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Objectives: To describe the participants of a university-based COVID-19 contact tracing course and determine whether the course changed knowledge, attitudes, and intention to participate in contact tracing. Participants: Faculty, staff, and students were eligible. Methods: Surveys evaluated the impact of the course on participant intentions to engage in contact tracing. Logistic regression identified characteristics associated with increased likelihood of participating in contact tracing. Results: Nearly 800 individuals participated, of whom 26.2% identified as Hispanic/Latino and 14.0% as Black. Nearly half (48.8%) planned to conduct contact tracing. While attitudes did not change, knowledge improved (67.9% vs. 93.8% scores on assessments; p < 0.001). Younger participants and Black individuals were more more likely to be confident that they would participate in contact tracing. Conclusions: Course completion was associated with increased knowledge. Participants were racially and ethnically diverse, highlighting how universities can partner with health departments to develop workforces that reflect local communities. [ABSTRACT FROM AUTHOR]

Background: Patient portals can improve access to electronic health information and enhance patient engagement. However, disparities in patient portal utilization remain, affecting disadvantaged communities disproportionately. This study examined patient- and provider-level factors associated with portal usage among Medicaid recipients in a large federally qualified health center (FQHC) network in Texas. Methods: Deidentified electronic medical records of patients 18 years or older from a large Texas FQHC network were analyzed. The dependent variable was a binary flag indicating portal usage during the study period. Independent variables included patient- and provider-level factors. Patient-level factors included sociodemographic, geographic, and clinical characteristics. Provider characteristics included primary service line, provider type, provider language, and years in practice. Because the analysis was at the individual level, a multivariable logistic regression model focused on adjusted associations between independent variables and portal usage. Results: The analytic sample consisted of 9,271 individuals. Compared with individuals 18–39 years, patients 50 years and older had lower odds (50–64 OR: 0.60, p < 0.001; 65+ OR: 0.51, p < 0.001) of portal usage. Males were less likely to use portals (OR: 0.44, p = 0.03), and compared to Non-Hispanic Whites, Non-Hispanic Black (OR: 0.86, p = 0.02) and Hispanics (OR: 0.83, p < 0.001) were significantly less likely to use portals. Individuals with 1 or more telemedicine consults had a two-times greater odds of portal usage (OR: 1.97, p < 0.001). Compared to individuals who had clinic visits in December 2018, portal usage was significantly higher in the pandemic months (March 2020–November 2020, all p's < 0.01). Importantly, the behavioral health service line had the greatest odds (OR: 1.52, p < 0.001), whereas the dental service line had the lowest odds (OR: 0.69, p = 0.01) compared to family practice. No other provider characteristics were significant. Conclusion: Our finding of significant patient-level factors is important and can contribute to developing appropriate patient-focused health information technology approaches to ensure equitable access and maximize the potential benefits of patient portals in health care delivery. [ABSTRACT FROM AUTHOR]

Social isolation is a well-documented contributor to poor mental and physical health, and interventions promoting social connectedness have been associated with various health benefits. This study examined predictors of participation in a telephone-based social connectedness intervention for socially isolated older adults. Data were obtained from a social-connectedness intervention that paired college students with Houston-area, community-dwelling adults aged 65 years and older and enrolled in Medicare Advantage plans. We combined machine learning and regression techniques to identify significant predictors of program participation. The following machine-learning methods were implemented: (1) k -nearest neighbors, (2) decision tree and ensembles of decision trees, (3) gradient-boosted decision tree, and (4) random forest. The primary outcome was a binary flag indicating participation in the telephone-based social-connectedness intervention. The most predictive variables in the ML models, with scores corresponding to the 90th percentile or greater, were included in the regression analysis. The predictive ability of each model showed high discriminative power, with test accuracies greater than 95%. Our findings suggest that telephone-based social-connectedness interventions appeal to individuals with disabilities, depression, arthritis, and higher risk scores. scores. Recognizing features that predict participation in social-connectedness programs is the first step to increasing reach and fostering patient engagement. [ABSTRACT FROM AUTHOR]

