authorization (including VA and non-VA passive collected data, such as health and related data, occupational data, and environmental data).

Self reported data: The two surveys (questionnaires) for MVP augment data that from the EHR. The MVP Baseline Survey collects demographic information, pedigree, health status, lifestyle habits, military experience, medical history, family history, and physical features. The MVP Lifestyle Survey contains questions from validated instruments to provide information on sleep and exercise habits, environmental exposures, dietary habits, and sense of wellbeing.

Biopecimen collection and use: Blood specimens are sent to the VA Central Biorepository in Boston, MA, where they are banked. Collection kits containing the necessary supplies for drawing, packaging, and shipping of the requested sample are mailed to study personnel at each participating site. Specimen handling follows established standard operating procedures; samples are processed on the day they arrive; plasma, buffy coat, and DNA are stored in

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nitrogen freezers.

MVP enables scientific investigations that include genotyping, whole-exome sequencing, and whole-genome sequencing.

An Affymetrix Axiom® Biobank Array, with approximately 723K markers, is the “MVP chip” for genotyping. This array: a) is enriched for exome SNPs; b) has tag SNPs validated for diseases, including psychiatric traits; and c) has been augmented with biomarkers of specific interest to the VA population (including enrichment for African-American and Hispanic ancestry markers, as well as validated markers for common diseases (such as hypertension, prostate cancer, and breast cancer). This approach allows for the genotyping of a manageable and targeted number of SNPs at a very low cost. Sequencing is currently performed on Ilumina® and Ion-Torrent platforms.

Passive Data Collection: Healthcare data is extracted from national VA clinical and administrative databases, including the National Patient Care Database, VAMedicare/Medicaid merge, and national Laboratory and Pharmacy extracts. Additional information can be obtained from nonVA databases, such as the National Death Index. These data can be downloaded and transferred, with appropriate permissions, for use in the MVP in accordance with VA policies.

Data Management and Security The

Genomic

Information

System

for Integrative Sciences (GenISIS) is the informatics infrastructure for storage, integration, retrieval, and analysis of MVP data. GenISIS has four main functions: assist in recruitment activities; track MVPcollected specimens; provide secure data storage; and maintain a secure computing environment for future research analyses. In addition, tools have been developed within GenISIS and in conjunction with VINCI that allow data extracted from the VA EHR to be incorporated into analysis.

To assure confidentiality of patient data, participants are assigned a participant study ID, and specimens are labeled with a preprinted numeric label (specimen code), lacking any participant identifiers. The data linking the specimen code to the participant’s study ID is entered into a password-protected and encrypted (“crosswalk”) database. The data extracted from health and related data sources is also linked using identifiers. All information on sample collection, shipment, sample processing and storage is tracked in a Laboratory Information Management System (LIMS) that is connected to GenISIS. Thus, neither study sites, the VA Central Biorepository, or investigators using the data can link a specimen to participant identity. GenISIS systems and data access are controlled by roles and permissions authorized at the individual-user level, with data and servers behind the VA firewall.

Access to that database is restricted. In addition, application of VHA policies and procedures regarding data, data repositories,

privacy, and information security provide additional protections.

Given that the genetic and other tests are being done for research purposes only, information about the participant’s DNA is not entered into the participant’s electronic medical record. A Certificate of Confidentiality issued by the Public Health Service, Department of Health and Human Services, has also been obtained to help ensure the privacy of the participant’s identity and data.

Progress to date Formal planning for MVP began in 2009, and proposed strategies were soon piloted.

Following protocol approval by the VA Central IRB in 2010, enrollment began in early 2011 at VA hospitals in Boston, MA, and West Haven, CT. The Program later expanded to 7 additional vanguard sites that provided feedback on best-practice procedures. Subsequently, sites were added to reach a steady-state of approximately 50 locations. Sites are selected based on availability of research infrastructure and the pool of eligible veterans.

Approximately 3 million veterans have been invited by mail to participate; more than 500,000 have returned baseline questionnaires. Over 420,000 veterans have enrolled, at a cost of approximately $150 each. Thus, MVP has so far enrolled over 13% of the 3 million veterans contacted by phone; more than 200,000

Robert Turtil, VA Photos VA administrators present findings from the first Veterans Civic Health Index at the National Press Club in Washington, D.C. in April.

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lifestyle questionnaires have been received.

Genotyping of approximately 400,000 samples will be complete by the end of 2015, and another 100,000 in 2016. Subsets of these samples are also undergoing whole-exome sequencing (approx. N=28,000) and wholegenome sequencing (approx. N=2,000), with additional sequencing planned.

Characteristics of participants Baseline characteristics of the first 200,000 participants currently available genotyping data are consistent with the population receiving healthcare from the Veterans Health Administration; most of the participants are male (92.0%), and a majority (55.0%) are between the ages of 50 and 69.

Based on N=224,610 enrolled participants with returned baseline questionnaires and cleaned data. The majority of enrollees are white (77.2%); the African-American population (13.5%) is well represented.

Regarding military service 43.8% of participants reported service in the Army, 19.6% in the Navy, 15.5% in the Air Force, and 11.3% in the Marines. The 20 most common self-reported conditions include hypertension (62.9%), hyperlipidemia (56.6%), depression (28.4%), diabetes (26.9%), and sleep apnea (24.5%). These data are currently being linked to electronic health record information.

Using the resource

Access to MVP data and/or samples is governed by the MVP consent and VA policies and requires scientific review by appropriate committees. Currently, systems for accessing MVP data are being tested by VA paid and Without Compensation (university affiliated) investigators participating in alpha and beta test projects. A phased expansion of access to the broader research community will occur as the computational infrastructure is further developed in collaboration with academic and industry partners.

The current access process allows initial access to crude data to develop research protocols, and access to more detailed data to conduct approved projects. With approval, potential users can conduct (with or without technical assistance) initial data queries for proposal development. Once a project has gone through peer-review and is approved, a study-specific datamart is created for the investigative team. After the analysis is complete, the researcher is expected to retain key findings in GenISIS, with data and analysis routines to be made searchable by future researchers, and with corresponding publications also uploaded.

Early test projects

Robert Turtil, Department of Veterans Affairs A member of the Old Glory Honor Flight visits the Vietnam Veterans Memorial in Washington D.C. 3 million veterans have been invited to participate, and 500,000 of them have returned baseline questionnaires.

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Long-term goals include conducting randomized trials based on results from MVP, as well as developing systems for returning research results to clinicians providing direct patient care.

As an MVP-based, alpha-test activity, a linked but separate project 15 focusing on schizophrenia and bipolar disorder has enrolled over N=9,500 “case” patients, to be matched 1:1 with “control” patients from MVP who do not have corresponding diagnoses nor evidence of medications for those disorders. A genome wide association study (GWAS) is assessing genetic determinants of functional disability in these diseases. As a second and entirely intra-MVP alpha-test activity, a GWAS of posttraumatic stress disorder (PTSD) is underway. Determination of whether or not a participant has PTSD, is algorithmically conducted using the EHR and data from MVP questionnaires, without direct patient contact (except for a small validation study).

This project highlights the challenges, and represents the initial opportunity, of determining phenotype (e.g., case-control status) using database information.

To expand the scope of MVP, an intramural, VA-based Request for Applications (RFA) was announced in September 2014, with an emphasis on phenotyping experience and a focus on encouraging consortia of investigators as “beta testers.”

Among 30 proposals, four projects— addressing cardiac, metabolic, renal, and substance abuse disorders—were approved in the Spring 2015 review cycle, and future RFAs are planned (details pending). Longterm goals include conducting randomized trials based on results from MVP, as well as developing systems for returning research results to clinicians providing direct patient care.

Summary Research using longitudinal cohorts traditionally involves baseline evaluation

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and prospective follow-up of participants for outcome assessment. MVP and other mega-cohorts expands the data available for each participant. In particular, MVP enables linking of survey data and banked biospecimen genetic and in the future other “omic” data to health information in the VA EHR and elsewhere.

MVP’s early success demonstrates the utility of this approach and can serve as a model for the NIH Precision Medicine Initiative. MVP provides an opportunity for basic and population scientists from many disciplines—such as geneticists, statisticians, social scientists mathematicians, informaticists, computational biologists, and many others—to come together to collaborate. MVP also provides a platform to explore health conditions related to military service.

By combining genomic information with medical record and questionnaire data, MVP provides a valuable resource to improve the health of, and healthcare for, U.S. Veterans and the general population. MVP can contribute to a better understanding of the role of genes and the environment in health and disease, and in turn to the transformation of healthcare delivery. MVP could inform clinicians and health systems about how to generate and collect health information.

Dr. John Gaziano

studies from 5 cohorts. Circ Cardiovasc Genet 2009;2:73–80.

Dr. John Gaziano, MD, 9. NCI Cohort Consortium. http://epi.grants.cancer.

MPH is a cardiologist gov/Consortia/publications.html; accessed 9 July 2015. and chronic disease epidemiologist whose 10. The UK Biobank sample handling and storresearch interests inage protocol for the collection, processing and clude the epidemiology archiving of human blood and urine. Elliott P, of chronic dis- eases. He Is Scientific Peakman TC, on behalf of UK Biobank. Int J Epidemiology 2008;37:234–244.

Director of the Massachusetts Veterans Epidemiology Research and Informa11. Allen N, Sudlow C, Downey P, et al. UK Biobank: tion Center, Chief of the Division of AgCurrent status and what it means for epidemioling at Brigham and Women’s Hospital ogy health policy and technology. Health Policy and Professor of Medicine at Harvard Technol 2012;1:123-126.

Medical School.

12. Sudlow C, Gallacher J, Allen N, et al. UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age. PLoS Dr. John Concato Med 2015;12:e1001779. doi:10.1371/journal. pmed.1001779.

Dr. John Concato is Di-

rector of the VA Clinical 13. BioVU. https://medschool.vanderbilt.edu/dbmi/ Epidemiology Research research/projects/biovu; http://www.mc.vanCenter and Professor of derbilt.edu:8080/reporter/index.html?ID=8032.

Accessed 9 July, 2015.

Medicine at Yale University. As a clinician-in14. Kaiser Permanente Research Program on Genes, v e s t i g a t o r, his research interests Environment, and Health. http://www.dor.kaiser. include a fo- cus on identifying and org/external/DORExternal/rpgeh/index.aspximplementing rigorous methods of ?ekmensel=194f64c3_47_48_btnlink. Accessed 9 July, 2015. patient-oriented research. Drs. Gaziano and Concato serve as PIs of the Million 15. Chen Z, Chen J, Collins R, et al. China Kadoorie Veteran Program.

Biobank of 0.5 million people: survey methods, baseline characteristics and long-term follow-up.

Int J Epidemiol 2011;40:1652-1666.

1. Collins, FS. Human genome collection. http:// www.nature.com/nature/supplements/collections/humangenome/index.html. Accessed 9 July 2015.

2. The International HapMap Consortium. A second generation human haplotype map of over 3.1 million SNPs. Nature 2007;449:851-861.

3. The International HapMap Consortium. A haplotype map of the human genome. Nature 2005;437:1299-1320.

4. Holden, AL. The SNP Consortium: summary of a private consortium effort to develop an applied map of the human genome. BioTechniques 2002;32:S22-S26.

5. 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature 2010;467:1061-1073.

6. Roden DM, Tyndale RF. Genomic Medicine, Precision Medicine, Personalized Medicine: What’s in a Name? Clin Pharmacol Ther 2013;94:169-172.

8. Psaty BM, O’Donnell CJ, Gudnason V, et al., CHARGE Consortium. Cohorts for heart and aging research in genomic epidemiology (CHARGE) consortium: design of prospective meta-analyses of genome-wide association

16. Lavori PW, Krause-Steinrauf H, Brophy M, et al.

Principles, organization, and operation of a DNA bank for clinical trials: a Department of Veterans Affairs cooperative study. Control Clin Trials 2002;3:222-39.

17. Kaufman D, Murphy J, Erby L, Hudson K, Scott J. Veterans’ attitudes regarding a database for genomic research. Genet Med 2009;11:329-37.

18. Kaufman D, Bollinger J, Dvoskin R, Scott J. Preferences for opt-in and opt-out enrollment and consent models in biobank research: a national survey of Veterans Administration patients. Genet Med 2012;14:787-94.

19. Harvey PD, Siever LJ, Huang GD, et al. The genetics of functional disability in schizophrenia and bipolar illness: methods and initial results for VA Cooperative Study #572. Am J Med Genet Part B 2014;165B:381-389.

20. Landrigan PJ, Baker DB. The National Children’s Study—end or new beginning? New Engl J Med 2015;372:1486-1487.

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HEALTH HIGHLIGHTS

IMPROVING AMERICAN MENTAL HEALTH POLICY: NO SIMPLE ANSWERS Michael B. Friedman, LMSW Adjunct Associate Professor, Columbia University School of Social Work This article explores the obvious need for improvements in American mental health policy, noting that the complexity of the system results in a wide range of challenging and contentious policy questions that go beyond health policy and involve social welfare policy, disability policy, criminal justice policy, and more.

The complexity arises from the heterogeneity of populations with mental and/or substance use disorders; the range of potentially useful interventions (including but not limited to treatment services); the diverse mix of public and private providers and funding sources; shifting responsibilities among federal, state, county, and municipal governments; and vituperatively competitive ideologies. The author maintains that even though the complexity makes it unlikely that there can be extensive transformation of mental health policy at this time, it also means that there a host of ways in which the mental health system can be made better, just not all at once.

Fueled in large part by rare but highly publicized acts of violence by people with serious mental disorders, a consensus has emerged that the American mental health system is “broken” and must be fixed. This is not a good metaphor. Broken implies that it used to work but that lately it doesn’t. The truth is that the mental health system has always been far from what it should be, that it is better now than it used to be, but that it

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remains imperfect in a host of complicated ways. 1, 2, 3 There has been progress, but for the past 35 years it has been incremental rather than transformational.

One major reason for the failure to transform the mental health system is that it is far more complex than is generally recognized. Mental health policy properly understood is not just a subset of health policy. It is, and must be, an amalgam of

health policy, social welfare policy, criminal justice policy, substance abuse policy, disability policy, education policy, child welfare policy, and more.

That is to say, in order to meet the needs of people with mental and/or substance use problems, we need to address not only their needs for treatment and rehabilitation, but also how they will survive if they are unable to work, how they will be treated if they

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commit or are accused of committing crimes, what rights they have to liberty and to nondiscrimination, how the schools will educate children with psychological problems, how society will respond to children who have traumatic experiences; etc.

Given the heterogeneity of the population in need, mental health policy cannot be as simple as providing more services to more people; services and supports must be responsive to the specific needs of specific populations.

