About

Jaya Aysola, MD, DTMH, MPH, is an Associate Professor of Medicine (General Internal Medicine) at the Hospital of the University of Pennsylvania. She is a faculty affiliate at the Center for Health Incentives and Behavioral Economics and a senior fellow at the Leonard Davis Institute of Health Economics, both at the University of Pennsylvania. Dr. Aysola serves as the Executive Director of the Penn Medicine Center for Health Equity Advancement within the Office of the Chief Medical Officer at the University of Pennsylvania Health System. Her professional interests include health equity, cultural humility, implicit bias, health services research, and health policy. Her research focuses on health disparities, patient-centered care, social determinants of health, access to care, and issues related to race and structural racism. She is actively involved in community outreach, education, and organizational efforts aimed at promoting health equity and addressing social determinants impacting healthcare delivery.

Research topics

• Medicine
• Medical education
• Psychology
• Law
• Political Science
• Family medicine
• Management
• Gender studies
• Engineering

Selected publications

• Characteristics Associated With Community Violence Prevention Programs in <scp>US</scp> Hospitals: A Cross‐Sectional Survey Analysis

  Academic Emergency Medicine · 2026-04-01

  articleOpen access

  BACKGROUND: Violence is a social determinant of health, and hospitals are well-positioned to promote patient well-being by addressing its root causes. Understanding factors associated with hospital engagement in community violence prevention can guide intervention development and capacity building. OBJECTIVE: To examine hospital and county-level factors associated with the presence of community violence prevention programs (CVPPs) in U.S. hospitals. METHODS: This cross-sectional study linked data from the 2022 American Hospital Association Annual Survey with county-level socioeconomic and demographic data from the US Census Bureau and all-cause homicide rates from the US Centers for Disease Control and Prevention. The sample included general medical and surgical hospitals with Medicare identification numbers. Survey-adjusted logistic regression assessed associations between hospital CVPP presence and all-cause homicide. Our response variable was whether or not the hospital had a CVPP, and our explanatory variable was county-level all-cause homicide rates. We adjusted for hospital characteristics and county-level socio-demographics. RESULTS: Of 4,374 hospitals, 990 (22.6%) reported having CVPPs. Compared to those without CVPPs, hospitals with CVPPs were more likely to be nonprofit (85.0% vs. 62.9%), large (> 500 beds; 16.9% vs. 4.7%), have more annual ED visits (51,873.9 vs. 26,224.5), and be urban (81.1% vs. 51.8%) (all p < 0.001). They also more frequently offered outpatient psychiatric (86.1% vs. 46.9%), substance use (74.4% vs. 23.2%), and pain management (93.1% vs. 65.2%) services. In adjusted models, homicide rates were not associated with CVPP presence (aOR = 1.01, 95% CI [0.99, 1.04]). CVPP presence was independently associated with nonprofit ownership, larger size, trauma designation, and lower social deprivation in urban counties. CONCLUSIONS: Hospital and community characteristics, rather than homicide rates, predict CVPP presence. CVPPs are concentrated in larger, urban, well-resourced hospitals rather than in areas with the highest homicide rates, highlighting potential misalignment between program placement and community need.

  PublisherOA PDFDOI

• The Benefit of the Doubt Phenomenon in Emergency Triage Assignment Disparities

  medRxiv · 2026-02-14

  articleOpen access

  Emergency department (ED) triage decisions critically impact patient care and are standardized, yet ethnoracial disparities in triage assignment are well documented. We analyzed ethnoracial differences in triage assignments across four U.S. EDs (two adult, two pediatric), comprising 1.4 million encounters from 2011-2025. To better characterize these disparities, we developed an automated triage algorithm that replicates the Emergency Severity Index (ESI) criteria, the standard triage protocol used at each site. The algorithm identifies high-acuity symptoms and danger-zone vital signs that inform triage decisions at the level-2 (emergent) versus level-3 (urgent) boundary. We compared nurse triage assignments across ethnoracial groups, stratified by algorithmic ESI scores, using causal inference methods to adjust for clinical presentation and hospital context. Significant ethnoracial disparities in triage assignment were observed across all sites. Disparities were concentrated among patients algorithmically classified as lower risk but assigned higher acuity by nurses. This pattern is consistent with a "benefit-of-the-doubt" disparity, in which relatively stable, non-Hispanic White patients are more often assigned higher priority than Hispanic and non-Hispanic Black patients with comparable presentations. By contrast, disparities were attenuated or absent among patients deemed high risk by both nurses and the algorithm. Finally, analysis of the projected length-of-stay impact of substituting nurse-assigned with algorithmic triage scores suggests that algorithmic ESI decision support could reduce triage disparities with minimal effects on patient flow.

