Slalom CONNECT Magazine | Digital Health: Beyond the New Normal

HEALTHCARE AND LIFE SCIENCE EDITION

SUMMER 2021

DIGITAL HEALTH BEYOND THE NEW NORMAL ROBOTS AND AUTOMATION • DIVERSITY IN CLINICAL TRIALS • BUILDING BETTER HEALTHCARE PRODUCTS + MORE

Foreword

As an optimist and innovator, I am incredibly excited about the opportunity to leverage the learnings of this past year to drive innovation and equity into our Health & Life Sciences ecosystem.

As an adjunct lecturer in Healthcare, perhaps what has me most excited about our future is the resurgence in our next generation’s interest in working in the Health & Life Sciences industry. With the advances in digital technology, the distribution of talent required to support a global supply chain and the renewed focus on health equity, now is the time to be building our next generation of leaders.

BARRY WOLFIELD Managing Director, Healthcare Northeast

This issue of Slalom Connect will explore how we can leverage the recent influx of fresh perspectives and bold ideas to improve the health of our global community. Here are a few highlights of what you will find inside: • The past year has allowed us to explore and optimize how children learn using digital technology. How can we leverage this knowledge to improve how we build AI / ML based learning systems?

• The pandemic has shined a bright light on socio-economic and health equity in the US and around the globe. How can we leverage the rapid acceleration of virtual healthcare to be more inclusive of those in rural communities, inner cities and developing nations?

• The speed, scale and global reach of the recent Covid-19 clinical trials highlighted the collective power of the life science industry, but the media spotlight highlighted the lack of diversity in these trials. How do we improve our public / private partnerships to take this to the next level?

• Our ability to bring vaccines to market in a year has been an amazing feat by any standard but it has also exposed the weaknesses in our supply chains. How can we convert the many innovative temporary solutions into tomorrow’s digital supply chain infrastructure?

Now is the time to think differently, expand your network, explore new partnerships and capitalize on the momentum that is driving the Health Life Sciences industry forward.

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Slalom Connect — Healthcare 2021

Contents 5

Building Resilience in Life Sciences Supply Chain to Mitigate the Effects of COVID-19

ANKUR BALAR

10

Impactful Healthcare Products Begin and End with Outcomes DAN GALLAGHER

14

U.S. Women Most at Risk in Developed World During Childbirth

SHANNON MONTANEZ; LEAH O’DONNELL

20

Robotic Process Automation The Future of Healthcare MAREN MELLEN; CARLY SHUMRICK

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Slalom Point of View: Clinical Trials in 2021+ The Future of Clinical Trials is Accelerating Thanks to a Pandemic’s Worth of Attention

JOHN PUGH; COLLIN BURDICK

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Promoting Diversity in Clinical Trials

Slalom Connect Copyright © 2021 by Slalom, LLC All rights reserved.

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Images provided by: unsplash.com Printed in the United States of America Contact Slalom Consulting 399 Boylston Street Suite 1000 Boston, MA 02116 617-316-5400 technology.slalom.com Contributors Ankur Balar Dan Gallagher Leah O’Donnell Shannon Montanez Maren Mellen Carly Shumrick John Pugh Collin Burdick Meghan Sommerkamp Audra Bieg April Ferguson Elaine Chung Michelle Yi

MEGHAN SOMMERKAMP; AUDRA BIEG; APRIL FERGUSON

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Why Robots & AI Need to Play to be More Impactful in Healthcare

ELAINE CHUNG

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Our Partners Slalom Connect — Healthcare 2021

Production, Design & Publication Josh Drumm Blake Foster Karl Schwirz Maren Mellen Special Thanks Barry Wolfield Becky Kailus Jeff Yeakley Mike Dolan

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Slalom Connect — Healthcare 2021

Building Resilience in Life Sciences Supply Chain to Mitigate the Effects of COVID-19

ANKUR BALAR

The global COVID-19 pandemic has

crisis has forced business leaders

impacted every facet of our lives

to build increased resilience in their

personally and professionally, including

supply chains to protect them from

the Life Sciences industry. The focus

the impacts of the pandemic and

on vaccines and therapeutics for

other disruptive events in the future.

COVID-19 has disrupted supply chains considerably. Whether it be delays in the supply of active pharmaceutical ingredients, rescheduling patient procedures, access to medicines, or the global shortage of Personal

Based on our conversations with Life Sciences supply chain leaders, we foresee the following longterm trends post-COVID-19 for Life Sciences supply chains.

Protective Equipment (PPE), this

Slalom Connect — Healthcare 2021

5

Drug Manufacturing will evolve from global to “local”, e.g. distributed and localized supply chains. Review your sourcing and supply chain strategy and practices accordingly.

Historically, the production of medicines for the U.S. population has been domestically based.

However, in recent decades, drug manufacturing has gradually moved out of the United States. This is particularly true for manufacturers of active pharmaceutical ingredients (APIs), the actual drugs that are then formulated into tablets, capsules, injections, etc.

The FDA recently reported that only 28 percent of the manufacturing facilities making APIs to supply the U.S. market were in the U.S. In the last decades, Life Sciences companies have organized their supply chain networks focusing on costs control instead of risk management to enable flexible supply chains.

We predict that the largest global suppliers of drugs, mainly India and China, will continue to apply temporary export controls for essential drugs and PPE equipment post-pandemic. This will pressure various Life Sciences companies to build production capabilities closer to home.

Life Sciences leaders will have to shift their approach to start sourcing ingredients from a more diverse range of suppliers and vendors. This enables Life Science organizations to build and implement new sourcing tactics and partnerships accordingly.

6

Digitization will be required for increased supply chains visibility Among the biggest reasons why Life Sciences companies are struggling to react quickly is their lack of end-to-end supply chain visibility. When there was no shortage of supplies, Life Sciences companies operate by making compartmentalized and siloed decisions that often lack a comprehensive view. This approach left drug manufacturers blind to which ingredients were in the shortest supply or even which ones might run out during pandemic lock-downs.

Reports on ideal stockpile levels and country-of-origin information for every ingredient or part that could affect manufacturing capability were not available centrally and were more reactive than proactive. With all these underlying issues in mind, the pandemic, has accelerated the need for change for drug manufacturers across the Life Sciences industry.

In the short term, Life Sciences companies must quickly deploy

new platforms for supply chain visibility as well as integration capabilities to tear down data silos and enable end to end insights generation. They must immediately focus on implementing cloud-based visibility solutions on top of their existing systems. Also, Life Sciences companies must establish a rapid response team as part of a multi-function and multi-geography supply chain command center. This team must be comprised of Senior Supply Chain leaders from each area of supply chain, including patient and customer experience representatives.

