Alyce Adams, PhD, is Associate Director of the Health Care Delivery and Policy section of the Division of Research. Her own research examines barriers to adherence to chronic disease medications among vulnerable patient populations and ways to mitigate them at the health system and policy level.
Q: If you had to think back, is there a single moment in your life that sparked your interest in what you’re doing now?
My interest in research goes back to spending time with my grandparents and other older relatives. They had severe disabilities related to diabetes and hypertension, such as lower leg amputation and blindness. Yet, they also had health insurance. I found it troubling that patients who had access to reasonably good quality of care had such terrible and avoidable outcomes. This is what led to my focus on understanding the modifiable drivers of disparities in chronic disease outcomes.
Q: What do you see as some of the barriers to delivering health care?
Barriers to delivering health care appear at all levels, from patients, such as the ability to afford services, health literacy and language barriers; and providers, including having the time to attend to complex patient needs; and the health care system, such as workflows and regulatory constraints; and the policy level, like changes in coverage.
Q: What kind of research are you doing and why do you think it’s important?
It’s estimated that nonadherence to clinically effective medications to treat chronic conditions such as diabetes, hypertension and depression costs the U.S. an estimated $300 billion each year in avoidable health care costs. Persistent racial and ethnic disparities in adherence are not only a moral and social justice issue but a financial one. This is what drives my research and why I think the underuse of potentially life-saving medications among vulnerable patients is such a critical issue in health care delivery.
I am increasingly drawn to rapid-cycle analysis of electronic health data, interventions, and the use of machine learning to predict the impact of changes in care delivery and policy across these vulnerable subgroups. Advances in electronic health record data and technology, such as machine learning, have made it possible to generate evidence in a timelier way while still employing rigorous research methods. It’s amazing to be a researcher in this day and age where we are not nearly as constrained by technology and data availability.
However, these strategies are only meaningful if they also surface contextual factors that explain what we see in the data and engage patients, clinicians and health system leaders so that our findings can improve patient care outcomes.
Q: In your free time, what do you like to do?
In my spare time, my husband and I like to explore new restaurants in the San Francisco area and spend time with our large family. We also spend a lot of time exploring the area parks with our dog.
Q: You focus much of your work on patients with diabetes. What has surprised you in what you’ve found?
I am always amazed by the resilience of patients and by their interest in research. They are the motivation for what we do!