Changing the Game: Digital Solutions in Healthcare
By Yechan Kang and Leah Strickling
Every major life science conference we attend now has a digital health track, as this broad and evolving field and everything it encompasses continues to grab industry attention. The BIO International Convention, which wrapped up last week in Philly expanded its digital health sessions and reported that every pharmaceutical company exhibiting has a digital health initiative.
Back Bay’s industry analysts are watching a number of different areas where we think there will be significant movement, including applications of data and digital health to pharmaceuticals and medical devices, and the potential of digital health in emergent care situations, which we will examine and release via a new white paper this fall (request a copy here).
We’re most interested in real-world solutions to improve patient care—particularly the promise of AI to bring treatments to patients more quickly and less expensively.
At this year’s annual conference of the Healthcare Information and Management Systems Society (HIMSS), several trends rose to the top which we continue to track across the year’s significant biopharma and healthcare conferences, including ASCO and BIO International. These trends encompass all aspects of healthcare and span academic institutions, startups, and large corporations and include to promise of AI/machine learning to:
Lessen physician burnout – With physician burnout in the United States reported to contribute up to ~$4.6 billion lost dollarseach year, it is among healthcare’s most significant issues. To bring attention to this phenomenon, the WHO will update its definition of burnout in their 11th version of the International Statistical Classification of Disease and Related Health Problems (ICD-11), with the new definition characterizing it as an occupational phenomenon influencing an individual’s health status and “professional efficacy.”
With more than half of physicians in the US reporting symptoms of physician burnout, we’re looking to digital health to help alleviate the burden and prevent dissociation with patients.
AI-powered assistants, such as the one developed by Suki, may decrease burden by reducing EHR input errors, automating menial tasks in the exam room, and allowing doctors to focus more time on their patients rather than keying information into a computer.
Suki, the “Alexa for doctors,” is voice-enabled and personalized to each doctor that is continually learning and improving. The goal of this digital technology is to be “invisible and assistive,” taking notes during each patient visit and integrating with the EHRs to lighten the overall load of physicians in the clinical setting.
Speed up diagnoses—A team of pathologists at Mount Sinai, Los Angeles, developed an AI platform used to more efficiently and accurately identify different disease states. The technology is currently available to select pathologists across the country who have experience with machine learning. The physicians are involved in uploading images of slides containing tissue specimens from patients with different diseases to an aggregated library within the platform, as well as programming the platform to recognize specific disease states so that the platform can quickly and accurately aid in the identification of diseases when new images are uploaded.
This type of platform uses AI to analyze and quickly and accurately identify different disease states through reproducible pattern recognition, which could aid in faster diagnoses and earlier treatment for patients.
The limited number of pathologists with computer science capabilities and familiarity with digital pathology poses a significant barrier to uptake. As more pathologists become familiar with the platform, the library will continue to grow and allow for faster and more accurate recognition of diseases using the platform’s machine learning capabilities.
Expand healthcare access – As the US healthcare system continues to move towards a value-based model, incentivizing positive outcomes over fee-for-service, closing the gap on social determinants of health—which the World Health Organization defines as “the conditions in which people are born, grow, live, and age”—have become a critical component of this effort.
One area in which companies are aiming to “close the gap” is addressing the lack of reliable transportation, a barrier that impacts up to 3.6 million Americans each year and leads to delayed or missed medical appointments.
Lyft, a ride-sharing service, recently allied with Blue Cross Blue Shield (BCBS) to improve patient care and health equity by providing access to healthcare in areas with transportation deserts.
Under the partnership, BCBS utilizes Lyft’s ride services to provide healthcare access for its members who do not have access to transportation. According to Lyft’s Impact Report, 28% of healthcare riders indicate that they would have been less likely to make their appointments without Lyft, and 36% indicate that reliable transportation to appointments reduced their utilization of urgent care. Building upon the early success of its program, the partnership was expanded to offer non-emergency transportation (NEMT) to Medicare Advantage members in February 2019.
BCBS claims that social determinants of health drive ~80% of health outcomes as differences in political, cultural, environmental, and economic backgrounds can result in health inequities and societal stratification. Companies like Lyft (and Uber, which offers a similar service via Uber Health) have the potential to leverage their technology and innovation to close the gap in social determinants of health and improve access to healthcare.
Share data beyond organization walls – With the 2018 acquisition of PillPack online pharmacy, Amazon turned industry heads and created new thinking around access to medication. Amazon recently unveiled Haven, a not-for-profit joint venture with Berkshire Hathaway and JP Morgan Chase, with the mission of lowering the cost of healthcare in the United States. Amazon has clear intentions of becoming a significant player in the healthcare space, and in addition to disrupting pharmacy distribution and improving healthcare access, the company is leveraging its cloud-computing platform, Amazon Web Services (AWS), to tackle another challenge in the field – healthcare interoperability.
Using digital innovations to coordinate and connect across organizations to improve healthcare means massive amounts of healthcare data can be put to good use to improve the health of individuals and populations. The increasing availability of healthcare data has generated a widespread push for interoperability to exchange data efficiently and cohesively that is often siloed or disjointed among hospitals, pharmacies, laboratories, and patients. The promise of interoperability in healthcare can facilitate the integration of data across different systems to provide seamless access and a comprehensive understanding of individuals and populations to optimize patient care and outcomes. While interoperability remains a challenge, and institutions will need to address issues regarding data privacy, the rise of cloud-computing services like AWS, which provides high-performance computing, analytical tools powered by artificial intelligence, and storage capabilities, has enabled government organizations, healthcare groups, and industry to build towards a healthcare interoperability ecosystem.
Digital health continues to enthrall and shape the healthcare industry. Those of us helping to inspire the next generation of life science companies are eager to identify issues in the field and create solutions. Now more than 60 years old, AI and machine learning are no longer new concepts, but experts believe that we’re at an inflection point with the convergence of deep learning, high-performance computing, a wealth of healthcare data, and bottomless data storage.
As the field evolves, there will certainly be increased scrutiny to address issues, such as data privacy and corporate responsibility. However, the potential is evident for AI in the near term to equalize access to healthcare, ease physician burnout, speed diagnosis, and bring much-needed treatments to the broadest patient populations regardless of socioeconomic determinants.