In the longer term, Life Sciences companies should focus on establishing “Supply chain control towers” throughout the entire supply chain organization (analysts to Chief Supply Chain Officer and Chief Commercial Officer) across the end-to-end supply chain, both internally and externally with partners. Their primary goal should be to gain insights into their supply chain by embracing existing systems and external data sources, predicting the risks before they

Among the biggest reasons why Life Sciences companies are struggling to react quickly is their lack of end-to-end supply chain visibility.

Slalom Connect — Healthcare 2021

happen, and taking recommended actions prescribed by the tool as a decision support platform. Also, Life Science organizations need to up-level their relationships and partnerships with external providers, commercial and government stakeholders, and downstream providers. The COVID-19 pandemic has triggered more collaboration; however, now it is time to solidify the foundations and change siloed mindsets to sustain the improvements required to face the pandemic.

With high demand and supply variability: prepare your organization for volatility.

One of the biggest challenges left to face is the need to address the simultaneous increased variability of patient demand with the increased supplier visibility.

Slalom Connect — Healthcare 2021

As a result of the pandemic, patient behavior and supply chain actors have changed. Now, patients are stocking up on many drugs due to fear of drug shortages. A quick review of Drug Shortages reported by The FDA clearly presents this picture.

moves further up the supply chain. This often results in upstream manufacturers experiencing a decrease in forecast accuracy as the buffer increases between the customer and the manufacturer. The diagram below illustrates the concept.

Healthcare teams are recommending patients to take this action to reduce their exposure to COVID. The noise in the demand data stream has increased, making the true demand signal harder to determine. On the other hand, suppliers have their own disrupted upstream supply chain network, hence they are unable to meet their commitments at the previous levels.

Given these competing market forces, The Bullwhip Effect is in full force up and down the healthcare supply chain. The Bullwhip Effect, also known as The Forrester effect, is a concept explaining inventory fluctuations that result from demand changes as the information

To mitigate demand and supply disruptions, an improved ability to “sense” supply and demand trends can be established through next-generation analytics that integrate relevant data from a range of sources. With the integration of such a broad range of structured and unstructured signals and automation of real-time data updates, realization of continuous planning and accelerated response to unexpected changes can be established.

These additional sources of data combined with deeper statistical analysis and forecasting can improve the overall accuracy of demand forecasting.

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Companies can implement advanced demand planning solutions that enable life-cycle planning, multi-variate segmentation, hierarchical planning, and machine-learning based on tuning of the most accurate algorithm for each forecasted item. Visual analytics be leveraged to incorporate a broad range of factors and enable artificial intelligence (AI) capabilities to learn and refine relationships. This supports an approach based on what-if scenarios, informed decisions, and operational adjustments to identify possible supply chain events.

If appropriately applied, even a small fraction of improvement in demand forecast accuracy can enable a significant reduction in costs and improvements in fill-rates. In a post-pandemic era, dynamic planning will become of increased importance as will the ability to plan based on probabilities of change rather than firm predictions.

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A balancing act, “from costs focus to resilience”, will lead to innovative efficient and effective supply chains Whether to onshore or offshore production, leaders should start with the question, “How can we forge a supply chain that creates the most value?”. That will often lead to an answer that involves neither offshoring nor onshoring; but rather, “multishoring,” which is helps reduce risk by avoiding dependency on any single source of supply.

The supply chain design for Life Sciences companies will need to strongly consider not only ‘justin-time’ but also ‘just-in-case’.

One important area of vulnerability that many Life Sciences companies realized during the pandemic is the lack of deeper understanding of the upstream nodes in their supply chain.

Often during the pandemic, critical inventory material could not be delivered in a timely manner because the supplier of suppliers could not deliver

the expected supply. With such situations, Life Sciences companies will need to evaluate their risk aversion and make decisions utilizing bottom-up estimates of inventory and scenario planning. Suppliers could be required to develop and maintain risk management plans. By asking introspective questions like: Is there an element to collaborative planning then can play in here, on top of requiring suppliers to build risk management plans?

What is in it for them? Life Science organizations can conduct better, more accurate scenario planning with key partners.

In conclusion, Supply Chain leaders will need to further prioritize capabilities to build greater resilience. The impact of the pandemic requires adopting new supplier risk management and digital-planning tools to create greater resiliency, increased capability, better inventory management, accurate demand management, and diverse risk management across the value chain. Doing this will enable Life Sciences companies to react well to changes in supply or demand conditions. n

Slalom Connect — Healthcare 2021

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IMPACTFUL HEALTHCARE PRODUCTS BEGIN AND END WITH OUTCOMES DAN GALLAGHER

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Slalom Connect — Healthcare 2021

A common (and critical) mistake product teams make is over-estimating the impact the product or feature they are building will have on their target audience. In fact, only 20% of software product or features have the positive impact initially intended, according to Jeff Patton in User Story Mapping: Discover the Whole Story, Build the Right Product.

So, what about the remaining 80%? Patton argues that 60% of features have little to no impact, while 20% are a complete failure and releasing them ended up hurting the product. In essence, 80% of products and features bring no value and users and organizations would have been better off if the time, effort, and resources were never invested in them to begin with.

From our experience at Slalom, Patton’s numbers are not far off. We often engage with clients after they have gone through an agile transformation only to find that the continuous delivery nature of agile is resulting in the building the wrong things faster. The idea that 80% of features go unused is incredibly detrimental in any industry, but it is particularly destructive in healthcare. In healthcare, successful products and features bring outcomes that go beyond a better patient experience. Successful products and features bring outcomes that can save patient lives and enable institutions to scale game-changing procedures.

As Healthcare continues to shift toward Agile software product development, progress and success is often focused on the rapid delivery of features, which is also the focus of agile. The success of agile transformations is predominately measured by velocity (story points per sprint, burndown charts, etc.). These metrics measure how fast outputs (features or applications) are delivered; however, they don’t measure the value created and realized by the patients, providers or institutions. It is through this outcome that impact is made, and value is realized, not solely the usage of the product itself.

the product development process. However, the discovery pathway is murky. To successfully navigate this pathway, product teams need to continually discover and validate along the way. Often the countless assumptions that are made about the provider, the patient, the underlying need, the workflow, the value proposition, existing alternatives, etc. contribute to the lack of clarity throughout the development process. Navigating the discovery pathway to high impact products takes constantly adapting to continuous feedback. It is in this constant adaption that the delivery cadence of agile can be the foundation that enables continuous discovery of what to build. If that cadence is enabling the delivery of something for users to respond to then assumptions can be validated (or invalidated) continually through user feedback.

At Slalom, we believe that true product discovery begins when something, designed to test critical assumptions, is built. Whether it is a low fidelity mock-up, a mid-fidelity prototype or high fidelity working software, what matters most is the early validation (or invalidation) of critical assumptions.