Data chronicling the geo-locations of all 61,589 pharmacies in the U.S. (from the Homeland Infrastructure Foundation-Level Data (HIFLD) Open Data interface, updated on April 2018) across 215,836 census block groups were combined with Medically Underserved Areas (MUAs) information, and the Centers for Disease Control and Prevention's Social Vulnerability Index (CDC-SVI). Geospatial techniques were applied to calculate the distance between the center of each census block and the nearest pharmacy. We then modeled the expected additional travel distance if the nearest pharmacy to the center of a census block closed and estimated additional travel costs, CO2 emissions, and lost labor productivity costs associated with the additional travel. Our findings revealed that MUA residents have almost two times greater travel distances to pharmacies than non-MUAs (4,269 m (2.65 mi) vs. 2,388 m (1.48 mi)), and this disparity is exaggerated with pharmacy closures (107% increase in travel distance in MUAs vs. 75% increase in travel distance in non-MUAs). Similarly, individuals living in MUAs experience significantly greater average annual economic costs than non-MUAs ($34,834 ± $668 vs. $22,720 ± $326). Our findings suggest the need for additional regulations to ensure populations are not disproportionately affected by these closures and that there is a significant throughput with community stakeholders before any pharmacy decides to close. [ABSTRACT FROM AUTHOR]

The Coronavirus Aid, Relief, and Economic Security Act led to the rapid implementation of telemedicine across health care office settings. Whether this transition to telemedicine has any impact on missed appointments is yet to be determined. This study examined the relationship between telemedicine usage and missed appointments during the COVID-19 pandemic. This retrospective study used appointment-level data from 55 Federally Qualified Health Centre clinics in Texas between March and November 2020. To account for the nested data structure of repeated appointments within each patient, a mixed-effects multivariable logistic regression model was used to examine associations between telemedicine use and missed appointments, adjusting for patient sociodemographic characteristics, geographic classification, past medical history, and clinic characteristics. The independent variable was having a telemedicine appointment, defined as an audiovisual consultation started and finalized via a telemedicine platform. The outcome of interest was having a missed appointment (yes/no) after a scheduled and confirmed medical appointment. Results from this initial model were stratified by appointment type (in-person vs. telemedicine). The analytic sample included 278,171 appointments for 85,413 unique patients. The overall missed appointment rate was 18%, and 25% of all appointments were telemedicine appointments. Compared to in-person visits, telemedicine visits were less likely to result in a missed appointment (OR = 0.87, p <.001). Compared to Whites, Asians were less likely to have a missed appointment (OR = 0.82, p <.001) while African Americans, Hispanics, and American Indians were all significantly more likely to have missed appointments (OR = 1.61, p <.001; OR = 1.19, p =.01; OR = 1.22, p <.01, respectively). Those accessing mental health services (OR = 1.57 for in-person and 0.78 for telemedicine) and living in metropolitan areas (OR = 1.15 for in-person and 0.82 for telemedicine) were more likely to miss in-person appointments but less likely to miss telemedicine appointments. Patients with frequent medical visits or those living with chronic diseases were more likely to miss in-person appointments but less likely to miss telemedicine appointments. Telemedicine is strongly associated with fewer missed appointments. Although our findings suggest a residual lag in minority populations, specific patient populations, including those with frequent prior visits or chronic conditions, those seeking mental health services, and those living in metropolitan areas were less likely to miss telemedicine appointments than in-person visits. These findings highlight how telemedicine can enable effective and accessible care by reducing missed healthcare appointments. Telemedicine was associated with 13% lower odds of missed appointments. Patients with frequent medical visits or those living with chronic diseases were less likely to miss telemedicine appointments but more likely to miss in-person appointments. Patients seeking mental health services were less likely to miss telemedicine appointments but more likely to miss in-person appointments. Similarly, those living in metropolitan areas were less likely to miss telemedicine appointments but more likely to miss in-person appointments. [ABSTRACT FROM AUTHOR]

In this study, we explored whether psychological distress plays a role in the use of recommended clinical preventive services among community-dwelling older adults. The sample is drawn from respondents 65 years and older who participated in the 2011 Medical Expenditure Panel Survey (MEPS). Logistic regressions with selected covariates were entered in the model to estimate odds ratios (OR) with 95% confidence interval (CI) for the independent effect of psychological distress on the utilization of each of five preventive services. With the exception of breast cancer screening where the uptake of preventive services was significantly lower for older adults with psychological distress (OR = 0.57, p <.001), uptake of other key preventive measures revealed no significant utilization differences between older adults with and without psychological distress. The results suggest that adherence to breast cancer screening guidelines may be increased by improving recognition and treatment of emotional health problems in older women. [ABSTRACT FROM AUTHOR]