A Heterogeneous Population

Not Just Treatment

Mental health policy is unavoidably complex primarily because people with mental and/or substance use disorders are a heterogeneous population, including: • Adults disabled by severe, long-term mental and/or substance use disorders (1-3% of the adult population)4,5, some of whom are homeless6 or incarcerated in jails and prisons7, many of whom have co-occurring substance use disorders8, and most of whom will die 10-25 years prematurely9 • Adults with diagnosable mental and/ or substance use disorders (22-24% of the adult population)10, who experience considerable emotional pain and some dysfunction, but do not live with severe, long-term disability • Those who will take their own lives (now about 40,000 people per year)11 • Those who commit very rare acts of violence towards others12 • Special populations, such as veterans and military personnel who have a high prevalence of depression, post-traumatic stress disorder, substance abuse, and suicide13 • Children and adolescents with “serious emotional disturbances” that interfere with their education and relationships and sometimes contribute to run-ins with the law14 • Children and adolescents who have diagnosable disorders that cause significant emotional pain and family conflict, but do not cause severe functional impairment • Children and adolescents who are victims of abuse or other trauma that puts them at risk for mental and physical disorders both now and later in life15 • The rapidly growing minority population, for which there are critical issues of access, cultural competence, and discrimination16 • The elder-boomers, a population that will soon be as large as the population of children under the age of 18 and for whom there are critical issues of access, generational competence, and cooccurring cognitive, mental, and physical disorders—including dementia17,18 And more.

Meeting the needs of these diverse populations is not just a matter of providing an array of treatment services. Despite the almost irresistible logic of the idea that people with mental and/or substance use disorders need treatment, in fact some do not benefit from treatment at all, and many need additional or alternative services such as rehabilitation, housing, case and care management, outreach, peer supports, advocacy, social supports, family support, accommodations for disabilities, protection of rights, court diversion, income supports, preventive interventions, and more.

As a result, expansion of mental health services is an extremely complex matter contributing to any number of tough policy questions. What forms of intervention should be emphasized or de-emphasized in the course of building a better mental health service system? Treatment? If so, what forms of treatment? Inpatient? Outpatient?

In-home?

Crisis? Verbal?

Psychiatric medications? ECT? Involuntary treatment?

Outreach and engagement?

Early intervention? Evidence-based practices?

Or should a reformed system emphasize recovery-oriented rehabilitation above all else?

What about creating the kinds of social conditions that are necessary to help people with psychiatric disabilities lead satisfactory lives in the community? Shouldn’t housing be at the center of all mental health policy development? How should the criminal justice system be changed? What about income supports? What about supports for families that provide housing and other care for disabled family members?

And what about preventive interventions?

Early intervention and preventing the development of a mental or substance use disorder completely seem like obvious goals of a better system, but each raises thorny

policy questions. Should we intervene at the first signs of mental disorders or will that result in unnecessary treatment and overuse of medication?

Should we intervene extensively after a first psychotic break rather than hoping that this person will be one of those having a transient episode that will never return?

Primary prevention is particularly challenging because it largely depends on identifying the social determinants of mental and substance use disorders and intervening in the social conditions that contribute to later problems in life. Social determinants include family violence, living in dangerous communities, poor early childhood education, poverty, and more.

Real prevention calls for extensive changes in the American society. Is that possible? What role should the mental health system play in bringing about social change?

Many Providers, Many Perspectives, Many Interests Policy questions are made even more complex because of the incredible range of providers in the United States.

This includes an array of mental health professions: psychiatry, psychology, social work, nursing, school, mental health, and family counseling, mental health management, health economics, and more.

Increasingly, primary care physicians are the major providers of mental health services, relying on medications as the treatment of choice.19 In addition, there are both public and private sectors of providers. The public sector includes mental health and substance abuse services of many kinds that are run by states, local governments, community agencies, and general hospitals. The Veterans’ Administration and the military are major providers of mental health and substance abuse services. In addition, many schools and child welfare organizations as well as organizations in other systems, including jails and prisons and nursing homes, provide clinical services. Over the past decade or so, more and more mental health services are being provided by community health centers.

The private sector, which is the source

Real prevention calls for extensive changes in the American society. Is that possible? What role should the mental health system play in bringing about social change?

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of behavioral health services probably for most people who get such services, includes behavioral health and physical health care professionals in solo private practice or in small groups. There is now a trend to establish large, group medical practices, which increasingly provide some behavioral health services.

In addition, many employers, especially large employers, provide services to address the personal needs of their employees and their families. This includes employee assistance, disability management, and wellness programs addressing stress and depression in the workplace. In addition, employers design the mental health benefits in the health plans that they fund, which cover more than half of all Americans.20,21 The private sector also includes the pharmaceutical industry. About 30% of current behavioral health spending in the United States is for psychiatric medications.22 The multiplicity of providers leads to a host of policy issues including the appropriate scope of practice of different professions, appropriate roles of governmental and non-governmental providers, the legitimacy of profiting on human suffering, the likely overuse of medication, conflicts of interest, and many more.

Multiple Funding Sources Improving the American mental health system depends to a large extent on both the structure and amount of available funding.

Although the Affordable Care Act (ACA) promises to increase access to behavioral health services and promotes integrated service delivery, current funding structures often don’t align well with service goals and need to be restructured so that they support higher quality and more appropriate services, as well as increased access and integration.

Given the number of funding sources and their specific goals, this is far easier said than done. Medicaid, Medicare, and private insurance are designed to fund treatment and some rehabilitation services that are “medically necessary.”24,25 State governments and, to some extent, local governments also provide funds for mental health services that can go beyond medical models of care.

But over the years, states have increasingly transferred financial responsibility to the federal government by relying more and more on Medicaid.26 This has resulted in substantial increases in total funding for behavioral health services (estimated to have been $240 billion in 2014)27, but it has vastly

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limited flexibility to use non-medical services that can make life better for people with serious mental illness.

Currently underway are a number of major experiments in using managed care both to contain costs and to increase the flexibility to use Medicaid funds in ways that improve overall care for people with serious mental illness and avoid unnecessary hospitalization. These new models are also designed to integrate mental health, substance abuse, and physical health services. The hope is to keep people with serious mental illness healthier and ultimately to increase their life expectancy, which currently is much lower than the general population. We do not yet know whether these new forms of mental health management will result in slowed cost growth and better care—a promise that has been made, but not been kept, at every stage of major change in mental health policy since Dorothea Dix pressed for asylums in the mid-19th century.

The Federal Government and others also provide funds for research, demonstrations, and workforce development.

A host of policy issues related to funding emerge from all of this. Should government and private health insurers move beyond the medical model? Will the complex models of managed care actually benefit people with behavioral health problems? Will the ACA effectively achieve parity and integration between behavioral and physical health coverage? What sort of research should government fund—mostly biomedical or also services research? And many, many more.

Multiple Levels of Government Improving mental health policy in America is further complicated by the fact that federal, state, county, and municipal governments “share” responsibility for mental health policy.28 Although all these levels of government do in fact take on a variety of tasks related to mental health, they also engage in constant efforts to transfer funding responsibility to other levels of government. This results in frequent debates about which level of government should be responsible for what.

There are also frequent debates regarding restructuring the relationships among different levels of government and about restructuring at each level of government.

Should there be an Assistant Secretary for behavioral health in HHS? 29 Should States merge mental health and substance abuse departments? 30 Should state and local mental

health departments be merged into their health departments? Should local schools become service centers for families and children experiencing emotional problems?

Competitive Ideologies Compounding the complexities already noted are vituperative differences in ideologies.

Some people who care about mental health have a libertarian bent; some have a protective bent. Those who are more or less libertarian want to protect the rights of people said to be “mentally ill”. They are willing to accept some of the inevitable hazards of liberty for the sake of avoiding unjust incarceration and loss of personal privacy.31 Those who tilt towards protection believe that we should change the criteria for involuntary inpatient and outpatient commitment so as to reduce risks of harm to self or others.32 They also believe that we should change the rules of confidentiality so as to be able to share information more easily with families.33 Some—but not all— also believe that America has gone too far in reducing inpatient utilization and insist that more people should be admitted to hospitals and stay there longer. 29,34 A few call for a return to asylums.35,36 Is it possible to bridge these ideological differences?37

It Can Be Better The incredible complexity of American mental health policy, the conflicting interests that arise from it, and the range of ideologies that drive it make it unlikely, I believe, that there can be extensive transformation of mental health systems at this point in history. What bold stroke or strokes would leverage vast change that would help the diverse populations of people with mental and/or substance use disorders? More coercive interventions and more long-term in-patient care, as some suggest, could conceivably benefit a very few people with severe, unrelenting disorders and might infinitesimally reduce violence in America, but what about everyone else with behavioral disorders?

Development of a “recovery orientation” throughout the system is the right thing to do for people with psychiatric disabilities but is mostly meaningless to people with transient disorders that are not disabling.

Integration of behavioral health services into

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primary physical health care unquestionably could result in more identification and treatment of mental and/or substance use problems, but it does not address a host of issues in the lives of people with severe and persistent disorders. Innovative managed care enterprises integrating behavioral and physical health care may or may not improve care for people with co-occurring chronic conditions who are eligible for Medicaid, but the impact on other populations will be limited at best. Assuring that everyone has full coverage of mental health services equal to the coverage provided for physical health services would probably result in some increase in access to treatment, but not in better treatment, better living conditions, a fairer criminal justice system, more effective preventive interventions, etc. So far as I can tell, there is no bold stroke on the horizon that would revolutionize the mental health system.

Does that mean that improving the mental health system is impossible? Not at all. The complexity actually means that there a host of ways in which the mental health system can be made better, just not all at once. We should take steps to make treatment more accessible and of much higher quality. We should promote integration. We should work to reduce suicide, to build a bigger and more competent workforce, to overcome stigma, to reform the criminal justice system, to re-evaluate America’s income supports, to follow through on the requirements of the Americans with Disabilities Act, to prepare for demographic changes, to meet the mental health needs of veterans and military personnel, to change social conditions so as to reduce the risks that contribute to growing up with mental and physical disorders, and on and on and on.

With persistent advocacy much has been accomplished since the advent of community mental health policy but not nearly enough.

We can do better. We just need to keep at it.

Michael B. Friedman, LMSW, teaches mental health policy at Columbia University School of Social Work. He is the retired founder and Director of the Center for Policy, Advocacy, and Education of the Mental Health Association of New York City. He can be reached at mf395@ columbia.edu.

REFERENCES Grob, GN The Mad Among Us: A History of the Care of America’s Mentally Ill. Free Press.

1994 Frank, RG and Glied, SA. Better But Not Well: Mental Health Policy in the United States Since 1950. Johns Hopkins University Press, 2006.

Glied, SA and Friedman, MB. “Improving The American Mental Health System Requires Accurate History”. The Huffington Post, August 20, 2014. Available at: http://www. huffingtonpost.com/michael-friedman-lmsw/ improving-the-american-me_b_5664260.html.

Kessler, RC et al. “Prevalence, Severity, and CoMorbidity of DSM IV Psychiatric Disorders in the National Comorbidity Survey Replication”.

Archives of General Psychiatry. June 2005.

Available at: http://archpsyc.jamanetwork. com/article.aspx?articleid=208671&gt.

U.S. Surgeon General. Mental Health: A Report of The Surgeon General. 1999. Available at: http://profiles.nlm.nih.gov/ps/access/ NNBBHS.pdf U.S. Substance Abuse and Mental Health Services Administration. Current Statistics on the Prevalence and Characteristics of People Experiencing Homelessness in the United States. July 2011. Available at: http:// homeless.samhsa.gov/ResourceFiles/hrc_ factsheet.pdf.

National Institute of Corrections, Justice Center of the Council of State Governments, and The Bureau of Justice Assistance. Adults with Behavioral Health Needs Under Correctional Supervision: A Shared Framework for Reducing Recidivism and Promoting Recovery.

2012. Available at https://www.bja.gov/ Publications/CSG_Behavioral_Framework. pdf.

U.S. Substance Abuse and Mental Health Services Administration (2014). Mental and Substance Use Disorders. Available at: http://www. samhsa.gov/disorders.

Insel, TR “Mortality and Mental Disorders”.

Director’s Blog, February 24, 2015. Available at: http://www.nimh.nih.gov/about/ director/2015/mortality-and-mental-disorders. shtml.

Kessler, RC et al. “US Prevalence and Treatment of Mental Disorders 1990-2003” in New England Journal of Medicine, June 16, 2005. Available at: http://www.ncbi.nlm. nih.gov/pmc/articles/PMC2847367/pdf/ nihms-176713.pdf.

American Foundation for Suicide Prevention (2015). “Facts and Figures”. Available at: https://www.afsp.org/understanding-suicide/ facts-and-figures.

Harvard Mental Health Letter, “Mental Illness and Violence”. January 2011. Available at: http://www.health.harvard.edu/newsletter_ article/mental-illness-and-violence.

U.S. Substance Abuse and Mental Health Services Administration (2014). Veterans and Military Families. Available at: http://www.samhsa. gov/veterans-military-families.

U.S. Centers for Disease Control (2013). Mental Health Surveillance Among Children—United States, 2005-2011. Morbidity and Mortality Weekly Report. May 17, 2013. Available at: http://www.cdc.gov/mmwr/pdf/other/

su6202.pdf.

Chapman DP et al. “Adverse Childhood Events As Risk Factors For Negative Mental Health Outcomes” in Psychiatric Annals, May 2007.

Available at: http://www.theannainstitute.org/ ACE%20folder%20for%20website/51%20 ACE%20risk%20factors%20for%20 negative%20MH%20outcomes.pdf.

U.S. Substance Abuse and Mental Health Services Administration (2015). “Behavioral Health Equity”. Available at: http://www.samhsa. gov/behavioral-health-equity.

Geriatric Mental Health Alliance of New York.

Geriatric Mental Health Policy: A Briefing Book. Center for Policy, Advocacy, and Education of The Mental Health Association of NYC. 2009. Available at: http://www. networkofcare.org/library/Briefing%20book-Policy%20in%2021st%20century.pdf.

Friedman, MB. “Generational Competence: A New Conceptual Framework”. Mental Health News. Spring 2011. Available at: http:// michaelbfriedman.com/mbf/images/stories/ GENERATIONAL_COMPETENCE.pdf Wang, PS et al. “Changing Profiles of Service Sectors Used for Mental Health Care In the United States”. American Journal of Psychiatry. July,2006. Available at: http:// ajp.psychiatryonline.org/doi/pdf/10.1176/ ajp.2006.163.7.1187 Goetzel, RZ et al. “The Business Case for Quality Mental Health Services: Why Employers Should Care about The Mental Health and Well-Being Of Their Employees”. Journal Of Occupational and Environmental Medicine.

