Role of Visit Modality in the HIV-Related No-Shows During the COVID-19 Pandemic: A Multisite Retrospective Cohort Study.

The emergence of the COVID-19 pandemic necessitated rapid expansion of telehealth as part of healthcare delivery. This study compared HIV-related no-shows by visit type (in-person; video; telephone) during the COVID-19 pandemic (April 2020-September 2021) from the Data for Care Alabama project. Using all primary care provider visits, each visit's outcome was categorized as no-show or arrived. A logistic regression model using generalized estimating equations accounting for repeat measures in individuals and within sites calculated odds ratios (OR) and their accompanying 95% confidence interval (CI) for no-shows by visit modality. The multivariable models adjusted for sociodemographic factors. In-person versus telephone visits [OR (95% CI) 1.64 (1.48-1.82)] and in-person versus video visits [OR (95% CI) 1.53 (1.25-1.85)] had higher odds of being a no-show. In-person versus telephone and video no-shows were significantly higher. This may suggest success of telehealth visits as a method for HIV care delivery even beyond COVID-19.

Assessing the Impact of COVID-19 on Retention in HIV Primary Care: A Longitudinal Multisite Analysis.

We compared retention in care outcomes between a pre-COVID-19 (Apr19-Mar20) and an early-COVID-19 (Apr20-Mar21) period to determine whether the pandemic had a significant impact on these outcomes and assessed the role of patient sociodemographics in both periods in individuals enrolled in the Data for Care Alabama project (n = 6461). Using scheduled HIV primary care provider visits, we calculated a kept-visit measure and a missed-visit measure and compared them among the pre-COVID-19 and early-COVID-19 periods. We used logistic regression models to calculated odds ratios (OR) and accompanying 95% confidence intervals (CI). Overall, individuals had lowers odds of high visit constancy [OR (95% CI): 0.85 (0.79, 0.92)] and higher odds of no-shows [OR (95% CI): 1.27 (1.19, 1.35)] during the early-COVID-19 period. Compared to white patients, Black patients were more likely to miss an appointment and transgender people versus cisgender women had lower visit constancy in the early-COVID-19 period.

Data for Care (D4C) Alabama: Clinic-Wide Risk Stratification With Enhanced Personal Contacts for Retention in HIV Care via the Alabama Quality Management Group.

BACKGROUND: The Alabama Quality Management Group (AQMG), a consortium of 9 Ryan White-funded part C and D clinics, distributed statewide was established in 2006 under the guidance from the Health and Resources Services Administration with a clinical quality improvement (CQI) focus. METHODS: We describe the origins and evolution of the AQMG, including requisite shifts from aggregate clinic-wide to de-identified individual-level data reporting for implementation of the Data for Care (D4C-AL) Alabama program. The D4C-AL strategy uses a clinic-wide risk stratification of all patients based on missed clinic visits in the previous 12 months. Intermediate (1-2 missed visits) and high-risk patients (>3 missed visits) receive the evidence-informed Retention through Enhanced Personal Contact intervention. We report on a pilot of the D4CAL program in 4 of 33 primary HIV care clinics at the UAB 1917 Clinic. RESULTS: Among 3859 patients seen between April 2018 and February 2019, the missed visit rate was not significantly different between the D4C-1917 (19.2%) and non-D4C clinics (20.5%) in a preintervention period (May 2017-April 2018). However, a significantly lower missed visit rate was observed in the D4C-1917 vs. non-D4C-1917 clinics during the intervention period (April 2018-February 2019, P = 0.049). CONCLUSIONS: The AQMG has been transformed into a health service research and implementation science platform, building on a shared vision, mission, data reporting, and quality improvement focus. Moreover, CQI may be viewed as an implementation strategy that seeks to enhance uptake and sustained use of effective interventions with D4C-AL representing a prototype for future initiatives embedded within extant quality improvement consortia.