  PublisherOA PDFDOI

• Racial and Ethnic Disparities in Inpatient Palliative Care Consults in the US: A Systematic Review and Meta-Analysis

  Journal of Pain and Symptom Management · 2026-05-12

  article
  PublisherDOI

• Penn, Social Systems, and the Community: fostering equity-focused public health practice through asynchronous learning

  Frontiers in Public Health · 2026-02-11

  articleOpen access

  Penn, Social Systems, and the Community (PSSTC) is a semester-long, non-credit, asynchronous course designed to prepare the University of Pennsylvania (UPenn) Master of Public Health (MPH) students for community engagement by analyzing how historical and systemic inequities impact public health. As a prerequisite for the Applied Practice Experience (APE), PSSTC addresses a key pedagogical challenge in public health education: providing foundational training on structural inequalities and their influence on public health practice. The curriculum includes nine online modules and four synchronous discussions covering topics such as racism and other forms of oppression, social determinants of health, implicit bias and microaggressions, transformative justice, and the role of UPenn itself in these broader systems. A post-course survey was administered and respondents agreed that the course prepared them for the applied practice experience and other public health work. Students also reported gaining knowledge and practical strategies for working with diverse populations. Suggested improvements included condensing content for more focused learning and incorporating broader perspectives from underrepresented racial, ethnic, and religious populations. In response, course revisions are ongoing to streamline content and ensure alignment with the evolving public health landscape.

  PublisherOA PDFDOI

• Prevalence and Treatment of Anxiety and Depression Among US Healthcare Workers, 2021–2024

  Journal of General Internal Medicine · 2026-05-11

  articleOpen access

  BACKGROUND: Healthcare workers (HCWs) face high levels of psychological distress due to workplace stressors, but there is a paucity of evidence on the prevalence and treatment of anxiety and depression among HCWs. OBJECTIVE: To examine the prevalence and treatment of self-reported anxiety and depression among HCWs. DESIGN: Retrospective cross-sectional study using nationally representative data from the 2021-2024 National Health Interview Survey (NHIS). PARTICIPANTS: 76,800 adults aged 18-64 years old. EXPOSURE: The primary exposure was HCW status, categorized by self-report. MAIN MEASURES: The primary outcomes were self-reported anxiety and depression. The secondary outcome was self-reported untreated anxiety or depression. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression models. KEY RESULTS: Among 76,800 participants (59.0% aged 18-44, 50.4% female, and 58.9% non-Hispanic White), self-reported anxiety (23.3% vs 19.1%, p < 0.001) and depression (22.3% vs 18.9%, p < 0.001) were more common among HCWs than non-HCWs. Among individuals with self-reported anxiety or depression, HCWs were more likely to report untreated anxiety (72.1% vs 64.9%, p < 0.001) and untreated depression (67.2% vs 60.7%, p < 0.001), respectively. Anxiety and depression increased from 2021-2024 for HCWs (both p < 0.001). In multivariate regression, compared with non-HCWs, HCWs had higher odds of self-reported anxiety (OR: 1.21, 95% CI: 1.12-1.31) and depression (OR: 1.20, 95% CI: 1.11-1.29). HCWs had increased odds of self-reported untreated anxiety (OR: 1.28, 95% CI: 1.12-1.46) and depression (OR: 1.25, 95% CI: 1.10-1.42) among adults with self-reported anxiety or depression, respectively. CONCLUSIONS: In this study, HCW status was associated with self-reported anxiety and depression, as well as lower rates of treatment. The prevalence of anxiety and depression significantly increased over the study period. These findings underscore the importance of structural interventions in protecting the mental well-being of the healthcare workforce.

  PublisherOA PDFDOI

• Perceptions of Culturally Responsive Care Among People With Disabilities

  Annals of Internal Medicine · 2025-03-03 · 5 citations

  articleSenior author
  PublisherDOI

• Synthetic data and health equity: accounting for racism and sexism in health care delivery

  Health Affairs Scholar · 2025-08-18

  articleOpen accessSenior author

  Introduction: Synthetic data are a promising new tool for answering health service research questions, including those relevant to health equity. However, it is unclear whether synthetic data can accurately capture inequities in health care, which may perpetuate racial and ethnic health inequities when applied to the real world. Methods: In this study, we determine to what extent Synthea, a popular open-source synthetic electronic health record data generator captures racial, ethnic, and sex disparities in clinical practice and evaluate whether the data can be augmented by other publicly available data sources. We examine rates of intervention for 3 common medical conditions-myocardial infarction, chronic obstructive pulmonary disease, and type II diabetes mellitus. Results: For 2 of the 3 conditions, Synthea data showed higher rates of intervention for all patients and attenuated or no disparities in intervention, vs comparator literature. After incorporating data on race, ethnicity, and sex disparities from the Dartmouth Atlas, updated Synthea proportions approached their literature counterparts in both absolute and relative terms. Conclusion: If using synthetic data, researchers and policymakers can work to ensure such data accurately reflect downstream effects of social forces in order to mitigate inadvertent harm to minoritized populations.