May 2002. Available at: http://journals. lww.com/joem/Abstract/2002/04000/ The_Business_Case_for_Quality_Mental_ Health.12.aspx Smith, JC and Medalia, C. Health Insurance Coverage in the United States: 2013. U.S. Census Bureau, September 2014. Available at: https://www.census.gov/content/dam/ Census/library/publications/2014/demo/ p60-250.pdf Mark, TL et al. “Spending on Mental and Substance Use Disorders Projected to Grow More Slowly Than All Health Spending Through 2020”. Health Affairs. August 2014.

Available at: http://content.healthaffairs.org/ content/33/8/1407.abstract.

Mechanic, D et al. “The Financing and Delivery of Mental Health Services”. Chapter 7, Mental Health and Social Policy: Beyond Managed Care 6th Edition. Pearson. 2014.

U.S. Center for Medicare and Medicaid Services.

“Medicaid Documentation for Behavioral Health Practitioners”. July 2014. Available at:http://www.cms.gov/Medicare-MedicaidCoordination/Fraud-Prevention/MedicaidIntegrity-Education/Downloads/docmattersbehavioralhealth-factsheet.pdf Hopkins, E. “What ‘Medically Necessary’ Means and How It Affects Your Medicare Coverage”.

Medicare.Com. May 2015. Available at:https://medicare.com/medicare-news-andtips/what-medically-necessary-means-andhow-it-affects-your-medicare-coverage/ Buck, JA. “Medicaid, Health Care Financing Trends, and the Future of State-Based Public Mental Health Services.” Psychiatric Services, July 2003. Available at: http://www.ncbi.nlm.

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German Tenorio HEALTH HIGHLIGHTS

Immigrants Face Barriers Both as Health Care Patients and Providers Leighton Ku, PhD, MPH Abstract: Despite recent efforts to expand health insurance coverage and access to medical care in the United States, significant gaps persist for immigrants, particularly those who are undocumented and legal immigrants who have not yet become citizens. Some of these disparities exist because of federal exclusions aimed specifically at immigrants. It is paradoxical that, while the nation imposes barriers for immigrants as patients, immigrant clinicians play a critical role as health care providers. Immigrant physicians, for example, form a very large share of the primary care physician workforce and are particularly important in providing care for patients in disadvantaged areas. More can be done to ensure that the U.S. is providing equal care and equal opportunities for all.

A

lthough America has been called a nation of immigrants, immigrants are often placed at the fringes of our health care system, both as patients and as health care providers. The U.S. has laws and policies that prohibit discrimination on the basis of gender, race, religion or national origin, but it is often permissible to discriminate on the basis of immigration status. These policies affect immigrants’ ability to receive care and to bestow care.

Even when they have severe needs for care, due to medical or financial problems, many immigrants are unable to get the care they need. It is paradoxical that although many immigrants encounter major barriers to adequate care as patients, the nation’s primary health care system relies heavily on

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the availability of immigrant and foreigntrained clinicians.

Immigrant status categories are numerous and complex.

Millions of foreign-born immigrants eventually become naturalized citizens. Millions more are lawful permanent residents with green cards who enter and remain in the U.S. legally, but who have not yet attained citizenship. Many are admitted as refugees and asylees and have many of the same privileges as lawful permanent residents. Temporary immigrants include visa holders who may reside in the U.S. for a limited time as workers, students or other categories, provided that they remain in that status. And finally there are undocumented immigrants who entered illegally or have overstayed their visas, but

there are legal distinctions even within that category. Many are in a “pending” gray zone as the government seeks to determine the appropriate immigration status. U.S. born children of immigrants are native-born U.S. born citizens under the 14th Amendment, but might still encounter problems. For example, the state of Texas has refused to provide birth certificates to some U.S.-born babies of undocumented women, because the mothers lack satisfactory proof of their identities. The legal rights and responsibilities for each demographic of immigrants differ.

While the immigrant population is diverse and spans the full spectrum of American society, immigrants, particularly those who are undocumented or who have not yet become citizens, are often disadvantaged. Non-citizen immigrants are disproportionately poor and generally have less access to health insurance, which in turn limits their access to health care services. As seen in Exhibit 1, non-citizen immigrant adults (including both legal and undocumented immigrants), are almost three times as likely to be uninsured as U.S.born citizens. The lack of health insurance weakens their financial access to health care.

Non-citizen immigrants are significantly less likely to have received primary medical care, visited an emergency department or been admitted to a hospital in the past 12 months than those who are US-born.

Since they use less health care, much less is spent on immigrants’ health care.

The average per capita cost of health care

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received by undocumented immigrants is about one-quarter that of US-born citizens, while the average cost for legal non-citizen immigrants is about half as high as for citizens. The level of publicly-funded health care – including charity care – received by the undocumented was about one-tenth the level of public subsidy for citizens while the legal non-citizen immigrants received less than one-quarter the level of citizens.

The gaps in immigrants’ health insurance coverage mainly stem from two problems.

First, many immigrants are in low-wage, low-skill jobs that do not offer work-based health insurance. Work-based insurance is the primary source of insurance coverage for most Americans. If immigrant workers cannot get coverage, their families may also go uninsured.

Second, publicly-funded health insurance programs, such as Medicaid, Medicare or the federally-subsidized health insurance exchanges generally exclude undocumented as well as many legal immigrants. A 1996 welfare reform law eliminated eligibility for Medicaid (and other public benefits) for legal immigrants who had been in the U.S. for less than five years; the undocumented were already ineligible. The 2010 Affordable Care Act denies undocumented immigrants coverage in the newly created health insurance exchanges, although it creates some new insurance opportunities for legal immigrants. A particular paradox is that while undocumented workers, like citizen workers, contribute to the Medicare Trust Fund through payroll deductions, the undocumented are barred from receiving Medicare when they retire; this creates a surplus that helps sustain the Medicare Trust Fund for citizens.

Underlying these policies that discriminate against immigrants is deep social and political discord about the role of immigrants, exemplified recently by Presidential candidate and tycoon Donald Trump’s inflammatory statements about Mexican immigrants and the backlash that followed.

An additional factor that can impair immigrants’ access to care is language barriers. Although almost 40 million U.S. residents speak Spanish at home, many Latino immigrants cannot find clinicians who speak their language or get assistance from an interpreter. Asians, Africans and Europeans who speak less common languages must hurdle even higher linguistic barriers. To reduce barriers related to national origin, Federal policy requires that

The lack of health insurance weakens immigrants’ financial access to health care. Non-citizen immigrants are significantly less likely to have received primary medical care, visited an emergency department or be admitted to a hospital in the past 12 months than those who are US-born. health care providers offer free language assistance to those who do not speak English well, but language problems still occur every day in clinical settings across the nation.

Cultural differences may also affect access.

For example, mental illness is stigmatized in many cultures, so fewer immigrants might seek care when they need help. And because behavioral counseling requires that the therapist and patient be able to discuss intimate and complex problems, potential language barriers become even more significant in behavioral care.

A variety of alternative mechanisms have developed to help immigrants. About half the states have taken a 2009 option to offer Medicaid to legal immigrant children without a five-year waiting period. Four states offer state-funded health insurance to lowincome children regardless of immigration status, so that undocumented children can get coverage. California just became the fourth state in July 2015. But in the rest of the country, immigrants, particularly undocumented adults, face great difficulty finding access to health insurance unless it is offered through their jobs.

A result is that both legal and undocumented immigrants often rely on

safety net health care providers, such as community health centers or missiondriven charity hospitals, for care. These facilities may offer free or reduced price care to patients, regardless of insurance or immigration status. However, safety net providers typically have limited funding and capacity and are also responsible for serving uninsured citizens, who usually outnumber uninsured immigrants, so they struggle to keep pace with demand for care. Because so many safety net patients have limited English skills, community health centers and safety net hospitals often make special efforts to have clinicians or interpreters with appropriate linguistic and cultural skills, but their availability and capacity are also limited.

While immigrants face a variety of barriers receiving health care, it is important to understand that the U.S. health system relies on immigrants to serve as health care providers. For example, almost one-quarter of medical residents (those receiving specialty training after medical school) are educated abroad and the majority of international medical graduates are non-citizen immigrants. (The other international medical graduates are U.S. citizens who studied abroad.) Immigrant and internationally-

Leighton Ku, PhD, MPH is a professor and interim chair of the Department of Health Policy and Management in the Milken Institute School of Public Health at George Washington University and is the Director of the Center for Health Policy Research. He is a nationally-known health policy researcher and analyst who is particularly known for his research about health access for disadvantaged populations, including immigrants, and the roles of Medicaid and health reform in improving their status. He has published articles in journals like Health Affairs, New England Journal of Medicine and the American Journal of Public Health, written numerous policy briefs aimed at policy and program audiences and testified before Congress about immigrant health. He helped establish the state-based health insurance exchange in the District of Columbia. Prior to coming to GW, he worked at the Urban Institute and the Center on Budget and Policy Priorities.

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trained physicians are particularly important in the provision of primary medical care that serves as the frontline of patient care in the US. About two-fifths of residencies in internal medicine, one-third of family practice and one-quarter of pediatric residents – the main primary care areas – are filled by immigrant or internationally-trained physicians. Citizens trained in U.S. medical schools predominantly select specialty areas (such as surgery, radiology, etc.) which tend to be more highly paid.

Both law and practice create requirements for immigrants that do not apply to the majority of physicians.

Internationally-trained physicians, whether citizens or not, must pass additional tests that demonstrate their linguistic and medical skills before entering residencies and almost half the applicants are screened out by this process. To train or practice in the U.S., immigrant physicians must obtain visas and, in order to qualify for a visa, many must agree to practice in a low-income or rural area with an insufficient supply of physicians.

While these policies create restrictions for immigrant clinicians, it helps them meet the medical needs of patients, most of whom are citizens, in areas where it would be otherwise difficult to find a doctor. The importance of immigrants in the health care workforce is not confined to physicians; immigrants also hold jobs as nurses, pharmacists, medical technicians, health care aides and so on.

As important as immigrant clinicians are to the American health care workforce, there are criticisms of the system. When immigrants who grew up and received training in a less developed nation come to the U.S. their home nations lose their skills and knowledge, which may reduce access to care in their home nations.

The U.S. has not yet established a level playing field or equitable policies for immigrants as patients or as health care providers. But, of course, these inequities apply not only in health care policy, but in many areas of public policy. Broader immigration reform, with potential goals of creating a pathway to citizenship as well as making it simpler for high skilled immigrants to join the U.S. workforce, has been under debate for many years, but has continued to flounder on the shoals of political and social controversy. Despite the efforts to increase insurance coverage and access to care under the Affordable Care Act, the nation still faces difficulties in ensuring that we can provide equal care or equal opportunities for all.

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Figure 1. Health insurance and access to medical care in the past 12 months, adults 18-64.

66% 41%

43% 19%

16%

No health insurance

Saw a primary care physician

US-born citizen

12%

Visited emergency department

8% 5% Admitted to a hospital

Non-citizen immigrant

Sources: Author’s analysis of the 2014 Current Population Survey and the 2013 National Health Interview Survey. All differences are statistically significant.

Figure 2. Percent of Medical Residents Who Are Immigrants or Internationally Trained, by Field 42% 34%

Internal Medicine

Family Medicine

23%

21%

Pediatrics

All Other Specialties

Sources: Accreditation Council for Graduate Medical Education, 2014

REFERENCES Hennessey-Fiske M. Immigrants sue Texas over services for persons with limited English state’s denial of birth certificates for U.S. born proficiency. Aug. 11, 2000. children. Los Angeles Times. July 18, 2015.

Megerian C, Mason M. California budget deal Derose K, Bahney B, Lurie N, Escarce J. Review: grants health coverage to children in U.S. Immigrants and health care access, quality, and illegally. Los Angeles Times. June 16, 2015. cost. Med Care Res Rev. 2009 Aug; 66(4):355- Accreditation Council of Graduate Medical 408.

Education. Data Resource Book: Academic Stimpson J, Wilson F, Su D. Unauthorized Year 2013-14. 2014. immigrants spend less than other immigrants Educational Commission for Foreign Medical and U.S. natives on health care. Health Affairs.

Graduates. http://www.ecfmg.org/ 2013; 32(7): 1313-8. certification/index.html Ku L. New opportunities to increase legal immigrants’ health insurance coverage. Blog at http://www.commonwealthfund.org/ publications/blog/2013/dec/legal-immigrantshealth-insurance Zallman L, Wilson F, Stimpson J, et al.

Unauthorized Immigrants Prolong the Life of Medicare’s Trust Fund. J Gen Intern Med. June 18, 2015. Epub ahead of time.

Associated Press. Donald Trump isn’t backing away from immigrant comments. New York Times, July 6, 2015.

Executive Order 13166. Improving access to

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Photo from Flickr, Creative Commons Public Domain Dedication.`

HEALTH HIGHLIGHTS

Lessons from Indiana: the case for broader implementation of syringe exchange programs By: Monica S. Ruiz, PhD, MPH, Sean T. Allen, MPH, and Allison O’Rourke, MPH This paper examines the recent HIV outbreak in Indiana and discusses the role of syringe exchange programs (SEPs) as effective interventions for HIV prevention in the US. We also briefly discuss the historical origins of legislation that govern SEP and how some of these policies impede broader implementation of this intervention. Finally, we present evidence for why these policies must change in order to more effectively contain the syndemic of HIV and substance use.

I

n 2015, the United States experienced something it hadn’t seen for three decades: a HIV outbreak.

On February 25th, the Indiana State Department of Health reported a quickly growing HIV outbreak in rural Scott County.1 Thirty cases had been identified since midDecember 2014. Less than a month later, there were 68 cases.2 As of July 14, 2015, 174 cases were confirmed3, the vast majority linked to injection of prescription opiates.

This outbreak of injection drug use (IDU)-associated HIV is a wakeup call about substance use in the US. The fact that the outbreak occurred in the rural Midwest, far away from urban centers typically associated as IDU hubs, highlights public misconceptions about where drug use occurs. It also highlights the importance of having comprehensive HIV prevention interventions, such as syringe exchange programs (SEPs), in geographically diverse locations. Unfortunately, wider SEP implementation is not possible due to policy restrictions at federal, state, and local levels.

This paper provides a brief overview of SEPs as effective interventions for HIV

prevention in the US. We explore some of the policies that impede implementation and present evidence for why these policies must change in order to more effectively contain the syndemic of HIV and substance use.

Why Needle and Syringe Exchange?