Assumptions are a necessary part of product development and are required in the beginning. However, invalid assumptions left unchecked can be fatal. It is these invalid assumptions that are behind the 80% of unused features highlighted above. An example of this was a clinical decision support (CDS) application we were developing for providers. The premise was to make society diagnostic guidelines interactive and customize them based on a patient’s medical record. This CDS app was intended to work within the clinical workflow. As most product developers in healthcare know, creating continuous feedback

Our commitment to continuous feedback loops and some out-of-the-box thinking

To build impactful products, it is critical to start with the desired outcome and use it as the driving force throughout

Slalom Connect — Healthcare 2021

opened powerful continuous learning opportunities.

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loops to guide continuous discovery and inform key product decisions is difficult.

Product discovery is further complicated by a lack of access to EHR systems, HIPAA constraints, and inability to consistently connect with the time-constrained providers that were the target audience of the product.

Our commitment to establishing continuous feedback loops and some out-ofthe-box thinking, opened powerful continuous learning opportunities. Working with the provider institutions that would benefit from this CDS product’s success, we got permission to set-up a folding table in the cafeteria to solicit user feedback directly from providers. The two-week cadence of these feedback sessions coincided with the sprint cadence, establishing a continuous feedback loop that helped us make pivot/pause/proceed decisions quickly and inform the next sprint.

We started with low-fidelity wire frames designed to test basic assumptions related to the user’s underlying needs. These initial “experiments” focused on assumptions related to desirability. What were the critical, and therefore riskiest, assumptions we were making about the user’s underlying needs? Would our initial product assumptions address the user’s underlying needs? After a few cafeteria sessions, using only low fidelity prototypes, it became clear that our initial research-based assumptions were invalid. This confirmed that true product discovery begins when something is built and tested, re-built and tested, re-built and tested, etc.

An example of a key assumption coming out of research was that placing a provider at a certain node within a diagnostic algorithm, based on the symptoms their patient is presenting with, was a highly desirable. But when confronted with how that would actually work and seeing it in the context of how they would interact with it, users grew concerned. They quickly realized that they were trusting technology to make the decisions

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leading up to that point in the algorithm and would have to back track to see what/how prior decisions were made. Furthermore, providers would often go through these diagnostic algorithms multiple times slightly altering their decision at critical points to see the impact different decisions would have.

Placing the provider contextually within the algorithm based on the details in the specific patient’s record was one of the cornerstone features of this new product as well as a significant technical challenge. Within the first three sprints (six weeks) we learned that one of the cornerstone features of this product was shaped by assumptions that were just plain wrong.

Fail early! That is what we did, we didn’t build the technology behind this feature only to find out that our assumptions were wrong after we spent the time and resource then released it to beta. We successfully invalidated research-based assumptions regarding what was desired. We were able to pivot and focus on some other cornerstone features that had emerged in the initial research and found that, through continuous discovery fueled pivots, were able to bring a successful product to market.

Continuous Discovery enables teams to test assumptions continually. It’s a process that refines and evolves ideas based on constant feedback from the continuous delivery of testable Minimal Viable Product (MVP) that keep the team on track toward building the right things. n

Slalom Connect — Healthcare 2021

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U.S. WOMEN MOST AT RISK IN DEVELOPED WORLD DURING CHILDBIRTH

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Slalom Connect — Healthcare 2021

SHANNON MONTANEZ

LEAH O’DONNELL

Women in the US today are 50% more likely to die in childbirth than their mothers. This chilling statistic flies in the faces of modern medicine and expanded life expectancy for women. Women in the U.S. are the most likely to die from complications related to pregnancy or childbirth than any other country in the developed world.

In 2018, there were 17 maternal deaths for every 100,000 live births in the U.S. — a ratio more than double that of most other high-income countries. In contrast, the maternal mortality ratio was three per 100,000 or fewer in the Netherlands, Norway, and New Zealand1.

The difference is even more staggering for women of color.

According to the CDC, Black, American Indian, and Alaska Native (AI/AN) women are two to three times more likely to die from pregnancy-related causes than white women – and this disparity increases with age. (Emily E. Petersen, et al., 2019) Thankfully, we see exciting work being done in this space to improve the quality, and dignity of care for expecting mothers.

For example, March for Moms brings together policymakers, traditional healthcare providers, midwives, and families to focus on maternal health advocacy. I had the privilege of working pro bono with March for Moms as they looked to identify the organization’s focus for the future. From our partnership with March of Moms, we see opportunity in the following areas:

Slalom Connect — Healthcare 2021

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Improving the Patient Experience during Pregnancy One in six mothers feel disrespected by healthcare providers during pregnancy.

Patients’ voices are the most important voices during any clinical interaction. Providers are likely not intentionally disrespecting women, but underlying biases can play a role in making assumptions about patient care. For example, women are seven times more likely than men to be misdiagnosed when having a heart attack.

This gender bias is rooted in the research around heart attacks which focused on male physiology. (Women Are Dying Because Doctors Treat Us Like Men, n.d.). While Labor & Delivery services are clearly focused on women’s bodies, these biases can trickle in from other areas.

Bringing in patient advocates and professionals like midwives and doulas can help create a more open collaborative setting for care. Doulas can provide education on what the labor and delivery process is like, providing the patient an additional source of knowledge and emotional support during that time. Midwives are certified practitioners (varies by state) who can deliver babies in other settings, such as the home.

Partnerships between OB/GYNs and other birthing professionals are becoming more common as patients opt for a more holistic approach. One potential way for providers to provide better communication during prenatal care as well as Labor & Delivery is to have strong communicators in the room who can raise concerns for the patient and create a more open dialogue.

This could be doulas, midwives, advocates or even trained physicians and nurses.

Women control most healthcare decisions, why doesn’t the healthcare industry serve them better?

In most industries, businesses follow the dollars. In the wacky world of healthcare, while that is sometimes the case, in other cases, not so much. Let’s take women’s health. For example, women:

51%

of the population

16

90%

are primary healthcare decision-makers in their families

27%

more expenses per capita than their male peers

66%

feel misunderstood by healthcare market

Slalom Connect — Healthcare 2021

Incorporating Women into Birthing Decisions Caesarean section (C-section) is the most common surgery performed in the United States every year.

Since 1990, babies being born via C-section have tripled. In the United States, over 1 million c-sections are performed each year2. C-sections are an invasive surgery and carry different complications than a vaginal birth. For a mom, risks include bleeding, uterine rupture, hysterectomy and more. For babies, birth by C-section

can raise the chance of obesity or autoimmune diseases. This may be attributed to a lack of exposure to vaginal microbiomes during delivery3.

This increase in C-sections is likely tied back to risk management by providers, and financial concerns. While researchers vary on what the optimal c-section rate should be, we know that the risks and birthing mom’s preferences should be considered before the decision is made. Communication of these risks is key to improving that birthing experience.

