BFAM Member Spotlights

Meet the members of the Stanford Medicine Black Faculty Affinity Meetings (BFAM), a network created through OFDD's Community Support Initiative. BFAM is intended to provide networking and social engagement opportunities for Stanford Medicine faculty across all clinical lines and departments.

Alyce S. Adams, PhD

Epidemiology and Population Health & Medicine (PCOR)

Associate Director, Health Equity and Community Engagement, Stanford Cancer Institute

Faculty Advisory Board, Stanford Impact Labs

Research Interests
Health services and policy research; Health Equity; Chronic Disease Treatment & Outcomes

Something you wouldn’t know just by looking at me.
I was in a rock band in graduate school.

What are some of your favorite restaurants?
Chez Maman, Chubby Noodle

What are some of your favorite social activities?
Finding new restaurants; sporting events (Warriors, Giants); symphony

Full Stanford Profile

Stanford Medicine Innovation Professor and Professor of Epidemiology and Population Health, of Health Policy and, by courtesy, of Pediatrics (Endocrinology)

asadams@stanford.edu

Bio

Dr. Adams is the inaugural Stanford Medicine Innovation Professor and Professor of Epidemiology and Population Health and of Medicine (Primary Care and Outcomes Research), as well as Associate Director for Health Equity and Community Engagement in the Stanford Cancer Institute. Focusing on racial and socioeconomic disparities in chronic disease treatment outcomes, Dr. Adams' interdisciplinary research seeks to evaluate the impact of changes in drug coverage policy on access to essential medications, understand the drivers of disparities in treatment adherence among insured populations, and test strategies for maximizing the benefits of treatment outcomes while minimizing harms through informed decision-making. Prior to joining Stanford School of Medicine, Dr. Adams was Associate Director for Health Care Delivery and Policy and a Research Scientist at the Kaiser Permanente Division of Research, as well as a Professor at the Bernard J. Tyson Kaiser Permanente School of Medicine. From 2000 to 2008, she was an Assistant Professor in the Department of Population Medicine (formerly Ambulatory Care and Prevention) at Harvard Medical School and Harvard Pilgrim Health care. She received her PhD in Health Policy and an MPP in Social Policy from Harvard University. She is Vice Chair of the Board of Directors for AcademyHealth and a former recipient of the John M. Eisenberg Excellence in Mentoring Award from Agency for Healthcare Research and Quality and an invited lecturer on racial disparities in health care in the 2014/2015 National Institute of Mental Health Director’s Innovation Speaker Series.

Publications

Identifying Predictors of Homelessness Among Adults in a Large Integrated Health System in Northern California. The Permanente journal Rodriguez, L. A., Thomas, T. W., Finertie, H., Wiley, D., Dyer, W. T., Sanchez, P. E., Yassin, M., Banerjee, S., Adams, A., Schmittdiel, J. A. 2023: 1-16 More

Abstract

Introduction Homelessness contributes to worsening health and increased health care costs. There is little published research that leverages rich electronic health record (EHR) data to predict future homelessness risk and inform interventions to address it. The authors' objective was to develop a model for predicting future homelessness using individual EHR and geographic data covariates. Methods This retrospective cohort study included 2,543,504 adult members (≥ 18 years old) from Kaiser Permanente Northern California and evaluated which covariates predicted a composite outcome of homelessness status (hospital discharge documentation of a homeless patient, medical diagnosis of homelessness, approved medical financial assistance application for homelessness, and/or "homeless/shelter" in address name). The predictors were measured in 2018-2019 and included prior diagnoses and demographic and geographic data. The outcome was measured in 2020. The cohort was split (70:30) into a derivation and validation set, and logistic regression was used to model the outcome. Results Homelessness prevalence was 0.35% in the overall sample. The final logistic regression model included 26 prior diagnoses, demographic, and geographic-level predictors. The regression model using the validation set had moderate sensitivity (80.4%) and specificity (83.2%) for predicting future cases of homelessness and achieved excellent classification properties (area under the curve of 0.891 [95% confidence interval = 0.884-0.897]). Discussion This prediction model can be used as an initial triage step to enhance screening and referral tools for identifying and addressing homelessness, which can improve health and reduce health care costs. Conclusions EHR data can be used to predict chance of homelessness at a population health level.

View details for DOI 10.7812/TPP/22.096

View details for PubMedID 36911893
Charting the Course Toward More Equitable Health Care Systems. Medical care Adams, A. S. 2023; 61 (1): 1-2 More

View details for DOI 10.1097/MLR.0000000000001796

View details for PubMedID 36477615
The Impact of Financial Assistance Programs on Health Care Utilization: Evidence from Kaiser Permanente AMERICAN ECONOMIC REVIEW-INSIGHTS Adams, A., Kluender, R., Mahoney, N., Wang, J., Wong, F., Yin, W. 2022; 4 (3): 389-407 More

View details for DOI 10.1257/aeri.20210515

View details for Web of Science ID 000863320000008
Address Changes Are Associated With Unmet Glycemic Targets: Opportunities to Improve Processes and Outcomes of Care Among People With Type 2 Diabetes. The Permanente journal Thomas, T., Dyer, W., Adams, A., Grant, R., Schmittdiel, J. 2022; 26 (2): 1-10 More

Abstract

Introduction The objective of this study was to identify and operationalize measures of potential housing insecurity within existing electronic health record data and to quantify the association between address changes and diabetes management goals among patients with type 2 diabetes. Methods We conducted a retrospective cohort study to measure potential housing insecurity in electronic health record data by quantifying the number of address changes in 2018. We considered at least one address change as a potential marker for housing insecurity. We used multivariable modified Poisson regressions to analyze the association between address change and clinical, utilization and preventive care outcomes while adjusting for patient and health system factors. Results We identified 274,123 adults with type 2 diabetes who were members of Kaiser Permanente Northern California in 2018 and 6% (N = 17,317) had at least one address change during 2018. In multivariate analyses, we found that one or more address changes was associated with greater chance of hemoglobin A1C < 9 (ARR: 1.12, 95% CI: 1.09, 1.15), lower chance of hemoglobin A1C < 8 (ARR: 0.95, 95% CI; 0.94, 0.96), lower chance of controlled blood pressure (ARR: 0.99, 95% CI: 0.98-0.99), greater chance of emergency department visits (ARR: 1.25, 95% CI: 1.23, 1.27), and lower chance of having a flu shot (ARR: 0.94, 95% CI: 0.93, 0.95) when compared to no address change. Discussion Changes in address are associated with worse diabetes management outcomes. Conclusion Identifying patients with potential housing insecurity and providing resources aimed at continuity of care and stable health care access could improve diabetes management for vulnerable populations.

View details for DOI 10.7812/TPP/21.144

View details for PubMedID 35933662
Glycaemic control over multiple decades and dementia risk in people with type 2 diabetes Moran, C., Lacy, M., Whitmer, R., Tsai, A., Quesenberry, C., Karter, A., Adams, A., Gilsanz, P. WILEY. 2022: 20 More

View details for Web of Science ID 000806995200034

see all 108 publications

BFAM Member Spotlights

Alyce S. Adams, PhD

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