In 2011, 6% and 14% of new HIV infections in men and women (respectively) in the US were attributed to IDU.4 Although this is a significant decline in IDU-associated infections since the late 1980s, new cases are still diagnosed.5 Hepatitis C (HCV) risk is also significantly higher with IDU; data from 55 countries show HCV prevalence rates as high as 20-50% among persons who use injection drugs (PWID).6 SEPs are a staple component of HIV

prevention strategies based on the harm reduction model of behavior change7, which “meets people where they’re at” in their addiction without requiring people to change behaviors before they are ready.8 This strategy is highly acceptable and highly effective in addressing the needs of marginalized populations.9,10 Further, studies show that SEPs are not associated with increased crime or illicit drug use.11 The first SEPs in the US were established in the late 1980s.12 According to the North American Syringe Exchange Network (NASEN), there are 194 SEPs operating one or more sites in 33 states, the District of Columbia, the Commonwealth of Puerto Rico, and the Indian Nations.13 Since the implementation of SEPs, IDU-attributable HIV incidence in the US has declined by approximately 80%14; this is the only category of adult HIV infection to show declines of this magnitude.15 The Politics of Policy Change for SEP Policies affecting SEP implementation occur at multiple levels of government. Laws governing drug use and “paraphernalia” (i.e., injection equipment) possession – such as the Harrison Act of 1914 -- were rooted in the perception of addiction as a criminal rather than public health issue.16 Many states passed their own paraphernalia

SEPs are a staple component of HIV prevention strategies based on the harm reduction model of behavior change, which “meets people where they’re at” in their addiction without requiring people to change behaviors before they are ready.

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laws, including policies restricting sales or distribution of sterile injection equipment.17 In some cases, state or municipal-level paraphernalia legislation was changed to allow SEP implementation. In other cases, policy changes were a direct response to public health crises, such as extraordinarily high HIV rates in PWID (e.g., Philadelphia, 1992) or evidence of a disease outbreak (e.g., Indiana).

There is Federal legislation specifically governing SEP. In 1988, Congress passed legislation prohibiting the use of federal monies to support SEPs.18 This legislation, known as the “Federal Ban”, was removed in 200919 and subsequently reinstated in 2012.20 During the two years in which the Ban had been lifted, only three US SEPs received federal funding.21 With the Ban’s reinstatement, restrictions on the use of federal monies apply to purchasing injection equipment as well as supporting personnel and delivery modes (e.g., vehicles) to distribute injection equipment.22 The Federal Ban remains despite the fact that the need for comprehensive prevention approaches for PWID is reflected in the National HIV/ AIDS Strategy.23 Washington, DC is in a class of its own with regard to legislation on SEP implementation, as both Federal and locallevel legislation govern the city. In 1998, Congress proscribed the use of federal funds for SEP in the Financial Services Appropriations Bill. While this legislation

did not affect states and localities, DC was affected due to Congress’ oversight of the city’s budget and operations through the Financial Services legislation. Thus, there were PWID in need of HIV prevention services, and DC was the only US city prohibited from using municipal revenue for SEPs. The “DC Ban” remained until December 2007, when a version of the

“Policy analyses conducted a priori should inform policymakers on optimal policy option that has maximum cost-effectiveness, community level impact, political viability and sustainability, etc.”

2008 Financial Services Bill without the Ban language was signed into law.

Ideally, the formation of any public policy should be rooted in rational interpretation of data, analysis of available policy options, and the consideration of the potential consequences.24 Policy analyses conducted a priori should inform policymakers on optimal policy option that has maximum cost-effectiveness, community level impact, political viability and sustainability, etc.

Having said this, there are many -- such as Meier25 and Bowen26 -- who contend that this rational model of policymaking does not apply to the US’ policy on SEP. Bowen goes further, arguing that US drug policy as

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a whole is “a charged issue, largely driven by values and morals, instead of logic, economics, and principles of public health.”27 This irrationality extends to community-level policy decisions, manifested through “not in my backyard” ideologies that marginalize already disenfranchised groups, such as PWID, the homeless, and the mentally ill.28

Our research on the use of research evidence as a foundation for policy change associated with SEPs in Baltimore (MD), Philadelphia (PA), and DC supports this idea. While morality arguments arose in each city context, the application of evidence to change policy was different in each city.

In Baltimore and Philadelphia, research guided policy discussions and helped change policymakers’ and constituents’ conceptualizations about substance use and the utility of SEPs. In DC, the unwillingness of Congressional SEP opponents to consider research evidence proved to be a significant impediment. Several stakeholders described Congress as an “evidence-free zone” where SEP opponents misinterpreted research findings or took evidence out of context to support their opinions. One person commented, “…Whether you quoted from scientific journals…and…statistical evidence, from what was happening across the United States, none of it mattered.”29 To our knowledge, no one has conducted a priori analyses to determine the soundness of changing legislation to allow SEP implementation. But could SEP policy be examined post hoc using some of the same criteria used in a priori analyses? Does SEP measure up in terms of two particularly important criteria – epidemic impact and cost effectiveness -- for control of the HIV/ AIDS epidemic?

Do SEPs Have Epidemic Impact?

Research evidence overwhelmingly demonstrates that SEPs successfully reduce HIV incidence as well as injection-related practices that increase HIV and HCV risk.30,31,32,33,34,35,36 Data from the earliest SEPs are the most impressive: in Tacoma, SEPs

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the average lifetime cost of treating HIV at $380,000 USD per person.47 Subtracting SEP operational costs, averting 120 cases of HIV translates to an approximate cost savings of $44.3 million USD.48 Given that the clinical care (including prescriptions) of many HIVpositive DC residents is covered by the city’s publicly funded health plan, costs saved in treatment are direct savings to DC taxpayers.

Photo from Flickr, Creative Commons Public Domain Dedication were associated with an over 80% reduction in the incidence of hepatitis B and C infections.37 Similarly, SEPs were associated with a 33% reduction in HIV infection in New Haven, CT,38 and a 70% reduction in New York, NY.39 While studies have examined changes in HIV incidence associated with the presence or absence of SEPs, our own research specifically looks at the epidemic impact of policy change – in this case, the DC Ban’s removal – as a naturally occurring policy intervention for HIV prevention for PWID. It is important to note that DC had a small, privately funded SEP during the time of the DC Ban so the examination of epidemic impact is not about the SEP’s presence or absence. The DC Ban’s removal was

as an effective HIV prevention intervention, but also shed light on the role of poor public health policy as a determinant of HIV risk.

Are SEPs Cost Effective?

Abundant, compelling evidence supports SEPs’ cost-effectiveness.

Numerous modeling studies show that widespread clean syringe access results in substantial financial savings compared to costs associated with lifetime HIV treatment.41,42,43,44 Lurie and Drucker estimated that between 4,394 (15% incidence reduction) and 9,666 (33% incidence reduction) HIV infections could be averted as a result of implementing SEPs nationally, resulting in a $244 to $538 million (in 1997 USD) costs savings to the US healthcare system.45 Extrapolating to 2015

“Our findings not only provide support for SEP as an effective HIV prevention intervention, but also shed light on the role of poor public health policy as a determinant of HIV risk.” important because the policy change allowed for the allocation and use of resources to ramp up SEP services. We estimated that the policy change – and the services that were implemented as a result – averted 120 new infections in the first two years alone.40 Our findings not only provide support for SEP

USD, the savings are approximately $361 to $796.5 million.46 Our research found similarly impressive cost-savings. In the two years following the DC Ban’s removal, we estimated 120 averted HIV infections. The Centers for Disease Control and Prevention (CDC) estimated

The Way Forward The evidence discussed above is only a brief summary of SEP impact, as providing a comprehensive overview of such research is beyond the scope of this paper. Nonetheless, the data are clear that SEPs are an effective strategy for HIV prevention.

A compelling reason for the broader implementation of SEPs is the recent increase in abuse of prescription opioids, particularly in suburban and rural areas.

These stories are seen both in the popular media49,50 as well as the scientific literature.

A 2012 study of 16-25 year old injectors found that initiation into prescription opioid misuse preceded the use of other illicit drugs such as heroin, and most surveyed injected their drugs.51 Given recent law enforcement crackdowns on prescription drug misuse, the transition from prescription opiates to cheaper, more easily accessible illicit drugs is inevitable. A recent Substance Abuse and Mental Health Services Administration (SAMHSA) report found that the number of people ages 12 and older who reported using heroin in the past year rose from 373,000 in 2007 to 681,000 in 2013, an 83% increase.52 While the report’s authors cannot verify that heroin use was a direct result of diversion from prescription opiate misuse, they cite information supporting the idea that individuals abusing pain relievers will switch to heroin due to decreased access to prescription drugs and lower relative cost.53,54 Which brings us back to Indiana.

Acting on the Executive Order 15-05 issued by Governor Mike Pence, State Health Department officials were able to act quickly to establish a SEP in Scott County in less than 2 months since the initial news of the outbreak,55 overriding existing legislation declaring such programs to be illegal in the state.56 Through this Executive Order, Governor Pence showed that he could suspend his own views about needle exchange (he has previously voiced opposition to SEPs), focus on the research evidence supporting this intervention, and respond quickly to the public health need that mandated it. Further, by passing a measure Fall 2015 Volume 15, Issue 1

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that extends the legalization of SEPs for a year and expands services to any jurisdiction in the state that can prove an IDU-associated outbreak,57 the State Legislature is getting ahead of this outbreak rather than running after it. Such leadership needs to be noted and commended.

Larger scale SEP implementation mandates the removal of the Federal Ban. Even with no financial investment, the lifting of the Federal Ban would allow states to use federal monies to support HIV prevention services – including SEPs -that are most needed by communities. The potential benefit is increased with financial investment: a $10-$50 million increase in SEP funding would avert an estimated 194816 HIV infections, with the cost savings per infection averted ranging from $51,601$61,302,58 a high return on investment.

From Indiana, it is clear that the syndemic of drug addiction and HIV infection is real.

If we are to combat these epidemics, we must put aside the personal and political biases that prevent the use of scientific evidence for public health benefit. The evidence on SEP effectiveness is clear and abundant. The public health need is evident and increasing.

What are we waiting for?

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Indiana State Department of Health. HIV Outbreak in Southeastern Indiana (main page). Available at: http://www.in.gov/ isdh/26649.htm. Accessed July 27, 2015.

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Centers for Disease Control and Prevention (CDC). HIV Surveillance in Injection Drug Users (through 2011). Slide set available through the Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, Sexual Transmitted Diseases, and Tuberculosis Prevention website: www. cdc.gov/hiv/library/slideSets/index.html.

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Des Jarlais DC, McKnight C, Goldblatt C, Purchase D. Doing harm reduction better: Syringe exchange in the United States. Addiction 2009; 104, 1441-1446.

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Available at: http://www.cdc.gov/idu/facts/ aed_idu_syr.pdf. amfAR, The Foundation for AIDS Research (amfAR). Syringe exchange program coverage in the United States, June 2014.

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Hall HI, Song R, Rhodes P, et al. HIV Incidence Surveillance Group Estimation of HIV Incidence in the United States. JAMA 2008; 300: 520-9.

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Parts M. Disease prevention as drug policy: a historical perspective in the case for legal access to sterile syringes as a means of reducing drug-related harm. Fordham Urban Law Journal 1997; 475-532.

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Green TC, Martin EG, Bowman SE, Mann MR, Beletsky L. Life after the ban:

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an assessment of US syringe exchange programs’ attitudes about and early experiences with federal funding. Am J Public Health 2012; 102 (5): e9-16. doi: 10.2105/ AJPH.2011.300595. Epub 2012 Mar 15.

The White House Office of HIV/AIDS Policy. “Dear Colleague Letter” regarding reinstatement of the ban on the use of federal funding for syringe access services.

Letter dated March 29, 2012.

The White House. National HIV/AIDS Strategy. Available at: http://www.whitehouse.gov/sites/default/files/uploads/ NHAS.pdf Sommer A. How Public Health Policy Is Created: Scientific Process and Political Reality. Am J Epidemiol 2001; 154(12): S4-S6.

Meier KJ. The politics of sin: Drugs, alcohol, and public policy. Armonk, NY: ME Sharpe, 1994.

Bowen EA. Clean needles and bad blood: needle exchange as morality policy. Journal of Sociology & Social Welfare 2012; 39(2): 121-141.

Tempalski B, Friedman R, Keem M, Cooper H, Friedman SR. NIMBY localism and national inequitable exclusion alliances: The case of syringe exchange programs in the United States. Geoforum 2007; 38(6): 1250–1263.

Allen ST, Ruiz MS, O’Rourke A. The evidence does not speak for itself: The role of research evidence in shaping policy change for the implementation of publicly funded syringe exchange programs in three US cities.

International Journal of Drug Policy 2015.

Prepublication copy available at http://dx. doi.org/10.1016/j.drugpo.2015.04.008 Hall HI, Song R, Rhodes P, et al. HIV Incidence Surveillance Group Estimation of HIV Incidence in the United States. JAMA 2008; 300: 520-9.

Kerr T, Small W, Buchner C, Zhang R, Li K, Montaner J, Wood E. Syringe sharing and HIV incidence among injection drug users and increased access to sterile syringes. Am J Public Health 2010; 100(8): 1449-1453.

Ksobiech K. A meta-analysis of needle sharing, lending, and borrowing behaviors of needle exchange program attenders. AIDS Educ Prev 2003; 15: 257–68.

Hurley SF, Jolley DJ, Kaldor JM. Effectiveness of needle exchange programmes for prevention of HIV infection. Lancet 1997; 21(9068): 1797-1800.

Palmateer N, Kimber J, Hickman M, Hutchinson S, Rhodes T, Goldberg D. Evidence for the effectiveness of sterile injecting equipment provision in preventing hepatitis C and human immunodeficiency virus transmission among injecting drug users: a review of reviews. Addiction 2010; 105: 844–59.

Tilson H, Aramrattana A, Bozzette S. Preventing HIV infection among injecting drug users in high-risk countries: an assessment of the evidence. Washington, DC: Institute of Medicine, 2007.

Wodak A, Cooney A. Do needle syringe programs reduce HIV infection among injecting drug users: a comprehensive review of the international evidence. Substance Use Misuse 2006; 41: 777-816.

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Kaplan E, Heimer R. HIV prevalence among intravenous drug users: model-based estimates from New Haven’s legal needle exchange. J Acquir Immune Defic Syndr 1992; 5: 163-9.

Des Jarlais DC, Marmor M, Paone D, Titus S, Shi Q, Perlis T, et al. HIV incidence among injecting drug users in New York City syringe-exchange programmes. Lancet 1996; 348: 987-991.

Ruiz MS, O’Rourke A, Allen ST. Impact evaluation of a policy intervention for HIV prevention in Washington, DC. In press, AIDS and Behavior, 2015. DOI :10.1007/ s10461-015-1143-6.

Lurie P, Drucker E. An opportunity lost: HIV infections associated with lack of a national needle-exchange programme in the USA. Lancet 1997; 349(9052): 604-8.