The fact is that despite women making the lion’s share of decisions and dollars when it comes to overall healthcare spend, women’s health gets a relatively low share, hovering around $1B of the $21B of seed, venture capital and private equity dollars that went to digital health funding in 2020.⁵

women are expected to be post-menopausal.

According to the Female Founders Fund, a venture capital fund that exclusively funds, you guessed it, female founders, the average spend over the course of menopause (which can last anywhere from four to 10(!) years) is $20,000.

The real opportunity is much, much bigger. We just need to expand how we think about women’s health.

Increasing the number of women in leadership positions across the healthcare spectrum will help drive future innovation. Venture capital firms with at least one female investing partner are three times more likely to fund companies with female CEOs — but less than 10% of investing partners in US venture capital firms are women. In 2019, womenfounded or women-led companies received just 2.7% of overall venture funding. And lastly, while 80% of healthcare industry employees are women, fewer than 20% are in leadership roles.

The good news is that the women’s health market is starting to expand. Interest and investment in a wider range of conditions have taken off recently as overall awareness and comfort with women’s health has grown. While not all women will get pregnant in their lifetimes, virtually all women who reach their 50’s will go through menopause. By 2025, 1.1 billion

Slalom Connect — Healthcare 2021

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Expanding Holistic Care and Patient Communication during Pregnancy Medicaid is the payer with the most births each year. In the United States, Medicaid covers more than 40% of births. These low-income patients may have different needs during the labor and delivery process. For instance, birthing mothers may not have received comprehensive prenatal care, either due to lack of awareness about the coverage or due to work schedules or other competing priorities.

According to a 2019 study, Medicaid-Covered C-sections pose a higher risk of infection. Similarly, women with Medicaid coverage are more prone to higher mortality risks during pregnancy4. Several factors may be at play here including the quality of the provider institution, a lack of adequate prenatal care or patient health literacy. Incorporating some of these patient communication and holistic care models into our Medicaid programs can make a huge difference in patient safety during Labor & Delivery, especially in vulnerable patient populations, such as those with transient living situations. n

March for Moms has been advocating for opportunities to design better public policies that focus on inequities in healthcare. For example, the Black Maternal Health Momnibus Act of 2021 was introduced into Congress and all 12 bills have been endorsed by more than 190 organizations. The bills address many issues such as improving data collection and qualities measures, providing funding to community-based organizations working to improve maternal health outcomes, growing and diversifying the perinatal workforce, and improving maternal healthcare and support for incarcerated moms. These bills will undertake the maternal health crisis in the U.S. and ensure that birthing people have access to the care and support needed to be able to thrive.

“March for Moms will engage in thoughtful, action-oriented conversation that will center birthing people that are disproportionately being impacted by health inequities. We will work across a broad coalition of consumer and family, professional, policymaker and industry representatives to align and amplify their voices to ensure that every American family can grow with dignity,” says Laneceya Russ, Executive Director of March for Moms. “We plan to do this by: educating stakeholders on policy changes that will lead to positive outcomes in the lives of birthing people and developing the capacity of community organizations and advocates through resource sharing and education. We aim to track the progress that is being made in the maternal healthcare space through the many amazing organizations that are on the ground doing the work to ensure birthing people are not only surviving but that they are thriving.”

1.

Maternal Mortality and Maternity Care in the United States Compared to 10 Other Developed Countries. Maternal Mortality Maternity Care US Compared 10 Other Countries | Commonwealth Fund. (n.d.).

3.

Neu, J., & Rushing, J. (2011, June). Cesarean versus vaginal delivery: longterm infant outcomes and the hygiene hypothesis. Clinics in perinatology.

2.

Jauniaux, E., & Grobman, W. A. (n.d.). Caesarean section. Oxford Medicine Online.

4.

Psqh. (2019, July 2). Medicaid-Covered C-sections Pose Higher Risk of Infection. Patient Safety & Quality Healthcare.

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Please visit MarchforMoms.org to learn more about their mission to improve the health and well-being of all mothers through advocacy and awareness.

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Robotic Process Automation THE FUTURE OF HEALTHCARE

MAREN MELLEN

CARLY SHUMRICK

In the next three years, Gartner predicts that 50% of healthcare providers will have invested in Robotic Process Automation (RPA)1. RPA provides many tangible benefits to healthcare organizations, including reducing manual errors, improving the patient experience, optimizing medical equipment, and simplifying business processes.

However, it can be difficult to pinpoint exactly what challenges RPA can solve for, what to prioritize, and where to begin your RPA journey. This article will discuss five key opportunity areas for RPA in healthcare today and provide example processes that can benefit a range of healthcare organizations.

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Slalom Connect — Healthcare 2021

5 Key Opportunity Areas for RPA in Healthcare Organizations good candidates for automation. With an investment under $100k, the client was able to automate four of these processes and realized $350k in estimated annual savings. Based on this success, this client is continuing their RPA journey and working through the backlog of additional identified processes.

view dashboard” with details on patient history, trends, and even predictive health analytics — empowering providers to personalize the patient experience and improve patient care.

Invoicing and Claims Processing Invoicing and claims processing can be an expensive, manual, and time-consuming activity for healthcare companies.

Adhering to strict billing guidelines is critical, as mistakes are often complicated and burdensome to rectify. Unfortunately, many mistakes are a direct result of human error and the inefficient, manual processes in place. RPA removes the risk of human error by replacing manual processes with clearly documented, tracked, and traceable steps. Furthermore, the cost savings associated with RPA in this area can be great due to the high volume of transactions that occur each day.

Recently Slalom partnered with a leading healthcare technology company that processes claims on behalf of its customers.

The company’s backend claims processes required manual intervention at multiple steps which often resulted in human error and complicated rework.

After assessing this division’s sub-processes, Slalom was able to identify over 55 claims processing workflows that were

Slalom Connect — Healthcare 2021

Document Management

Patient Experience Providing a seamless patient experience can be difficult when data is located within multiple systems. One study found that, on average, U.S. hospitals have 29 different electronic systems that store patient data². As patient demands become increasingly complex, companies must work harder to keep up with emerging medical and digital technologies while simultaneously maintaining and protecting patient data. RPA enables a better patient service by intelligently checking data across systems and updating patient records in real time. RPA ensures that the data is consistent and can automatically populate known information for traditionally manual activities like patient check-in forms. In addition, the ability to connect data across systems enables healthcare providers to access a “customer

Healthcare organizations spend a lot of time filing paperwork and completing documentation.

