Risk Prediction Tool for Medical Appointment Attendance Among HIV-Infected Persons with Unsuppressed Viremia

Successful treatment of HIV infection requires regular clinical follow-up. A previously published risk-prediction tool (RPT) utilizing data from the electronic health record (EHR) including medication adherence, previous appointment attendance, substance abuse, recent CD4+ count, prior antiretroviral therapy (ART) exposure, prior treatment failure, and recent HIV-1 viral load (VL) has been shown to predict virologic failure at 1 year. If this same tool could be used to predict the more immediate event of appointment attendance, high-risk patients could be identified and interventions could be targeted to improve this outcome. We conducted an observational cohort study at the Vanderbilt Comprehensive Care Clinic from August 2013 through March 2014. Patients with routine medical appointments and most recent HIV-1 VL >200 copies/mL were included. Risk scores for a modified RPT were calculated based on data from the EHR. Odds ratios (OR) for missing the next appointment were estimated using multivariable logistic regression. Among 510 persons included, median age was 39 years, 74% were male, 55% were black, median CD4+ count was 327 cells/mm(3) [Interquartile Range (IQR): 142-560], and median HIV-1 VL was 21,818 copies/mL (IQR: 2,030-69,597). Medium [OR 3.95, 95% confidence interval (CI) 2.08-7.50, p-value<0.01] and high (OR 9.55, 95% CI 4.31-21.16, p-value<0.01) vs. low RPT risk scores were independently associated with missing the next appointment. RPT scores, constructed using readily available data, allow for risk-stratification of HIV medical appointment non-attendance and could support targeting limited resources to improve appointment adherence in groups most at-risk of poor HIV outcomes.