Lurie P, Gorsky R, Jones TS, Shomphe L. An economic analysis of needle exchange and pharmacy-based programs to increase sterile syringe availability for injection drug users. J Acquir Immune Defic Syndr Hum Retrovirol 1998;18 Suppl 1:S126-32.

Holtgrave DR, Pinkerton SD, Jones TS, Lurie P, Vlahov D. Cost and cost effectiveness of increasing access to sterile syringes and needles as an HIV prevention intervention in the United States. J Acquir Immune Defic Syndr Hum Retrovirol 1998; 18 (Suppl 1): S133-138.

Laufner FN. Cost-effectiveness of syringe exchange as an HIV prevention strategy. J Acquir Immune Defic Syndr 2001; 28(3): 273-278. PMID: 11694836 Lurie P, Drucker E. An opportunity lost: HIV infections associated with lack of a national needle-exchange programme in the USA. Lancet 1997; 349(9052): 604-8.

DollarTimes.com. Inflation calculator.

Available at: www.dollartimes.com/calculators/inflation.htm. Accessed: July 30, 2015.

Centers for Disease Control and Prevention. HIV Cost-effectiveness. Page updated April 16, 2013. Available at: www.cdc.gov/ hiv/prevention/ongoing/costeffectiveness/ index.html. Accessed on July 9, 2014.

Ruiz MS, O’Rourke A, Allen ST. Impact evaluation of a policy intervention for HIV prevention in Washington, DC. In press, AIDS and Behavior, 2015. DOI :10.1007/ s10461-015-1143-6.

McCoppin R. White suburbanites going from pain pills to heroin. Chicago Tribune, September 26, 2011. Available at: http:// articles.chicagotribune.com/2011-09-26/ news/ct-met-drug-deaths-20110926_1_drugdeaths-prescription-drugs-heroin-deaths.

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Ly S. More people hooked on heroin.

MyFoxDC.com, Aug 08, 2013. Available at: http://www.myfoxdc.com/story/23088579/ more-people-hooked-on-heroin#axzz2u7LMywMr. Accessed last on July 30, 2015.

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Lipari RN, Hughes A. The NSDUH Report: Trends in Heroin Use in the United States: 2002 to 2013. (2015). Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality. Rockville, MD. Available at: http://www.samhsa.gov/data/sites/default/ files/report_1943/ShortReport-1943.pdf.

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Dooley DP. Boston patterns and trends in drug abuse: 2013. Proceedings of the Community Epidemiology Work Group, June 2014. Retrieved from: http://www.drugabuse.gov/sites/default/files/boston2014. pdf Cicero TJ, Ellis MS, Surratt HL, Kurtz SP. The changing face of heroin use in the United States: a retrospective analysis of the past 50 years. JAMA Psychiatry 2014; 71: 821–6.

Indiana State Department of Health. Needle Exchange for Scott County Only Now in Effect. Press release dated April 4, 2015.

Available at: http://www.in.gov/isdh/26649. htm. Accessed July 27, 2015.

No author given. Indiana governor overrides law to authorize needle exchange.

Chicago Tribune, March 26, 2015. Available at: http://www.chicagotribune.com/news/ local/breaking/chi-indiana-needle-exchangehiv-20150326-story.html. Accessed on July 30, 2015.

Associated Press. Indiana lawmakers pass bill allowing needle-exchange programs to combat HIV outbreak. FoxNews.com, April 30, 2015. Available at: www.foxnews. com/politics/2015/04/30/indiana-lawmakers-pass-bill-allowing-needle-exchange-program-to-combat-hiv/. Accessed on July 30, 2015.

Nguyen TQ, Weir BW, Des Jarlais DC, Pinkerton SD, Holtgrave DR. Syringe Exchange in the United States: A National Level Economic Evaluation of Hypothetical Increases in Investment. AIDS and Behavior 2014; 18(11): 2144-2155.

Dr. Monica S. Ruiz Monica S. Ruiz, PhD, MPH, is an Assistant Research Professor at the Milken Institute School of Public Health at The George Washington University. She is the PI of a NIDA-supported R01 examining the epidemic impact of policy change as a structural intervention for HIV prevention in Washington, DC.

Dr. Sean T. Allen Sean T. Allen PhD, is a Post-Doctoral Research Fellow in the Drug Dependence Epidemiology Training Program at Johns Hopkins University in Baltimore, MD. His areas of research include identifying antecedents of overdose, understanding the risk environments of marginalized populations, and evaluating the effects of policies that restrict syringe services programs.

Allison O’Rourke Allison O’Rourke MPH, is a Senior Researcher at Synectics for Management Decisions Inc. in Arlington, VA. She has worked in data management and statistics for over 10 years striving to better understand substance using populations and advocate for treatment and policies that are supported by research.

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HEALTH HIGHLIGHTS

The Fallacy of U.S. and China Hospital Collaborations – Are we able to bridge ideals with realities?

Garry Choy, MD, MBA, Julianne Ip, MD, and Dicken S. C. Ko, MD China is the fastest growing consumer market in the world with the healthcare market being one of the largest segments in its economy. With declining reimbursements and increasing regulatory complexity in the United States, there has been an increasing interest in “exporting healthcare” and investment in the Chinese healthcare market. Multiple factors include representation of the branding of the healthcare organizations seeking to venture into China, availability of high cost drugs, healthcare informatics issues including primary language, human capital requirements and staffing requirements. This article focuses on the potential pitfalls and risks of venturing into the Chinese healthcare landscape by western healthcare corporations and organizations.

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hina is the fastest growing consumer market in the world with a burgeoning population that is hungry for increasing goods and services. With declining reimbursements and increasing regulatory complexity, why not export healthcare from the USA along with CocaCola overseas to the largest customer base in the world?

Western medicine has, in fact, been in China since the 17th century when Jesuit missionaries brought remedies into China to add to the herbalist approaches of Traditional Chinese Medicine (TCM).

However, as the geopolitical climate changed with conflicts and national unrest, the landscape in China for healthcare followed a parallel track. Ideologies of TCM conflicted with scientific discoveries of the West, leading to difficulties in handling outbreaks of epidemics in infectious diseases related to early industrialization.1 Once the People’s Republic of China was founded in 1949, China tried to incorporate both a successful integration of TCM and Western Medicine.

At present, economic and cultural clichés call for another round of collaboration between East and West. In 2011, the Chinese government took healthcare in China off the restricted list of for foreign investors, encouraging outside entities to lay claim to reforming medical care in China.

With western medical practices becoming more regulated, consumer driven and legally complicated, catering to a nation of growing purchasing power with emerging first world healthcare needs is enticing. China’s healthcare market, expanding faster than the overall Chinese national economic growth – a market size of $1.2 trillion USD by 2020

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- is a sure bet if there ever was one.

Indeed many organizations are making the bet: Healthcare America, TPG Capital, Fosun Group, and Chindex are all operating or plan to operate private hospitals in China with collaborators from the USA - “Designed in the USA, Made in China.”2 However, there are potential pitfalls that one needs to consider in this emerging trend of US-China relations in the world of healthcare.

Complexity of Cultural Differences The actual culture of healing in China is different. A hernia repair that is an outpatient procedure in westernized countries may take weeks of convalescence in a Chinese hospital. When one member of a Chinese family is sick, the patient becomes the center of the family’s dynamics. Many Chinese family members even move into the patient’s room to take on the role of the caretaker along with the nurses and doctors. End-oflife care is quite different based on family dynamics and paternalistic approaches to life and healthcare. Can Western collaborators adapt and begin to understand in order to deliver culturally sensitive as well as appropriate healthcare services?

Prerequisite Branding

for

Hong Kong-Shenzhen Hospital (UHKSH) was the first public medical institution managed completely by an “outside” entity.

Media in Guangdong has revealed that ~$570 million USD was allocated for the building and infrastructure of the hospital.

The incentive for Hong Kong University was to provide staffing of administrators and doctors. However, ultimately, the staff hired was made up of locals who were not representative of the first tier Hong Kong doctors, but rather junior faculties.

Furthermore, the large sign adorning the hospital’s front entrance that leads off with the “University of Hong Kong…” suggests a new foreign entity.3 However, the culture and services provided are still distinctly Chinese and not primarily representative of Hong Kong. Repeating such mistakes by having minimalistic top tier personnel while selling out the brand can be catastrophic. As Western healthcare organizations step into China, one needs to recognize that the local consumers are quick to judge and see beyond the Western branding.4

Availability and Costs of USAApproved Drugs and Devices in China High-quality practice standards and evidence-based medicine are the foundations of a Western medical platform, as we rely on multi-detector CT scanners, wireless pacemakers, cutting-edge pharmaceutical agents, and countless other technologies.

Despite the fact that China now has the second largest number of millionaires in the world with an emerging middle class, the average annual income per capita was the equivalent of $10,220 compared to $84,300 in the United States.5 Economics 101 dictates that the cost-curve needs to bend significantly for a reliable margin in any healthcare venture in China. Furthermore, Western entities must negotiate with local regulatory agencies and develop sound relationships with the Chinese government.

Healthcare Informatics in Chinese or China: Authentic English?

While other industries may think this a paradox, we should not be inadvertently and especially not intentionally selling a knockoff product to the local market. One might consider the case of a failed 2500 bed public hospital in Shenzhen in 2012. Backed

by China’s Ministry of Health, University of

The Western medical culture dictates, “it did not happen unless it is documented.”

The EMR has to be the common platform from which clinicians facilitate collaboration and ultimately provide proper clinical care of patients. Even the simplest data entry into the EMR for health information exchange may need a common language, likely English.

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Dr. Garry Choy

Rose Symotiuk Patients receive treatment in an IV room in Shanghai, China.

A Chinese character keyboard is not the same as typing on a QWERTY standard.

Multilingual electronic medical records is also a novel consideration which has not yet reached widespread adoption or demand in the healthcare marketplace.6

Human Capital and Staffing Clearly to run an establishment and integrate itself into China, it is necessary to hire a Chinese workforce. However, will the local workforce have the abilities to match the standards and competencies set by “Western” expectations? Simply put, are the nurses, pharmacists, and doctors trained, examined, and accredited to the same level of “standards” as those established in Western countries? The interactions of management with employees may carry a different level of expectations and understanding. Regulation concerning operating a hospital may differ dramatically in the U.S. compared to China.

How will managerial oversight be managed from in China when the management may be located in the United States or elsewhere?

Viewpoint and Conclusion Collaboration and business opportunities within China is a new frontier that makes cultural, intellectual, and financial sense.

China makes no false pretense that she can gain faster with the added knowledge of Western medical care through collaborations with Western healthcare organizations from the United States. Westerners make no false assumptions that we are not doing this as a purely quintessential charity. Clearly, the numbers of companies and institutions that jumped into the fray have done due diligence with detailed economic analysis, consulting advisors, and leveraging political ties to ensure success calculable to the most granular components. Understanding and knowing your adversaries is the first step

for success in any relationship to minimize risk. Fundamentally, immersion of a foreign culture, concept, or financial calculation into a different society will require adaptation.

The overall strategy must first be answered by a self-introspection – “Are the US/ Western organizations all in?” To overcome the barriers of culture, branding, costs, informatics, and staffing, the entrepreneurial institution must bear the cost of ensuring all these addressed properly with a view for quick evolutions.

A hands-off approach to management from afar is a recipe for a rapid collapse and disastrous end results. This investment is long-term and will require an infusion of financial as well as human capital. The Designed in the U.S.A., Made in China theme has been overwhelmingly successful in other models, but does that mean it is readily applicable to the healthcare industry?

References: 1. Hong FF. History of Medicine in China – When Medicine Took an Alternative Path.

McGill J of Med, 2004 8:79-84.

2. Fischl J et al. Privatization of Healthcare in the Yangtze River Delta Reion II. US Commercial Services, USA Department of Commerce.

2014 Jun:1-22.

3. Chen F. HKU Caught on Wrong Foot in Shenzhen Hospital Venture. Ejinsight. 2014 Aug. 4. Nip A. HKU Won’t Drop Pricey Mainland Chinese Hospital even after HK$200M Bill.

South China Morning Post. 2014 July.

5. Weagley R. One Big Difference Between Chinese and American Households: Debt.

Forbes. 24 June, 2010.

6. Coorevits P1, Sundgren M, Klein GO, Bahr A, Claerhout B, Daniel C, Dugas M, Dupont D, Schmidt A, Singleton P, De Moor G, Kalra D. Electronic health records: new opportunities for clinical research. J Intern Med. 2013 Dec;274(6):547-60.

Garry Choy, MD MBA is a physician at Massachusetts General Hospital and on faculty at Harvard Medical School, focused on healthcare innovation through informatics. Dr. Choy is Cofounder of CredSimple, a platform that digitizes and automates the currently labor-intensive and manual processes of medical credentialing. Dr. Choy is also an Assistant Chief Medical Information Officer for Advanced Technologies at Massachusetts General Physicians Organization at MGH. Additional interests include applying technology and quality improvement strategies in telemedicine and global health including a significant focus on healthcare delivery in China.

Dr. Julianne Ip Julianne Ip, MD serves at Brown University in both the Alpert Medical School and the eight-year baccalaureate-MD Program in Liberal Medical Education(PLME) as Associate Dean of Medicine, Clinical Associate Professor of Family Medicine and Associate Professor of Medical Science. She directs and participates in the advising of PLME undergraduate students; reviews the PLME curriculum and teaches in the PLME while also overseeing Alpert Medical School/PLME visiting international student exchanges and opportunities.

Dr. Dicken Ko Dicken Ko, MD Dr. Dicken S. C. Ko, BSc, MD, FRCSC, FACS is a surgeon focused on surgical innovations, healthcare delivery and management, and global medical education. Dr. Ko is currently an active attending staff urologic and multi-organ transplant surgeon at the Massachusetts General Hospital (MGH), Harvard Medical School. He is a Canadian trained surgeon who has now been on the faculty at MGH for 20 years. Dr. Ko is an international leader in his field with experiences as Surgical Director of Renal Transplantation at MGH as well as Director of MGH Urology Regional Program. He was 28th President of the Urologic Society for Transplantation and Renal Surgery in 2012. Dr. Ko has lectured extensively internationally and is also an Adjunct Professor of Surgery at the Dr. Sun Yat-Sen University in Guangzhou, China.

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Photo credit: NPR HEALTH HIGHLIGHTS

Simulating the Impact of an Urban Farm Tax Credit Policy in a Low Income Urban Setting Joel Gittelsohn, PhD; Yeeli Mui, MPH; Sen Lin, MS; Bruce Y Lee, MD, MBA; Andrew Seiden, MPH; Arielle Gorstein, MPH; Pete Welchb; Sara Bleich, PhD; Takeru Igusa, PhD Urban farm tax credits, which incentivize the conversion of vacant lots into community farms, are increasingly being adopted as a means of improving low income urban food environments. At the request of members of the Baltimore City Council, we modified an existing agent-based model of the Baltimore city low income food environment to predict potential impact of the policy on numbers of privately owned vacant lots, fresh produce availability and consumption. The model predicted significant increases in fresh produce availability and consumption in low income areas of the city and was presented to the city council, who passed the legislation.