Inefficient document management affects each level of the organization, including patient care. One study estimates that physicians spend up to 49% of their time completing paperwork and navigating the EHR system³. RPA documentation solutions not only replace repetitive, monotonous employee tasks but they make data processing more efficient, freeing up time for providers to spend with patients. With data integration across platforms, RPA can automatically update forms, notes, and health records with known patient and provider information. Though automatic data entry, RPA helps providers quickly and accurately intake, file, and process patient health records while also monitoring the data, users, and activity for fraud and/or error prevention.

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Also, RPA can streamline front-office patient onboarding processes by simplifying patient registration and other critical documents with data validation, user verification, and cross-application data integration. RPA software robots can even scan document images for information and update patient records automatically. Plus, RPA document management solutions facilitate immediate collaboration and communication — enabling providers to share critical patient data across practices quickly and securely — saving critical time in the event a patient emergency occurs.

robots can make sure that the right people have access to the right information. Often patient data is important to many departments within an organization. With RPA you can ensure that members from finance, IT, and/or marketing, only have access to the patient information that is relevant to their needs.

Additionally, RPA solutions keep a detailed history helping organizations easily spot any issues or misuse in audit records.

Chatbots

Compliance Keeping electronic medical records secure and HIPAA compliant (along with maintaining other regulations) are top priorities for any healthcare organization. However, protecting patient medical data and ensuring that processes are HIPAA compliant can become complicated if organizations rely heavily on repetitive, manual processes or operate across several applications. RPA provides a solution to reporting standardization, payment transparency, and protecting patient privacy with secure features like role-based access. With rolebased access, RPA software

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Online chatbots can serve as valuable automation tools to elevate the patient experience and optimize processes. Chatbots can be used to book/modify appointments, send insurance quotes or pharmacy/medication reminders, capture customer feedback, and even streamline the check-in process by capturing information from the patient. RPA chatbots can interpret data from multiple sources and then trigger any number of business tasks. Since the chatbots never sleep, they work 24/7 to fulfill customers’ needs and/or process large volumes of repetitive tasks, thereby limiting or eliminating the need for costly and often error-prone human interactions and handoffs.

As an emerging AI technology, RPA can be a differentiator for a variety of healthcare organizations. Healthcare leaders need to consider how leveraging these new technologies can elevate the patient experience, as an estimated 20% of all patient interactions will involve some form of AI enablement within clinical or nonclinical processes by 2023 (up from less than 4% today).¹ RPA can be a first step for healthcare companies to leverage AI within their organizations; however, it is critical to pick the right partner that understands your organization’s unique needs and strategic goals to have a successful RPA implementation. Because RPA replaces many manual processes, companies must commit to transformational change with both their people and processes to successfully reach their goals. Both now and in the future, RPA will continue to be an important element for healthcare organizations to sustain a strategic competitive advantage in the marketplace. n 1.

Gartner Inc., Authors. “Gartner Says 50% of U.S. Healthcare Providers Will Invest in RPA in the Next Three Years.” Gartner, 21 May 2020

2.

Davenport, Thomas H., and Rajeev Ronanki. “Artificial Intelligence for the Real World.” Harvard Business Review, 2018

3.

Lee, Bruce Y. “Doctors Wasting Over Two-Thirds Of Their Time Doing Paperwork.”

Forbes, Forbes Magazine, 11 Sept. 2016

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Beyond the New Normal

Digital health is emerging as a key differentiator within life sciences and healthcare organizations. Here are the key trends we see today:

CONNECTED PATIENTS

DATA INSIGHTS

FOCUS ON EXPERIENCE

Organizations are leveraging tools and services that patients use every day like wearables, virtual assistants, and social media platforms to create a connected ecosystem.

Patient Data, AI, and analytics seamlessly feed healthcare systems and inform decisions on drug development, all while increasing efficiency and reducing compliance tasks.

Organizations are shifting their focus toward communication, value, and convenience to improve engagement and outcomes for patients.

Healthcare is now digital.

Are you ready?

Slalom helps organizations build innovative strategies and solutions to advance digital health and improve patient experience.

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Slalom Point of View: Clinical Trials in 2021+

The Future of Clinical Trials is Accelerating Thanks to a Pandemic’s Worth of Attention JOHN PUGH

The COVID-19 pandemic has caused momentous change in the life sciences industry.

Several of these changes have been positive and will help shape our new health journey future:

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COLLIN BURDICK

Digital transformation has accelerated dramatically as lockdowns required the healthcare workforce to adopt and adapt to new tools.

Personalized and digitally supported therapies can be diagnosed, administered, managed, and monitored remotely without the need for in-person HCP visits.

A greater awareness has emerged around the need for faster, more-efficient clinical trials. A hallmark example is the fastest vaccine development and deployment in history. The speed, safety profile, and efficacy of not one, but three successful vaccines in under 1 year is a landmark shift for clinical trials.

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The Health Industry’s Clinical Trial Transformation Life Sciences, healthcare organizations, clinical research organizations, and many other health related bodies have come together to collaborate in an unprecedented manner.

Operation Warp Speed and the

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rapid development of Covid-19 vaccines set a high bar for R&D timeline expectations. These results are shifting the established timelines and expectations for drug development.

In January 2020, it was largely accepted as a necessary, if not required, fact that drug development would take 10–15 years. The pressure on pharma

organizations, both internally and externally, will be to start-up, run, and complete clinical trials faster. As a result, we will see an innovation explosion across all stages of the clinical trial process that will impact organizational structures, processes, technology, and patient expectations.

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Accelerating Study Start-Up Timeline reduction during the start-up phase is critical to shortening time-to-approval via reduced trial durations. Organizations will seek to reduce redundant activities by streamlining processes, becoming data-literate, and collaborating.

Already, organizations are seeking to digitize the traditionally labor-intensive protocol design process. Once digitization is made possible, study design data becomes liquid and will no longer be locked away in analogue, unusable study formats. Advanced AI may one day design protocols to achieve desired study endpoints by not only learning from previous successes and failures, but also with real-time patient population data, site burdens, molecule success probabilities, and life science company organizational capacity.

Modern, patient-centric, and cross-organizational operating models — supported by effective use of data and technology — will speed timely processes.

Using umbrella or basket trials can make better use of existing infrastructure, start-up, and team dynamics. Reducing the time between phases by utilizing AI or other machine learning techniques will result in a much faster speed to market for promising molecules. We will see far more post-marketing surveillance using remote technology to better aid in extremely targeted follow-up indications and safety data furthering efficient use of funds, data, time and investigator, government, and patient expectations.

Advanced AI may one

Patients, have historically been left out of protocol design. Protocols created without patient input only find errors and patient hardships once study recruitment is in progress — these errors may delay studies and put undue burden on patients. Slowly, this is changing where patient representatives or organizations are better collaborating with life science companies which has brought new ideas, perspectives, and recruitment networks to clinical studies.

day design protocols

Faster, more targeted, and site-complete patient recruitment is needed (37% of all sites under-enroll) The use of predictive technologies in demographic populations and a trusted data collaboration between health systems, governments, health authorities and life sciences companies will allow for more efficient and less burdensome trials across the industry.

previous successes

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to achieve desired study endpoints by not only learning from and failures, but also with real-time patient population data.

