Clinical and Sociodemographic Factors Associated with Telemedicine Engagement in an Urban Community Health Center Cohort During the COVID-19 Pandemic.

Objective: To examine chronic diseases, clinical factors, and sociodemographic characteristics associated with telemedicine utilization among a safety-net population. Materials and Methods: We conducted a retrospective cohort study of adults seeking care in an urban, multisite community health center in the Northeast United States. We included adults with ≥1 outpatient in-person visit during the pre-COVID-19 period (March 1, 2019-February 29, 2020) and ≥1 outpatient visit (in-person or telemedicine) during the COVID-19 period (March 1, 2020-February 29, 2021). Multivariable logistic regression models estimated associations between clinical and sociodemographic factors and telemedicine use, classified as "any" (≥1 visit) and "high" (≥3 visits). Results: Among 5,793 patients who met inclusion criteria, 4,687 (80.9%) had any (≥1) telemedicine visit and 1,053 (18.2%) had high (≥3) telemedicine visits during the COVID-19 period. Older age and Medicare coverage were associated with having any telemedicine use. Older and White patients were more likely to have high telemedicine use. Uninsured patients were less likely to have high telemedicine use. Patients with increased health care utilization in the pre-COVID-19 period and those with hypertension, diabetes, substance use disorders, and depression were more likely to have high telemedicine engagement. Discussion: Chronic conditions, older patients, and White patients compared with Latinx patients, were associated with high telemedicine engagement after adjusting for prior health care utilization. Conclusion: Equity-focused approaches to telemedicine clinical strategies are needed for safety-net populations. Community health centers can adopt disease-specific telemedicine strategies with high patient engagement.

Demographic and Clinical Correlates of the Cost of Potentially Preventable Hospital Encounters in a Community Health Center Cohort.

This study sought to describe the cost of hospital care for ambulatory care-sensitive conditions (ACSCs) and to identify independent predictors of high-cost hospital encounters related to an ACSC among an urban community health center cohort. The authors conducted a retrospective cohort study of individuals engaged in care in a large, multisite community health center in New Haven, Connecticut, with any Medicaid claims between June 1, 2018 and March 31, 2020. Prevention Quality Indicators of the Agency for Healthcare Research and Quality were used to identify ACSCs. The primary outcome was a high-cost episode of care for an ACSC (in the top quartile within a 7-day period). Multivariable logistic regression was used to identify independent predictors of high-cost episodes by ACSCs among sociodemographic and clinical variables as covariates. Among 8019 included individuals, a total of 751 episodes of hospital care involving ACSCs were identified. The median episode cost was $793, with the highest median cost of care related to heart failure ($4992), followed by diabetes ($1162), and chronic obstructive pulmonary disease ($1141). In adjusted analyses, male gender (P < 0.01), increasing age (P = 0.02), and ACSC type (P < 0.01) were associated with higher costs of care; race/ethnicity was not. Community health centers in urban settings seeking to reduce the cost of care of potentially preventable hospitalizations may target disease-/condition-specific groups, particularly individuals of increasing age with congestive heart failure and diabetes mellitus. These findings may inform return-on-investment calculations for care coordination and other enabling services programming.

Social Determinants and COVID-19 in a Community Health Center Cohort.

Associations between social determinants of health (SDOH), demographic factors including preferred language, and SARS-CoV-2 detection are not clear. We conducted a retrospective cohort study among those seeking testing for SARS-CoV-2 at a multi-site, urban community health center. Logistic regression and exact matching methods were used to identify independent predictors of SARS-CoV-2 detection among demographic, SDOH, and neighborhood-level variables. Of 1,361 included individuals, SARS-CoV-2 was detected among 266 (19.5%). Logistic regression demonstrated that SARS-CoV-2 detection was less likely in White participants relative to Hispanic participants (adjusted odds ratio [aOR] 0.18, 95% confidence interval [CI] 0.05-0.46). and more likely in patients who prefer Spanish relative to those that prefer English (aOR 2.04, 95% CI 1.43-2.96). No observed SDOH predicted SARS-CoV-2 detection in adjusted models. A robustness analysis using a matched subset of the study sample produced findings similar to those in the main analysis. Preferring to receive care in Spanish is an independent predictor of SARS-CoV-2 detection in a community health center cohort.