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reative, cost-effective solutions are greatly needed to address the epidemic of obesity and diet-related chronic diseases, both nationally and in low income urban settings in particular. Low income urban communities frequently have minimal access to a range of affordable healthy foods.1 Studies have shown that these food source poor environments are associated with poorer diets and greater rates of obesity.2,3 Policy solutions, such as providing tax incentives to reallocate land for food production may be a viable approach.

Urban Food Environment The urban food environment is complex. Many competing food sources commonly exist in these settings, including supermarkets, corner stores, carryout restaurants, fast food restaurants, dollar stores, pharmacies and more. Yet in low income settings, there is commonly a lack of access to fresh fruits and vegetables (FV). In addition to these limitations in access, many community residents are unfamiliar with the proper and safe handling and preparation of FV.4 Therefore, consumer demand can be a barrier to FV consumption as well as local

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supply.

There is now substantial literature on the impact of programs to improve healthy food access in retail food sources.5,6 Much of this work is promising, but questions remain regarding sustainability, and to finding viable, long-term sources of fresh produce.

Urban Farm Tax Credits Urban farms represent a potential solution to these problems. In recent years, municipalities across the country have become interested in investing in urban agriculture, which can be broadly defined as “growing and raising food crops and animals in an urban setting for the purpose of feeding local populations.�7 This interest is born out of a variety of goals, including sustainability, development of local food sources, community development, creation of jobs, improving access to healthy foods in food deserts, and providing education about food and nutrition, all of which can be addressed in some way with urban agriculture. Municipalities have made use of three main strategies to encourage urban agriculture: zoning policy, food policy, and incentives through either funding or the

provision of land.8 One way that municipalities have used monetary incentives to encourage the development of urban agriculture is through property tax breaks to people who use their land for agricultural purposes. Provisions of these policies differ from place to place, including the allowable size of plots of land, the amounts of tax credits, the length of time people are allowed to receive the tax credits, and specific rules for how the land can be used. There are also variations in what can be done by state in terms of taxation policies. In most cases, the state must enact legislation that authorizes cities or counties to provide the tax breaks.

One of the first states to pass a law allowing for tax incentives for urban agriculture was California (Urban Agriculture Incentive Zones Act of 2013). San Francisco became the first city to take advantage of this law the following July by passing an ordinance allowing residents to apply for permits9 that would allow their property to be assessed as irrigated farmland as opposed to commercial property, which carries an extremely high tax burden in San Francisco.10 Under this policy, tax credit recipients must keep the farm active for at least five years, and in order to provide a community benefit, must sell or donate their products to local residents.11 However, the city received just two applications for these permits during its first application cycle at the end of 2014, and granted one.12 The latest city to implement Urban Agriculture Zones in California was Sacramento, which passed its Urban Farm Ordinance on March 24, 2015.13 In 2013, Missouri passed its Urban

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Agriculture Act, which allowed municipalities to set up urban agriculture zones on blighted areas. Under this law, people who use their land for “growing produce or other agricultural products, raising or processing livestock or poultry, and operating markets that derive at least 75 percent of their sales from locally grown or raised food” can enjoy up to 25 years of property tax abatement.

Similar plans are underway in Kansas City.14 The District of Columbia passed its Urban Farming and Food Security Act of 2014. This law, which went into effect in April 2015, “establishes a 90% tax abatement for private landowners who use, lease, or allow their land to be used for urban agriculture; instructs the Mayor to identify 25 Districtowned vacant lots for urban farming; creates a tax credit for individuals and businesses to donate locally farmed fruits and vegetables to D.C. food banks, pantries, and shelters; and provides that tax-exempt entities will not lose their tax-exempt status if grounds are used for urban farming or community gardens.”15 Simulation Modeling for Policy Despite the recent growing interest in urban farm tax credits, the actual impact and potential unintended consequences of such policies is almost completely unknown. It is possible that such initiatives might lead to minor or irrelevant changes to the diet.

Widespread use of such policies could lead to reduced tax revenues.

Within the safety of a virtual environment, simulation modeling can be used to address questions related to complex food systems and the potential impact of introducing new policies. In particular, agent-based models (ABMs) provide a platform to examine emergent properties (i.e., changes in dietary patterns or obesity trends) as a result of individual-level autonomous and adaptive behaviors that respond to environmental changes (i.e., introduction of an urban farm).

The dynamic and visual nature of ABMs is also an important feature that allows researchers and policymakers to together analyze various scenarios and outcomes related to the program or policy of interest before proceeding with implementation.16,17 In this paper, we present a case example of how simulation modeling was used to provide evidence and guide decision-making of policymakers, in regards to the adoption of an urban farm tax credit in Baltimore City.

Planning the Model The work presented here was documented

through three complementary information sources: minutes of the overall policy working group, minutes of the Baltimore Low Income Food Environment (BLIFE) model development working group, and through a series of in-depth interviews conducted with ten key stakeholders who provided evidence that helped to shape the model, and who provided a narrative stream that helped guide the development of the story of the urban farm tax credit development and its initiation. Informants included Baltimore City Council members, chiefs of staff for City Council members, project managers at the Baltimore City Health Department, Baltimore City Public Schools, and Baltimore City Department of Recreation and Parks. Snowball sampling was used to recruit new stakeholders, based on recommendations from earlier interviewees.

Setting: Baltimore City Similar to many urban cities across the United States, healthy food options are limited in many of Baltimore’s lowincome neighborhoods. Residents have far greater access to convenience stores, corner stores, fast food restaurants, and carry-out restaurants that are known to provide energydense, low-nutrient options.18,19 A recent study on food and nutrient intake among low-income urban adolescents in Baltimore found that mean daily energy intake levels exceeded recommended levels, and the most frequently reported foods included sugar-sweetened beverages, chips, candy, and milk. Furthermore, adolescents typically fail to meet adequate levels in a number of vitamins and dietary fiber.20 Consumption of fresh fruits and vegetables is rare, and well below national standards.

BLIFE agent-based model For the past two years, our study team has been developing and implementing a multi-level child obesity prevention program, called B’More Healthy Communities for Kids (BHCK).21As part of this trial, we formed a Policy Working Group, which enjoys participation from members of the Baltimore City Council, Department of Health, Recreation and Parks, and other citybased agencies and organizations. One of the key mechanisms for interaction within the Policy Working Group, has been through the development of an ABM of the food environment in low income areas of the city. BLIFE was developed on NetLogo, chosen as the simulation platform for its fast-prototyping capabilities (Lee et al, under review). NetLogo provides a low-threshold

graphical interface and programming tools to define agents, to analyze simulations, and to visualize results.

The BLIFE model depicts the postschool food foraging and physical activity behaviors of low income adolescent children. Child agent information includes age, gender, initial weight, initial height and food preference parameters, and behavioral rules such as selection of food sources, foods within source, and deciding whether or not to do exercise. The BLIFE model contains a map of a segment of the low income area of Baltimore (roughly 10% of the city is depicted), with each food source geolocated and specified with properties such as type (e.g., corner store, carryout, school, recreation center, etc.), HFAI (Healthy Food Availability Index) for corner stores, and store-owner training level. In each iteration (each simulated day or other duration), energy intake and expenditure are calculated, which then impact the weight of all children. The model follows the behaviors of children in the dynamically changing environment and simulates impact over the 5-year period. A detailed description of the model is available in Lee et al (under review).

From its inception in June 2013, the BLIFE model has been revised and refined in response to suggestions and comments from Policy Working Group members.

BLIFE simulated experiments for urban agriculture tax credit In August 2014, a Baltimore City Councilman met with leadership of the Policy Working Group, and requested that the BLIFE model be utilized to develop a simulated experiment of the potential

Joel Gittelsohn Joel Gittelsohn, PhD, is a Professor in the Global Obesity Prevention Center, International Health, Johns Hopkins Bloomberg School of Public Health. He develops, implements and evaluates community-based programs for the primary prevention of chronic disease in disadvantaged ethnic minority populations. His programs have shown success in increasing knowledge, healthy food purchasing and consumption of healthy foods and reducing obesity, and in improving stocking and sales in food sources.

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impact of an urban farm tax credit policy in Baltimore City. The modeling team (SL, TI, JG, YM) began planning the modifications with the assistance of members of the Baltimore City Office of Planning, which had specific knowledge of the number and types of vacant lots, challenges in conversion, etc. These discussions identified multiple challenges for the model, including: 1. How to model vacant lots? Vacant lots are areas that are not currently utilized but may be converted to urban farms. For the modified BLIFE model, each vacant lot is modeled as a fixed location on the Baltimore map, with properties such as latitude, longitude, area. Vacant lots in Baltimore fall into two categories: those that are privately owned (n=52) and those that are owned by the city (n=25). The tax credit applies only to privately owned property.

2. Rate of conversion of vacant lots to urban farms? Urban farms require a substantial amount of investment and management skill to be economically viable.

Based on our informant interviews, we were not able to derive a single agreed-upon rate of conversion should the tax credit pass (i.e., % of owners of vacant lots who would have their lots converted to urban farms/ year). Some respondents were extremely conservative and viewed this rate as just 1-2% of lots, and others felt the number would be higher. We used these responses to identify some reasonable bounds, and used those bounds to run simulations using the model.

3. What is the impact of urban farms on child agents in the model over a 5-year period? Urban farms increase the supply of healthy food in their surrounding region.

Our model assumed that local corner stores and carryouts would be used in some small way as a source for reselling that produce.

This is modeled in the BLIFE model by increasing the HFAI in these food sources that are within a set radius of each urban farm.

How Model Information Was Used to Support the Urban Farm’s Tax Credit As there was a range of estimates of the vacant lot to urban farm annual conversion rate, we ran several scenarios: 1) no conversion (0%); 2) minimal conversion (2%); and 3) moderate conversion (4%), annually.

The model indicates that with no urban farm tax credit, none of the existing vacant lots will be converted to urban farms over a five year period. The variety of FV available

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at small stores would remain the same, and the servings of FV consumed by children would also not increase.

With passage of the tax credit, and assuming a very conservative 2% conversion rate per year: we predict a decrease the number of vacant lots by 10% (from 30 to 27) after five years, and an increase in the number of urban farms by 60% (from 5 to 8). These changes would be associated with an increase in the availability of fresh fruits and vegetables in corner stores and carryouts by 49.1% (from 0.57 to 0.85 varieties), and an increase the consumption of fresh fruits and vegetables by children by 36.9% (from 0.65 to 0.89 servings).

Assuming a more moderate 4% conversion rate per year: we predict a decrease the number of vacant lots by 20% (from 30 to 24), and a consequent increase in the number of urban farms by 120% (from 5 to 11). These changes would be associated with an increase in the availability of fresh fruits and vegetables in corner stores and carryouts by 105% (from 0.57 to 1.17 varieties), and an increase in the consumption of fresh fruits and vegetables by children by 86.2% (from 0.65 to 1.21 servings).

The modeling team met with the City Councilman to present the results to him, and to provide various supporting materials, including a policy brief that provided a summary of the results of the simulation, and a video that presented the same information in more detail in a visually appealing manner.

In October 2014, by invitation of the Councilman, the lead author testified as to the findings of the modified BLIFE model, and presented the policy brief and video.

On May 11, 2015, the Baltimore City Council passed legislation to implement the urban farm tax credit law. The ability to pass such a law comes from Maryland’s “Property Tax Credit – Urban Agricultural Property”

law, which went into effect in April 2014 and allows counties and Baltimore City to give up to 100% tax abatements to owners of land that is used for “agricultural purposes,”22 Baltimore’s law will relieve property owners of 90% of their property tax bills for periods of five years at a time, for up to ten years, if they sell at least $5,000 of fruits and vegetables per year.23 Shortly thereafter, the Mayor signed the bill into law.

Discussion To our knowledge, this is the first reported use of an ABM to engage and work with policymakers for the purpose of changing the food environment. The model findings were well-received by the Baltimore City Council, and may have contributed to the eventual passing of the legislation.

Many challenges were faced in the conduct of this work. At the time of the presentation to the City Council, the potential tax revenue decline associated with passage of the bill was raised as a concern. Future versions of such models should try and incorporate a financial dimension, so that decision makers can best weigh the cost-benefits of such policies.

The literature is weak in terms of describing the impact of an urban farm on healthy food access and dietary behaviors.

Very limited information (and quite inconclusive) indicates the positive effects of community farmers markets.24,25 Our assumptions regarding proximity and actual intake are based on these limited previous studies.

A great challenge was predicting the number of lots that would be converted into urban farms on an annual basis. However, consultation with local stakeholders informed reasonable bounds of conversion rates which could be tested using the ABM. As the urban farm tax credit policy is implemented

Table 1. Simulated Impact of Baltimore’s Urban Farm Tax Credit in Selected Food Desert Areas over Five Years

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over the following years and data is collected, a more accurate measure of the conversation rate could be simulated in the model. Future work should also include sensitivity analyses by varying other parameters beyond the conversion rate of vacant lots to evaluate the impact of changing these additional parameters on access and dietary behaviors.

For future versions of the model, we plan to incorporate an economic sub-model, whereby each vacant lot owner becomes an agent who calculates the cost-benefit ratio of converting their vacant lot into a farm.

In this iteration of the model, potential social benefits of creating an urban farm were not considered. Future work could also evaluate the impact of greater access to urban farms on decreasing neighborhood crime as vacant lots are replaced by green space as well as on improving social cohesion among community members as residents interact with one another over gardening activities and a shared community space.

In terms of model development, there are limitations related to model assumptions and inherent simplification of reality. We assumed that vacant lot conversion rates remained the same over the 5-year period and that increased access to fresh fruits and vegetables in corner stores and carryout restaurants would be affected uniformly.

For future work, a readiness score could be assigned to each corner store and carryout restaurant that accounts for stores’ likelihood of stocking fresh produce and demand for fruits and vegetables among residents in the neighboring area.

In conclusion, conversion of vacant lots to urban farms in this setting may increase access to and consumption of fresh fruit and vegetables. Future research is needed to better understand the impact of urban farms of fresh food access and dietary behaviors.

Simulation modeling can be an effective tool for examining and supporting different policies and programs for obesity and chronic disease control by further bridging the gap between research and practice.

1. Galvez, Maida P, Kimberly Morland, Cherita Raines, Jessica Kobil, Jodi Siskind, James Godbold, and Barbara Brenner. 2008. “Race and Food Store Availability in an Inner-City Neighbourhood.” Public Health Nutrition 11 (6): 624–31. doi:10.1017/ S1368980007001097.

