Patient Portal Activation Among Neurology Patients in Washington, DC
Streicher, N. S.
Show abstract
Background and ObjectivesPatient portals have become essential infrastructure for healthcare delivery following the 21st Century Cures Act, yet adoption remains inequitable. Understanding demographic and geographic determinants of portal activation is critical for addressing digital health disparities, particularly among neurology patients who face unique access barriers. We examined the demographic, geographic, and neighborhood-level factors associated with patient portal activation among neurology patients at multiple geographic scales in the Washington, DC metropolitan area. MethodsWe conducted a retrospective cohort study of 72,417 adult neurology patients seen at two academic medical centers sharing an electronic health record in Washington, DC (February 2021-February 2026). We examined portal activation using multivariable logistic regression and geographic analysis at four nested scales: the metropolitan catchment area, DCs eight wards, individual census tracts (via geocoded patient addresses), and individual DC residents. ResultsPortal activation was 64.7% overall. Activation varied by race/ethnicity (Non-Hispanic White 76.1%, Non-Hispanic Black 57.0%, Non-Hispanic Asian 57.6%, Hispanic 55.0%) and geography (DC Ward 2: 82.0% vs. Ward 7: 48.0%). Ward-level educational attainment (r = 0.948), broadband access (r = 0.889), and income (r = 0.811) were strongly correlated with activation. Within individual wards, Non-Hispanic White patients activated at 84-91% while Non-Hispanic Black patients activated at 48-64%, demonstrating that neighborhood resources alone do not explain disparities. DiscussionPatient portal activation is shaped by demographic, socioeconomic, and geographic factors operating at multiple levels. Persistent within-ward racial disparities indicate that geographically targeted interventions must be paired with culturally tailored approaches to achieve digital health equity.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Association between City-wide Lockdown and COVID-19 Hospitalization Rates in Multigenerational Households in New York City 93%
- Massachusetts General Hospital Covid-19 Registry reveals two distinct populations of hospitalized patients by race and ethnicity 92%
- Hospital segregation, critical care strain, and inpatient mortality during the COVID-19 pandemic in New York City 92%
Similar papers in this journal
- Cohort Profile: A national prospective cohort study of SARS-CoV-2 pandemic outcomes in the U.S. - The CHASING COVID Cohort Study 93%
- Racial and Ethnic Disparities in SARS-CoV-2 Pandemic: Analysis of a COVID-19 Observational Registry for a Diverse U.S. Metropolitan Population 92%
- Viral And Antibody Testing For Coronavirus Disease 2019 (Covid-19): Factors Associated With Positivity In Electronic Health Records From The United States 92%
Similar papers in this journal
- A Survey of Individuals’ Willingness to Share Real-World Data Post-Mortem with Researchers 89%
- Operationalizing a complex acute clinical trial: Lessons from the BEACH study 88%
- A Retrospective Case Study of Successful Translational Research: Cardiovascular Disease Risk Assessment, Experiences in Community Engagement 88%
Similar papers in this journal
- Real-Time Electronic Health Record Mortality Prediction During the COVID-19 Pandemic: A Prospective Cohort Study 91%
- Clinical Utility of Automatable Prediction Models for Improving Palliative and End-Of-Life Care Outcomes: Towards Routine Decision Analysis Before Implementation 90%
- Large Language Models Facilitate the Generation of Electronic Health Record Phenotyping Algorithms 89%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.