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Trial Diversity and Equal Representation There is increasing pressure and awareness that clinical trials need to reach more representative patient populations. Around 75% of clinical trials participants are white, yet over 40% of the (US) population are non-white.

Not to mention that rare and specialty diseases in many countries impact non-white populations disproportionately. Life sciences companies must intentionally ensure inclusive, diverse, and equitable (IDE) access and representation to trials.

Better awareness and education across a broad spectrum of socio-economic demographics is needed to break-down unapproachable scientific terminology. Funding for basic science and scientific method education has decreased in our underserved and public education populations compounding the learning curve at adulthood.

Utilizing new access points and expanding the use of independent sites will help remove some barriers for patient participation.

Independent sites are faster and closer to patient communities but are typically underfunded and in need of technology enablement.

Identifying diverse geographic areas for those sites will be critical. Democratizing sites across life science industry companies — versus several exclusive site contracts — is needed to ensure the most benefit for patients versus the most benefit for corporations. Supportive, but democratic regulation and collaborations are needed.

Clinical trial recruitment teams need to innovate around how they find, engage, and educate patients. Utilizing social channels (TikTok, Instagram, Spotify), search engines (Google, Bing), and targeted messaging platforms can reach previously unreached communities of people. Human-centric research techniques will help to gain

a deeper understanding the reasons for non-participation.

By using more advanced analytical technologies to compress the screening process, it will not only help to speed up the recruitment process but also identify critical diverse segments and target populations for clinical success.

Transformational Technology The capability to use technology in an agile manner will transform trial speed and effectiveness.

An adaptive technology stack — supported by democratized data — will help guide and in some cases save trials from failure.

The pandemic changed how trials are run out of necessity (twice as many CTs as normal were stopped due to the pandemic). Some trial teams quickly adapted such as one team which changed the patient requirement from driving 3 hours to a lab to drop off and review samples

Democratization of, and public access to clinical trial data remains a barrier to entry.

Modern and more accessible technology is needed to meet the minimum standards of accessibility.

Patient Recruitment Building off the need for IDE trials, patient recruitment remains a challenge in general.

Not only is it difficult to find and convince patients to join a trial, but increased competition across the life sciences industry has patients choosing between trials and life science companies fighting over the same patients.

Slalom Connect — Healthcare 2021

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to dropping off blood locally and reviewing over video call.

Technology connections across the end-to-end trial timeline will support parallel trial analysis, supportive patient health management and effective communications.

An adaptive technology stack will enable virtual trials. Imagine a data-only trial performed digitally and ad-hoc to find new indications or safety profiles.

Patients may find themselves with new treatments immediately available and the health system will not need to fund extraneous trial outcomes.

Better data capture and technology is needed across the trial spectrum to make this a reality, but it must also be coupled with regulatory support.

This will increase the need for more two-way communication between patients and trial investigators with more emphasis placed on the patient experience. By 2021, 40% of the top 100 life sciences companies will begin to implement digital trial pilot programs. Virtual clinical trials will place more pressure on organizations to adapt to new ways of working, to leverage new

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technologies and to deal with a proliferation of data and data sources. New governance structure will need to be established and supported by technology.

Proven increased evidence of the effectiveness of digital therapeutics will see an increase of use in clinical trials leading to an increased need for better and faster technology. As organizations understand and identify

By 2021, 40% of the top 100 life sciences companies will begin to implement digital trial pilot programs.

digital biomarkers, there will be an explosion of research into the topic. Already, the FDA has approved the first game-based digital therapeutic to improve attention function in children with ADHD. No pharmaceutical or molecule is needed for therapy as behavioral and neuroscience research and modern technology is better able to treat patients with long-term success.

Not More, But Better Data A consistent theme throughout clinical trial effectiveness and efficiency is data. Organizations in the clinical trial ecosystem have already invested into their data and analytical capabilities, but more is needed.

Effective and accessible data pipelines are not only difficult to build, but require constant investment to ensure interoperability between organizations, reusability, secure access, and reliability. Those organizations that have the luxury to pour significant investment into their master data, ingestion processes, data analysis, processing, machine learning / AI, external data set integration, and more

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will be the organizations that will gain a significant competitive advantage. Failure to do so will inevitably lead to dwindling pipelines and, ultimately, redundancy. Legacy, disconnected systems impact the entire clinical value chain from patients who want their data, to investigators burdensomely sifting through hundreds of separate data files, to life science companies hoping to extract move value and therapies. Compounding investment need is the lack of technical and data savvy clinical executives. Strong leadership with a focused and cascaded vision for technical perfection must be paired with the traditional need for clinical literacy.

for the market forces to uncover the best treatment options available. Already, several health organizations have data sharing - direct access, thirdparty for-profit companies (e.g., Flatiron), data purchase agreements in place to support data-driven insights. Targeted regulation to publicize clinical information so it may be accessed outside golden walls will help more nimble upstarts find new therapies or indications.

Collaborative data sharing agreements are critical to decentralized and utilitarian progress

Finally, a concept of patientowned-and-operated data is emerging to better allow

Any cornerstone to data-driven change is security and trust.

Health data is the most sensitive information for the vast majority.

Malicious actors have an easy path to profit given the sensitivity.

for individuals to opt-in or out of broad or targeted trial support. A growing demand from patients who want more access to their own data could have fundamental implications the way trial data is collected, stored and shared .

Technology to make this possible has emerged from the recent digital advertising regulations.

Blockchain and similar technologies may make it even easier to ensure secure, traceable, and compliant data ownership, sharing, and democratization.

Slalom is uniquely positioned to best support these future trends through our in-depth knowledge of the ecosystem coupled with our leading technology expertise. n

Did you know?

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Slalom is a purpose-driven consulting firm that helps companies solve business problems and build for the future. We’ll help you find your why, we’ll help you embrace change, and we’ll partner with you to design and build the solution that’s right for you.

Find out more at slalom.com

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100 BEST COMPANIES TO WORK FOR 2020 5 YEARS IN A ROW

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Promoting Diversity in Clinical Trials MEGHAN SOMMERKAMP

AUDRA BIEG

APRIL FERGUSON

The following article summarizes information from two Slalom Daily Dose articles in the Promoting Diversity in Clinical Trials Series: “One Size Doesn’t Fit All: The Current Demographics of Clinical Trial Participants” and “Strategies for Promoting Participant Diversity”.