2. Morland, Kimberly B, and Kelly R Evenson.

2009. “Obesity Prevalence and the Local Food Environment.” Health & Place 15 (2): 491–95. doi:10.1016/j.healthplace.2008.09.004.

3. Morland, Kimberly, Ana V. Diez Roux, and Steve Wing. 2006. “Supermarkets, Other Food Stores, and Obesity.” American Journal of Preventive Medicine 30 (4): 333–39. doi:10.1016/j.amepre.2005.11.003.

4. Wolfson, Julia A, and Sara N Bleich. 2015. “Fruit and Vegetable Consumption and Food Values: National Patterns in the United States by Supplemental Nutrition Assistance Program Eligibility and Cooking Frequency.” Preventive Medicine 76 (April): 1–7. doi:10.1016/j.ypmed.2015.03.019.

5. Gittelsohn, Joel, Megan Rowan, and Preety Gadhoke. 2012. “Interventions in Small Food Stores to Change the Food Environment, Improve Diet, and Reduce Risk of Chronic Disease.” Preventing Chronic Disease 9 (January): E59. http:// www.pubmedcentral.nih.gov/articlerender. fcgi?artid=3359101&tool=pmcentrez&render type=abstract.

6. Escaron, Anne L, Amy M Meinen, Susan A Nitzke, and Ana P Martinez-Donate. 2013. “Supermarket and Grocery Store-Based Interventions to Promote Healthful Food Choices and Eating Practices: A Systematic Review.” Preventing Chronic Disease 10 (January): E50. doi:10.5888/pcd10.120156.

7. Goldstein, M., Bellis, J., Morse, S., Myers, A., & Ura, E. 2011. “Urban agriculture: A sixteen city survey of urban agriculture practices across the country.” Survey written and compiled by Turner Environmental Law Clinic at Emory University Law School, Atlanta, GA 1-94.

8. Mukherji, Nina, and Alfonso Morales. 2010. “Zoning for urban agriculture.” Zoning Practice 26 (3): 1-8.

9. Zigas, Eli. 2014. SF Approves California’s First Tax Incentive for Urban Ag [Web log post]. Retrieved from http://www.spur.org/blog/2014-08-05/sfapproves-california-s-first-tax-incentive-urban-ag.

10. Blackmore, W. 2014. This New Law Could Make Landowners and Urban Farmers Best Friends.

TakePart. Retrieved from http://www.takepart.com/ article/2014/08/13/sf-urban-ag-tax-incentives 11. EfficientGov (2014, Sept. 30). Tax Credits for Urban Farmers. Retrieved from http://efficientgov.com/ blog/2014/09/30/tax-credits-urban-farmers/.

12. Sabatini, J. 2015. Tax Break Sowing the Seeds of Urban Agriculture Growth. The Examiner. Retrieved from http://www.sfexaminer.com/sanfrancisco/ tax-break-sowing-the-seeds-of-urban-agriculturegrowth/Content?oid=2915813.

13. Urban Agriculture Ordinance. 2015. Retrieved from http://portal.cityofsacramento.org/CommunityDevelopment/Planning/Long-Range/UrbanAgriculture 14. Roberts, Rob. (2014, May 1). Farm Subsidies go Local: Council Expected to OK Urban Ag Incentives. Kansas City Business Journal. Retrieved from http://www.bizjournals.com/kansascity/blog/ bizventures-kc/2014/05/kcmo-urban-agriculturalbusiness-incentives.html?page=all 15. Rosen, L. (2014, Dec. 18). Urban Farming and Food Security Act of 2014…Passed! [Web log]. Retrieved from http://dcgreens.org/urban-farming-and-foodsecurity-act-of-2014-passed/

16. Gittelsohn J, Mui Y, Adam A, Lin S, Kharmats A, Igusa T, Lee BY. 2015. “Incorporating Systems Science Principles into the Development of Obesity Prevention Interventions: Principles, Benefits and Challenges.” Current Obesity Reports, Special Issue on “Preventing Obesity.”4 (2): 174-181.

17. Munar, Wolfgang, Peter S. Hovmand, Carrie Fleming, and Gary L. Darmstadt. 2015. “Scaling-up Impact in Perinatology through Systems Science: Bridging the Collaboration and Translational Divides in Cross-Disciplinary Research and Public Policy.” Seminars in Perinatology 39 (5): 416–23. doi:10.1053/j.semperi.2015.06.003.

18. Franco, Manuel, Ana V Diez Roux, Thomas A Glass, Benjamín Caballero, and Frederick L Brancati. 2008.

“Neighborhood Characteristics and Availability of Healthy Foods in Baltimore.” American Journal of Preventive Medicine 35 (6): 561–67. doi:10.1016/j. amepre.2008.07.003.

19. Lee, Seung Hee, Megan T Rowan, Lisa M Powell, Sara Newman, Ann Carroll Klassen, Kevin D Frick, Jennifer Anderson, and Joel Gittelsohn.

“Characteristics of Prepared Food Sources in LowIncome Neighborhoods of Baltimore City.” Ecology of Food and Nutrition 49 (6): 409–30. doi:10.1080/0 3670244.2010.524102.

20. Kolahdooz, Fariba, Jennie L Butler, Karina Christiansen, Gregory B Diette, Patrick N Breysse, Nadia N Hansel, Meredith C McCormack, Tony Sheehy, Joel Gittelsohn, and Sangita Sharma. 2015.

“Food and Nutrient Intake in African American Children and Adolescents Aged 5 to 16 Years in Baltimore City.” Journal of the American College of Nutrition, April, 1–12. doi:10.1080/07315724.2014 .959206.

21. Gittelsohn, J, EA Steeves, Y Mui, A Kharmats, L Hopkins, and D Dennis. 2014. “B’More Healthy Communities for Kids: Design of a Multi-Level Intervention for Obesity Prevention for LowIncome African American Children.” BMC Public Health, 1–9.

22. The Urban Agriculture Law Project: Maryland State Legislature Passes New Urban Agriculture Tax Credit Bill. 2014. Retrieved from http://communitylaw.org/ urbanagriculturelaw/propertytaxcredit.

23. Wenger, Y. 2015. “Baltimore City Council Approves Tax Credits for Urban Farmers.” The Baltimore Sun. Retrieved from http://www.baltimoresun.com/ news/maryland/baltimore-city/bs-md-ci-urban-ag20150504-story.html.

24. Olsho, Lauren Ew, Gayle Holmes Payne, Deborah Klein Walker, Sabrina Baronberg, Jan Jernigan, and Alyson Abrami. 2015. “Impacts of a Farmers’ Market Incentive Programme on Fruit and Vegetable Access, Purchase and Consumption.”

Public Health Nutrition, April, 1–10. doi:10.1017/ S1368980015001056.

25. Young, Candace R, Jennifer L Aquilante, Sara Solomon, Lisa Colby, Mukethe A Kawinzi, Nicky Uy, and Giridhar Mallya. 2013. “Improving Fruit and Vegetable Consumption among Low-Income Customers at Farmers Markets: Philly Food Bucks, Philadelphia, Pennsylvania, 2011.” Preventing Chronic Disease 10 (January): E166

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Photo credit: GE Ventures STUDENT CONTRIBUTIONS

Precision Medicine: Unraveling the Debate Priya Vedula As Precision Medicine comes to the forefront, the research will have to be questioned. The debate of whether or not precision medicine is necessary must be viewed from both the side of science, medicine, technology as well as the side of public health. Many advocate the benefits of targeted therapy through genome sequencing. However, the actual design of the cohort study is not made clear, and there are certainly many risks associated with the implementation of genetic testing. Current research on genome sequencing has been ongoing, but there has been little evidence of effectiveness. From a public health view, the cohort studies seem to intrinsically exclude the populations with health disparities. As the health and income status gap between the wealthy and the poor continues to grow, the goals of precision medicine must be questioned. Rather than focusing on the prospects of finding the cure to rare disease, it may be more useful to allocate funds to public health prevention.

J

ust over the horizon, there is an initiative that promises to change the scope of medicine. This idea is being met with great fervor and enthusiasm. There are talks of curing cancers and acute diseases with methods that are relatively quick and inexpensive. The idea is so salient that President Obama announced the Precision Medicine Initiative in his State of the Union address in which $215 million dollars will be invested in efforts to revolutionize the way we treat disease. “We have invited the brightest minds in medicine and technology,” he said, while emphasizing that “every patient is unique…it is about delivering the right treatment, at the right time every time.” President Obama spoke of the great advancements we have made throughout history, including the polio vaccine. Precision medicine may, indeed, revolutionize medicine.

However, there are two sides of every

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coin. On one hand, we have the side of medicine and technology, and on the other hand, we have the side of public health.

In this new age of science and technology, there is an increasing shift away from general public health initiatives. Precision medicine is about finding the genomic differences in an individual. There are some very important questions that must be asked. As a young student in the school of public health, I have come to realize the importance of questioning. We must question authority; we do not have to simply accept whatever is forced on us. We must not be intimidated but rather feel empowered to stare into the eyes of uncertainty. With this, I will begin to question why precision medicine is being met with acceptance on one end and resistance on the other.

Dr. Francis Collins, the director of the National Institutes of Health (NIH), shows great enthusiasm towards precision medicine.

He says that “each cancer has its own genomic signature,” and thus, understanding the genomic codes and the characteristic features of different cancers will help to target each of those cancers in specific ways.

For those who are in support of this idea, they believe that precision medicine’s most defining quality is its targeted intervention instead of a “one size fits all” method.1 The idea is this: if a young, active woman is suddenly diagnosed with a rare cancer, rather than putting her on a regimen that involves taking drugs that are only effective 10-15% of the time, this woman’s genome can be sequenced, and a drug that specifically targets her cancer can be developed and administered to her. In the paper “Precision medicine: Beyond the inflection point,” the authors argue, “Precision medicine is not a new field or study but rather an approach to knowledge acquisition.”2 The authors believe that the transformation will occur in improvements in patient care because the data, an integration of biomedical research and clinical studies, will be organized in a new, computational form that will be easily accessible.

The Chief Executive Officer of the Bill and Melinda Gates Foundation, Dr. Susan Desmond-Hellman expressed great fervor. “As a physician who worked in the pharmaceutical industry,” she says, “this vision certainly resonates with me.”3 Despite her eagerness for what is to come, Dr. Desmond-Hellman raises an important point.

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The new dependence of precision medicine on technology will delve into questions about patient privacy, both in biomedical research as well as clinical settings. The President’s 2016 budget is partly funding a voluntary national research cohort that will consist of a million volunteers. With this new research, we will have to begin to question how this study will be implemented, what the challenges are to such a study, and what the chances are of success. In their article, “Preparing for Precision Medicine”, Drs. Mirnezami, Nicholson, and Darzi make the important point that “the successes of precision medicine will depend on establishing frameworks for regulating, compiling, and interpreting the influx of information that can keep pace with rapid scientific developments.”4 There are different ideas for the way these studies can be designed and utilized, as illustrated in the Abrams et al paper “National Cancer Institute’s Precision Medicine Initiatives for the new National Clinical Trials Network.”5 However, these studies indicate the uncertainty of many of the outcomes. For instance, in some cases, chemotherapy may be much better than many drug interventions. There is also concern that this romanticized idea of an input-output machine may be much more complex and prone to a great amount of error. In her article published in the New Yorker, Cynthia Graber showed that there is cause for concern due to misinformation and human error. This may be due to a lack of trained geneticists in the field. For example, there have been occurrences of patients

What Dr. Gehlert is emphasizing is that precision medicine is certainly important but it must focus on those who need it most. The cohort group must be representative of the entire population, not just those who can afford treatment. being incorrectly diagnosed with DiGeorge Sydndrome in which there is a deletion on chromosome 22 based on genetic screening.

The prognosis involves psychiatric disorders, learning delays, and heart defects, all of which have no cure. When misdiagnoses occurs, this can lead to unnecessary treatments and harm that spans beyond “merely stoking the anxieties of a sick person or her parents”.6 These kinds of studies show that precision medicine is not necessarily a new idea but one that has been in the works for a while now. Yet, we have to ask, what are the results and where is the progress?

According to Simonds et al, “there are currently more than 1000 genomic tests available in clinical practice for an estimated 2500 conditions with approximately 30% specific to oncology…there has been little research to determine the clinical utility of these applications.”7According to their paper published in the Journal of the National Cancer Institute, there hasn’t been much evidence that these tests have been applicable to clinical settings- there is an “evidence gap.”

In a recent study published in the Journal of the American Medical Association, Drs. Joyner and Paneth said “Two much-publicized success

in disease gene identification were BRCA1/2 for breast or ovarian cancer and mutations for cystic fibrosis. Although finding a subgroup of the population that is at very high risk of cancer is important, no new therapy has resulted from discovery of the mutations. Instead, the 5% of patients with breast or ovarian cancer who are positive for BRCA are offered enhanced screening and preemptive surgery.”8 It is important to acknowledge that every human being is an individual. Every human life is precious. Every human life has a right to be respected. As I present the arguments from the public health side, it is important to keep in mind that the goal of public health is the promotion of better health and health practices amongst a population. That is not to say that it doesn’t respect the lives of each and every individual, but in fact, it now turns the spotlight to a group of individuals who may currently be excluded from this conversation- those who are on the lower side of wealth and income; those who are socioeconomically disadvantaged, who are currently not able to afford health care or even proper food let alone get their genome sequenced to target their rare diseases.

On one extreme, we have medical professionals and scientists arguing for the importance of precision medicine, and on the other, we have public health professionals who argue that although precision medicine may be promising, this may not be something that we need right now. In the middle of this argument is Dr. Sarah Gehlert, Professor of Racial and Ethnic Diversity at the George Warren Brown school of Social Work. Dr. Gehlert said, “The way it’s set up now, the way it’s envisioned, much of the information would come from an electronic health record. But many patients, particularly those of low income, may not have a cohesive medical record to contribute; many may not even have electronic records as they may have been seen in many different emergency departments rather than regularly attending a doctor or clinic.”9 What Dr. Gehlert is emphasizing is that precision medicine is

Photo credit: Al Jazeera President Obama asks Congress for $215 million to fund a precision medicine initiative.

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certainly important but it must focus on those who need it most. The cohort group must be representative of the entire population, not just those who can afford treatment.

This argument is very important as there is not only an income gap between the wealthy and the poor, but also a health gap, which is only getting bigger. Will precision

At his State of the Union address, President Obama said, “We have invited the brightest minds in medicine and technology.”

He spoke of the involvement of human rights activists who will help develop and implement the plans for precision medicine.

Why were the great minds of public health not invited to speak? Precision Medicine is a great idea and a great initiative but I believe

cancer institute’s precision medicine initiatives for the new national clinical trials network.