  PublisherOA PDFDOI

• Nursing Home–Based Care for Children Younger Than 18 Years: 2012–2019

  Pediatrics Open Science · 2025-11-24

  articleOpen access

  OBJECTIVES We examined nursing home use from 2012 to 2019 by children younger than 18 years and evaluated disparities in short-term stays (≤100 days) and long-term care nursing home stays across racial and ethnic groups. METHODS We categorized children into 5 groups: non-Hispanic white (NHW), non-Hispanic Black (NHB), Asian, Hispanic, and an “Other” group, which included American Indian or Alaska Native, Native Hawaiian or Pacific Islander, multiracial or multiethnic children, and children with unknown race or ethnicity. To examine changes in the total number of short-term and long-term nursing home stays among children, we aggregated the number of stays by year and used negative binomial regression models to assess the yearly trends. RESULTS From 2012 to 2019, there were 22 351 nursing home stays by children younger than 18 years, of which 50.4% were by NHW children, 23.2% were by NHB children, 15.4% were by Hispanic children, 4.4% were by Asian children, and 6.7% were by children in the Other racial and ethnic group. Nursing home use among children declined over the study period for both short- and long-term stays. The proportion of NHW children decreased in both types of stays, whereas the proportions of NHB and those in the Other racial and ethnic category increased. CONCLUSION Together, the findings suggest a worsening racial disparity in care delivery for medically complex children. Research to understand the causes of these shifts, such as changes in the demographics of the population at risk, access to care, or treatment preferences, is urgently needed.

  PublisherOA PDFDOI

• A Normal Forced Vital Capacity Does Not Reliably or Equitably Exclude Restriction

  Annals of the American Thoracic Society · 2025-06-12 · 1 citations

  letterOpen access
  PublisherOA PDFDOI

• Deciphering the influence of demographic factors on the treatment of pediatric patients in the emergency department

  ArXiv.org · 2025-10-03

  preprintOpen access

  Persistent demographic disparities have been identified in the treatment of patients seeking care in the emergency department (ED). These may be driven in part by subconscious biases, which providers themselves may struggle to identify. To better understand the operation of these biases, we performed a retrospective cross-sectional analysis using electronic health records describing 339,400 visits to the ED of a single US pediatric medical center between 2019-2024. Odds ratios were calculated using propensity-score matching. Analyses were adjusted for confounding variables, including chief complaint, insurance type, socio-economic deprivation, and patient comorbidities. We also trained a machine learning [ML] model on this dataset to identify predictors of admission. We found significant demographic disparities in admission (Non-Hispanic Black [NHB] relative to Non-Hispanic White [NHW]: OR 0.77, 95\% CI 0.73-0.81; Hispanic relative to NHW: OR 0.80, 95\% CI 0.76-0.83). We also identified disparities in individual decisions taken during the ED stay. For example, NHB patients were significantly less likely than NHW patients to be assigned an `emergent' triage acuity score of (OR 0.70, 95\% CI 0.67-0.72), but emergent NHB patients were also significantly less likely to be admitted than NHW patients with the same triage acuity (OR 0.86, 95\% CI 0.80-0.93). Demographic disparities were particularly acute wherever patients had normal vital signs, public insurance, moderate socio-economic deprivation, or a home address distant from the hospital. An ML model assigned higher importance to triage score for NHB than NHW patients when predicting admission, reflecting these disparities in assignment. We conclude that many visit characteristics, clinical and otherwise, may influence the operation of subconscious biases and affect ML-driven decision support tools.

  PublisherOA PDFDOI

Frequent coauthors

• Eve J. Higginbotham

  Office of Diversity and Inclusion

  38 shared

• Chang Xu

  University of Pennsylvania

  29 shared

• Marilyn M. Schapira

  University of Pennsylvania

  23 shared

• Matthew D. Kearney

  University of Pennsylvania

  22 shared

• Dominique Alexis

  University of Pennsylvania

  20 shared

• Allison Bautista

  University of Pennsylvania

  19 shared

• Jazmine M Smith

  University of Pennsylvania Health System

  19 shared

• Daniel K. Resnick

  18 shared

Education

• MD

  University of Pittsburgh School of Medicine

• Bachelors of Science, Honors Degree, Anthropology-Zoology

  University of Michigan

• MPH, Healthcare Management and Policy

  Harvard School of Public Health

  2010