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Slalom Connect — Healthcare 2021

The COVID-19 pandemic has given us many lessons about the U.S. Healthcare System. One lesson we’ve learned is that illnesses can have vastly different effects on segments of the U.S. population. Unfortunately, those segments of the population that are often most affected can also be the ones that are least represented in clinical trials for treatments combating those same illnesses. The health impact is that treatment outcomes observed in clinical trials cannot be generalized to the whole patient population. Potentially life-threatening outcomes or side effects unobserved in trials may be found in a broader patient population once a treatment has been approved. Oftentimes underrepresentation happens because of limitations in the study’s design and difficulty with recruiting and retaining participants and is not due to neglect by the study team. In this series, we’ll look into the current state of participant demographics in clinical trials and the importance of having representation from the potential patient population, what pharmaceutical companies can do to promote recruitment across diverse backgrounds, and how companies can work to understand the patient journey so that they can drive recruitment and retention from underrepresented populations.

According to the CDC (Center for Disease Control), there is increasing evidence that some racial and ethnic groups are being disproportionately affected by COVID-19. In a review of COVID-19-associated deaths reported to the National Vital Statistics System (NVSS) from May 1- August 31, 2020, the CDC reports that deaths among the Black population accounted for 18.7% of overall COVID-19 deaths despite representing just 12.5% of the U.S. population.

Similarly, deaths among the Hispanic population accounted for 24.2% of all deaths, even though Hispanics represent 18.5% of the U.S. population. Inequities in social determinants of health can lead to increased risk for COVID-19

Slalom Connect — Healthcare 2021

exposure among some racial and ethnic groups.

For example, people from underrepresented racial and ethnic groups might be more likely to live in multifamily households, reside in congregate living environments, hold jobs requiring in-person work, have limited access to healthcare, or experience discrimination. Finally, the differences in prevalence of underlying conditions among racial and ethnic groups might also be associated with increased vulnerability to COVID-19 associated complications and death.¹ The different health outcomes of COVID-19 highlight the need for pharmaceutical companies and research sponsors to assure that clinical trial participants represent the potential patient population. Similar to the different effects illnesses can have on patient populations, vaccines and treatments may also have various outcomes and side effects depending on the patient population. It is important to understand the variety of these outcomes because a treatment may have a favorable result in one population but may not have that same result in another population.

Unfortunately, minority populations are still underrepresented in clinical trials which could have a negative impact on the overall safety and efficacy of pharmaceutical products.

So, what can pharmaceutical companies and research sponsors do to promote diversity and increase enrollment of underrepresented populations in their clinical trials?

Strategies that pharmaceutical companies and research sponsors are taking in order to promote diversity in their clinical trials include: 1. Expand eligibility criteria and re-think recruitment tactics 2. Incorporate the patient’s perspective 3. Establish trust with participants and the communities where they live

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Expand eligibility criteria and re-think recruitment tactics: This past November, the FDA issued guidance on how to design and execute clinical trials that include participants with various demographic characteristics (i.e. age, sex, race, ethnicity, and location of residence) and non-demographic characteristics (i.e. patients with organ dysfunction, comorbidities and disabilities, those at weight range extremes, and populations with diseases or conditions with low prevalence). To promote inclusive trial practices, the FDA recommends that eligibility criteria serve the goal of having a representative sample of the population for whom the drug has been developed. Participants who reflect the characteristics of clinically relevant populations should be enrolled in trials.2 For instance, if you’re developing a treatment for diabetes, then you should be aware that the Hispanic population is 50% more likely to die from diabetes than the Caucasian population.

Therefore, the study population for this treatment should be represented by Hispanic participants.3 Simply expanding participant eligibility will not guarantee that research sponsors will be able to recruit more inclusive populations. In the example about clinical trials for diabetes treatment, in addition to expanding eligibility, it would also be beneficial to include a Spanish version of the consent form in order to recruit a higher number of Hispanic participants. An accompanying strategy that we recommend is analyzing your informed consent process to help increase participant recruitment. The informed consent process has become increasingly complex and difficult for participants to understand regardless of whether or not they are fluent in the consent form’s language. Moving from paper-based informed consent documentation to e-consent can help participants better understand the study’s objectives and expectations through their preferred learning style. E-consent is more than just converting the consent form to a digital version. It includes multimedia components (i.e. audio, video, diagrams, etc.) which can be used to develop an interactive and engaging informed consent experience for the participant.

Data from e-consent pilots through TransCelerate suggest that participants prefer on-demand access and multimedia content through the web

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or mobile device over paper.4 Additional recruitment tactics that we recommend are incorporating the participant’s perspective and establishing trust with participants which we will talk about next.

Incorporate the patient’s perspective: Incorporating the patient’s perspective in clinical research is critical to ensure that the measured outcomes reflect those that matter most to patients. Discrepancies exist between physicians’, sponsors’, and patients’ assessments of their disease, treatment preferences, decision-making factors, and thresholds to change treatment plans. These discrepancies highlight the importance of understanding and including the patient’s perspective. Additionally, patients from underrepresented groups have different needs, perspectives, and experiences than those who are from highly represented groups.

Involving patients in the planning and execution of clinical trials can give research teams insights into what it is like living with a particular diagnosis as well as the challenges faced with receiving care and treatment. Establishing a patient advisory board provides a go-to resource for study teams to receive support with clinical trial design and execution. Study teams can consult the patient advisory board on numerous patient-related topics regarding recruitment strategies, surveys designs, educational content, and participant retention.

Participating in a clinical trial can be demanding for patients and providing affordances is a way to ease those demands.

Slalom Connect — Healthcare 2021

Providing relevant affordances to patients can also be a helpful technique to engage more diverse and underrepresented populations. For instance, patients who live in rural areas could benefit from receiving transportation services so that they can travel to study sites. Patients who have children may benefit from receiving childcare so that they can take time away from their family to participate in a study. Low income populations may benefit from monetary affordances for their time and potential lost income for stepping away from work. Participating in a clinical trial can be demanding for patients and providing affordances is a way to ease those demands.

Having early discussions with patients about clinical trial expectations and spending time talking to patients about the study can go a long way.

Patients must first process the news of being diagnosed with a severe or life changing/life threatening condition before they can engage in any decision-making activities. Simply spending time with patients shows them that they are being cared for and that they matter. It also gives them time to ask questions, process the information they are receiving, and make an informed decision about their health. When patients understand the benefits of trials, they are more likely to become a participant and to remain on the trial.5

Establish trust with participants and the communities they live: Finally, participants from underrepresented populations may lack experience or knowledge about medical research as well as have beliefs and

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practices that may contrast with some aspects of the study design. Therefore, they may be unaware of a trial’s existence and once they become aware, they may be more apprehensive to participate.