2014; (): . http://meetinglibrary.asco.org/ content/114000071-144 (accessed 29 September 2015).

6. Graber C. The problem with precision medicine. 2015; (): . http://www.newyorker. com/tech/elements/problem-precisionmedicine (accessed 29 September 2015).

On one extreme, we have medical professionals and scientists arguing for the importance of precision medicine, and on the other, we have public health professionals who argue that although precision medicine may be promising, this may not be something that we need right now. medicine only exacerbate this difference?

Dr. Paneth and Dr. Joyner have noted that “improvements from public health have come either from general improvement in socioeconomic conditions or from programs targeted broadly to entire populations such as improved sanitation, mass immunization, and tobacco control.”

Dr. Ronald Bayer and Dr. Sandro Galea, Professors at the Columbia University Mailman School of Public Health wrote “the evidence that clinical intervention, however important, cannot remedy health inequalities emerges from a broad range of empirical study. Research undertaken in the name of precision medicine may well open new vistas of science and precision medicine itself may ultimately make critical contributions to a narrow set of conditions that are primarily genetically determined. But the challenge we face to improve population health does not involve the frontiers of science and molecular biology.”10 The University of Michigan Institute for Healthcare Policy and Innovation released an article regarding precision medicine and diabetes.11 In a study performed at the University of Michigan, researchers were trying to come up with a model of diabetes prevention using “blood sugar levels and waist-to-hip ratios” instead of genetic tests.

They were able to find seven useful factors that predicted the risk of diabetes. Towards the end of the study, the team emphasized the importance of exercise and weight loss- a lifestyle intervention, not a pill.

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that more emphasis needs to be placed on public health care initiatives and preventative measures not just treatment and cures. We need to focus on improving the most basic needs of the poor in our backyards before investing even more money that we already do in health care. We will have to brace ourselves for the effects of this new era.

Acknowledgements: I would like to thank my professor Dr. Ronald Bayer for inspiring me to write this contribution.

1. Collins FS, Varmus, H. A new initiative on precision medicine.The New England Journal of Medicine 2015;http://www.nejm.org/doi/ full/10.1056/nejmp1500523 (accessed 29 September 2015).

2. Hawgood S, Hook-Barnard IG, O’Brien TC, Yamamoto KR. Precision medicine: Beyond the inflection point. Sci Transl Med. 2015 Aug 12;7(300):300ps17.http://stm.sciencemag.org/ content/7/300/300ps17 (accessed 29 September 2015).

3. S. Desmond-Hellmann, Toward Precision Medicine: A New Social Contract? Sci. Transl.

Med. 4, 127ed3 (2012).https://www.ucsf.edu/ sites/default/files/legacy_files/documents/ science-translational-medicine-editorial.pdf (accessed 29 September 2015).

4. Mirnezami R, Nicholson J, Darzi A. Preparing for precision medicine. The New England Journal of Medicine 2012; 366. http://www. nejm.org/doi/full/10.1056/NEJMp1114866 (accessed 29 September 2015).

5. Abrams J, Conley B, Mooney M, Zwiebel J, Chen A, Welch JJ, Takebe N, et al. National

7. Simonds NI, Khoury MJ, Schully SD, Armstrong K, Cohn WF, Fenstermacher DA, et al.

Comparative effectiveness research in cancer genomics and precision medicine: current landscape and future prospects. Journal of the National Cancer Institute 2013; http://jnci.oxfordjournals.org/ content/early/2013/05/08/jnci.djt108.full (accessed 29 September 2015).

8. Joyner MJ, Paneth N,. Seven questions for personalized medicine. Journal of the American Medical Association 2015; (): . http://jama. jamanetwork.com/article.aspx?articleid=2344586 (accessed 29 September 2015).

9. O’Connor A. The possibility-and pitfalls- of precision medicine.2015; (): . http://news. stlpublicradio.org/post/possibility-and-pitfallsprecision-medicine (accessed 29 September 2015).

10. Bayer R, Galea S. Public health in the precision-medicine era.The New England Journal of Medicine 2015; (): . http://www.ucsf. edu/sites/default/files/legacy_files/documents/ science-translational-medicine-editorial.pdf ’ (accessed 29 September 2015).

Priya Vedula

Priya Vedula is a student at the Mailman School of Public Health in the department of Health Policy and Management. She earned a Bachelor of Science degree from the University of Michigan. She also performed research work at the University of Minnesota.

Harvard Health Policy Review

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STUDENT CONTRIBUTIONS

From Cells to Systems: The Application of Precision Medicine to Improve Healthcare Delivery Dr. Jonathan M Clarke Precision medicine promises significant advances in the individualized treatment of the leading causes of disease through unprecedented understanding of a patient’s particular pathology and physiology. The development of such tailored care coexists with health systems that are frequently inequitable and often fail to live up to the ‘gold-standard’ of clinical care. Many of the approaches and techniques used in providing precise medical therapies could be extrapolated to health systems with the aim of delivering tailored, responsive, adaptable healthcare. This article discusses the present need for health systems’ improvement in the context of personalized medicine, and lays out a structured framework through which such an approach might improve the quality and equity of care delivered at a population level.

T

wo decades of scientific progress have witnessed an exponential increase in our understanding of human disease.

Patient-specific genetic and phenotypic data pertaining to some of the greatest causes of mortality — particularly cancer, diabetes and cardiovascular disease — have contributed significantly to this progress. These data exist thanks to advances in techniques that are able to identify subtle genetic and phenotypic variants in response to disease, the development of computer systems capable of performing complex statistical analysis, and greater emphasis on multi-centre collaboration between academic departments and healthcare institutions.

Together, these data keep the physician far better informed about the biological idiosyncrasies of their patients and their pathologies—with that comes the prospect of specific therapies tailored towards targeted pathological pathways1. Oncologists have ventured into evidence-based, individualized therapies for the treatment of cancer, and studies have demonstrated the potential benefit of individualized therapies across a range of tumours including colorectal cancer, brain tumours and haematological malignancies2–5.

In a number of cases, however, personalized treatments for cancer have had less convincing outcomes, suggesting that a healthy dose of scepticism might be in order6,7.

By committing $70 million to precision medicine in his 2015 State of the Union Address, President Obama greatly spurred interest in the research and implementation of tailored therapies8,9. Recent years have seen an accelerated evolution of healthcare funding and provision in the United States, albeit within a health system defined by disparities in access to care and quality of accessed care.

Improving the equity and quality of an existing standard of care may increase the health and wellbeing of the population more effectively than an investment in the discovery of evermore individualized therapies10. Applying the analytical skills, research structure, and implementation strategies of precision medicine to health systems research would result in individualized systems that are more robust, adaptable, and responsive to the needs of the population they serve.

The Cost of Personalized Medicine Personalized medicine, or adapting a patient’s treatment to the individual characteristics of their disease, is more costly than current therapies. To individualize therapy, a clinician must have a detailed understanding of their patient’s pathology and the biological milieu in which it arose. This necessitates a higher degree of specific, complex, and costly diagnostic tests, which often take the form of genotypic and phenotypic analysis. Only once armed with this information a clinician may choose—out of an array of therapies—the one

that is likely to maximize benefit and minimize harm. Whether for logistical or financial reasons, most of these investigations remain beyond the reach of the majority of health systems worldwide.

As a pathology is fragmented into a range of disease subtypes, so too are the range of therapeutic regimens designed to treat it.

The greater the number of treatments each centre uses, the smaller the quantities of each product it requires. This raises the price of each treatment, leading to a higher cost of individual care.11 Patients are priced out of the market in a double sense: not only are the nuances of their condition too expensive to identify, but—even if this difficulty is overcome—the therapies are also unaffordable12.

Marginal Benefits System Failures

are

Dwarfed

Additional improvements in individualized therapy are dwarfed by the potential to improve population healthcare through advances in the efficiency and equity of health service provision and disease prevention10.

Both between and within nations, significant disparities exist in disease risk and treatment outcomes, though the specific treatment for a condition seldom changes from country to country. It matters little how individualized a therapy may be if health system failures lead to absent preventive measures, delayed diagnosis, and poor implementation of care. The efforts of data scientists and clinicians towards increasingly marginal gains may be directed more effectively towards population health systems improvement13.

Scientific, organizational, and computational advances that have contributed to the development and early success of precision medicine in cancer treatment have been closely paralleled by analogous advances in health systems improvement14. The international transition towards electronic health records has provided rich and standardized information regarding the provision of care within a particular centre, and in comparison to regional,

Figure 1 Fall 2015 Volume 15, Issue 1

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national and international standards. As a result of these changes, just as in oncology, health systems can be improved in an unprecedented evidence-based, individualized fashion.

A Personalized Approach to Systems In the model of precision medicine for cancer therapy, physicians treat their patients based on the identification of patient-specific characteristics of the cancer. Individualized therapies may therefore be instituted based on robust evidence to maximize efficacy and minimize harm. A health system could be modelled in a similar fashion.

Different health systems, like different cancers, have many features in common with one another, but also many differences that may represent important avenues for intervention. These unique systems differences must be considered within each system’s broader environment, just as the impact of a tailored cancer therapy is evaluated in the context of the individual patient it is designed to treat. In both cases, this evaluation results in the implementation of bespoke, precise, and personalized therapies or interventions.

The intervention chosen may draw from prior empirical evidence and the consensus of learned bodies or national guidelines, and the response to an intervention may be reflected upon via a review of a patient in clinic or a review of a health system through regular audit of performance (Figure 1).

In both the case of a cancer and a health system, investigation of the problem may not reveal a known solution15. In the absence of such rigorous investigation, as is the case prior to precision medicine, the success or failure of treatment would be judged simply as fortune or misfortune. With precision medicine, the physician is able to say with greater certainty than ever before whether or not a treatment will be effective for a patient. In such situations, the physician may inform their patient that there may be little that current medicine is able to offer them. Where current medicine is unable to provide a solution, there is often a strong desire felt by both patients and their physicians to work to improve upon what medicine can offer. This situation tends to lead to innovation, in which novel strategies are adopted with the hope of improving a patient’s condition in the understanding that their prognosis may not be improved or may even be worsened as a consequence.

An important difference in the case of innovation in health systems is that unlike a single cancer patient agreeing to participate in a clinical trial, it is rarely possible to consult all stakeholders served by a health system on the risks of an intervention or to seek widespread

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consent for every change. As such, safeguards aimed at ameliorating any negative outcomes must be no less stringent and regularly assessed than in the context of a clinical trial. Real-time, precise analysis of local and national healthcare data provides the opportunity not only to test innovations, but also to ensure the safety of a population during a change in care delivery.

Clinicians have often been fearful of largevolume, highly specific datasets. However, precision medicine has developed strategies to overcome such fears, and these strategies should be embraced and utilized in understanding the behavior of health systems. Aggregating local electronic healthcare data will allow us to evaluate—simultaneously—the function of a national health system and of a single institution within it. Through identification of local or systemic deficiencies in care, a network of institutions may individually or collectively innovate to solve these problems. Real-time, standardized data collection permits ready, replicable analysis of how systems respond to change, thereby empowering clinicians to monitor care delivery on a previously unattainable scale.

1. Mirnezami R, Nicholson J, Darzi A. Preparing for Precision Medicine. N Engl J Med. 2012;366(6):489-491.

2. Schwaederle M, Zhao M, Jj L, et al. Impact of Precision Medicine in Diverse Cancers : A Meta-Analysis of Phase II Clinical Trials . J Clin Oncol. 2015 Aug 24 pii: JCO.2015.61.5997. [Epub ahead of print] 3. Allegra CJ, Jessup JM, Somerfield MR, et al. American society of clinical oncology provisional clinical opinion: Testing for KRAS gene mutations in patients with metastatic colorectal carcinoma to predict response to anti-epidermal growth factor receptor monoclonal antibody therapy. J Clin Oncol.

2009;27(12):2091-2096.

4. Hunger SP, Mullighan CG. REVIEW Redefining ALL classification : toward detecting high-risk ALL and implementing precision medicine. Blood. 2015;125(26):39773988.

5. Prados MD, Byron S a., Tran NL, et al.

Toward precision medicine in glioblastoma: the promise and the challenges. Neuro Oncol.

2015;17(February):1051-1063.

6. Peer D. Precision medicine – Delivering the goods? Cancer Lett. 2014;352(1):2-3.

7. Arnedos M, Vicier C, Loi S, et al. Precision medicine for metastatic breast cancer— limitations and solutions. Nat Rev Clin Oncol.

2015. doi:10.1038/nrclinonc.2015.123.

8. Collins FS, Varmus H. A New Initiative on Precision Medicine. N Engl J Med. 2015 Feb 26; 372(9):793-5.

9. Obama BH. State of the Union Address.

Capitol Building. Washington, D.C. 20th January 2015.

10.

Bayer R, Galea S. Public Health in the Precision-Medicine Era. N Engl J Med. 2015;373(6):497-499.

A Patient-Focused Future Precision medicine certainly has the potential to improve the efficacy of therapies for some of the leading causes of disease. As in preceding years, the next decade promises exciting advances in how we understand the biology of disease and subsequently adapt care to a patient’s pathology. Presently, and perhaps for some time to come, personalized care will remain entirely out of reach for most health systems because of its costly implementation.

Even where it is within reach, precision medicine may only exert a subtle impact on health outcomes for many conditions. But if we apply techniques from precision medicine to health systems, we might open up the possibilities for timely, tailored improvements in the efficiency and equity of healthcare for the benefit of the wider population. As healthcare looks towards a patient-focused and data-driven future, a physician finds him or herself well positioned to combine the two. Rather than fixating on giving ever more individualized care to patients in the singular, the physician can improve care in the plural through an openness to precise health systems analysis, and the innovations it can provide.

Dr. Jonathan Clarke is a Kennedy Scholar and Master of Public Health Candidate at the Harvard TH Chan School of Public Health.

He is a general surgical resident and research fellow at the Department of Surgery and Cancer at Imperial College London.

11.

Aronson N. Making personalized medicine more affordable. Ann N Y Acad Sci. 2015: Jun 1346(1): 81-9.

12.

Trusheim MR, Berndt ER, Douglas FL. Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers. Nat Rev Drug Discov.

2007;6(4):287-293.

13.

Coote JH, Joyner MJ. Is precision medicine the route to a healthy world? Lancet.

2015;385(9978):1617.

14.

Larson E, Wilke R. Integration of Genomics in Primary Care. Am J Med. 2015. doi:10.1016/j.amjmed.2015.05.011.

15.

Andre F, Mardis E, Salm M, Soria J-C, Siu LL, Swanton C. Prioritizing targets for precision cancer medicine. Ann Oncol.

2014;25(12):2295-2303.

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