In a survey of general U.S. consumers conducted

by Par8o, 56% of survey respondents think that a healthcare provider they already know would be the most trustworthy source to learn about a potential clinical trial.6 Community Health Centers which are located in medically underserved areas in lower income rural and inner-city communities are integral for establishing trust with patients because they are often at the center of the community, becoming entwined with their neighborhoods they provide care for.7 Engaging with a community’s health center early on in clinical trial development gives the community health center time to educate their staff on the study as well as strategize on how to engage with target patients amid their busy patient visit schedules. The community health center staff can then effectively educate their patients, fostering trust within the greater community.

With the rapid development of the COVID-19 vaccine, pharmaceutical companies are now under pressure to complete the research, development, and clinical trial stages of drug development quicker than ever before. It is critical that as drug development timelines are shortened, pharmaceutical companies and research sponsors are spending their time wisely by expanding participation in clinical trials. From both a safety and efficacy standpoint, as well as for the health of all patients, it is important that racial, ethnic, and socioeconomic minorities are increasingly recruited and retained in clinical trials. n

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WHY

Robots & AI NEED TO PLAY TO BE MORE IMPACTFUL IN HEALTHCARE ELAINE CHUNG

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MICHELLE YI

Slalom Connect — Healthcare 2021

A Connected World Today we live with and are surrounded by many connected devices, including devices that monitor our health and wellness, but when we take a close look at HOW it’s accomplishing this, there is a common theme: devices are learning and monitoring one specific aspect — expertise.

Take arrhythmia detection as an example. While arrhythmia detection is still largely completed through ECG, there is a growing application for artificial intelligence learning models in this detection. These models are able to predict arrhythmias based on a deep ECG dataset on specific arrhythmias. However, even with this advancement, a more integrated and broader picture of detecting other potential cardiac issues is still missing, and it doesn’t take much of a stretch to see how much more beneficial to patients and healthcare systems this could be.

Artificial intelligence is an increasingly present part of our lives, especially with the digital shift to and reliance on digital systems resulting from COVID-19 and resulting precautions from gathering, as well as new developments in technology.

However, artificial intelligence today is far from the artificial generalized intelligence (AGI) capable of completely mimicking the human decision-making process on its own. In fact, the developments of today are still largely reliant on humans and are better at tackling very specific, well-defined tasks with a lot of data as in the example above.

Recently, Dr. Chelsea Finn of Stanford spoke about the connection of advancing AI/ML learning through training them how to learn like toddlers. What’s so compelling and albeit pretty amazing is that play is a child’s way of active and impressive learning.

Therefore, it makes complete sense that play would help in learning within this capacity. As we further develop smarter algorithms to do more generalizable tasks through independent learning, the only way we’ll get there is through advancing the richness of their data, increasing the data distributions that they are learning and the method in which they learn implicitly. For us to understand why learning like toddlers do, through play, supplies a rich learning process, we need to break down what’s going on with brain development for toddlers.

Neuroscience and Play Now, it’s important to understand what’s going on in toddlers. During this stage of development, their brain growth is immense. During these first few years, more than 1 million neuronic connections are formed each second! When this stage ends, there is a process called pruning, which ends up eliminating connections or pathways that aren’t used.1 Their brains (and they) are wideeyed explorers, taking in each input from sound, touch, taste and experimentation. They are also observing and modeling what they see, whether it be from adults around them or the family dog.

Play enables them to explore through these senses and also test their own reactions. Learning through these experiences is how their brain continues to form the additional neuronal connections and decides which connections to strengthen and prune. It’s these connections that enable children to create solutions in novel situations.

Play is a way children learn and test their own knowledge on limited sets of data. Take a

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two-year-old playing with blocks for the first time, for example. Even through playing with blocks, they are starting with their little-known universe and applying it to additional exploration. If they are playing with blocks, they are exploring textures (does this feel similar to what I have felt beforesoft like a blanket? Hard like the floor?) and even what additional properties it may have (Can I stack this like I may have done before? Does it have a shape that I have seen before-like a train?). They are drawing these parallels and experimenting with limited knowledge. This is why we are never surprised when a block suddenly turns into a car as easily as it becomes a house. Through simply playing with blocks, they are also increasing their understanding counting concepts, groupings, and creating and examining patterns. From physics concepts to team work in group situations, play is a mechanism for minds to continuously gathering inputs, reorganizing them and reapplying them in a variety of situations.

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Importance of Increasing Data Distribution Being able to increase data distributions despite limited datasets, as Dr. Finn’s study showed, by incorporating how children play and learn into algorithm development can help us address some of the current challenges in artificial intelligence in healthcare and beyond. In particular, there are three areas where incorporating the way children learn can help us improve.

These three challenges share a primary root cause: lack of relevant data distributions. By mimicking and learning how children broaden their knowledge of the world through play and creating “features” and connections despite limited data (e.g. blocks), there is a significant opportunity to advance the inherent challenges in today’s AI methods and applications in healthcare.

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Narrow versus broad application Today, our algorithms require a significant amount of data on a very specific area to be effective. Anything outside of the application for which the algorithm was trained, or any nuanced cases that do not look like any of the data points it was trained on, may result in a false positive or missed opportunity. In Healthcare, these false positives can have severe ramifications. As we move toward integrative medicine and more holistic analyses that require us to be able to make broader inferences across a generalized population using multiple datasets (e.g. genomic, medical images, activity monitoring), having a better understanding of many diverse data types will be key to driving effective AI-embedded decision support tools that benefit all.

Slalom Connect — Healthcare 2021

Bias

Small data

Recent developments have shown significant bias embedded within AI-systems in the arena of facial recognition specifically. This kind of bias can manifest in any area where we may not have diverse distributions of data or representation, resulting in systematized bias. In healthcare applications across telehealth, clinical trial support, medical devices, and others, it is critical to consider ways to increase data distributions in multiple ways (e.g. recruitment, public data, new features based on existing data, etc.) to reduce the chances of systematizing bias.

There are some problems like rare diseases in medicine that are inherently small data problems, which are not ideal for the types of algorithms and techniques available today. Achieving good data distributions can be challenging in these scenarios, but there are advances in GANs and engineering data for GANs that leverage the creativity of AI to either create realistic synthetic data or to engineer existing data in a new way that reduces the amount of training data needed significantly . Some of these advances closely emulates how human children learn from limited datasets.

Opportunities for the Future Now, let’s re-examine our earlier example of arrhythmia detection. If we layer in a greater data distribution of ECG, we could get to a point where we could also be detecting multiple other cardiac issues, such as other heart defects, heart enlargement, ischemia, etc. through that broader batch of data versus training for each specific disease.

Increasing this distribution can unlock the potential of AI in holistic, personalized healthcare.

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The journey of achieving artificial generalized intelligence ironically starts with an understanding of ourselves, how we learn and play. And if we can unlock this, it is possible for us to not only develop better technology to augment our lives, but also to fully understand ourselves. n

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