Measuring retention in HIV care: the elusive gold standard.

Background: Measuring retention in HIV primary care is complex, as care includes multiple visits scheduled at varying intervals over time. We evaluated 6 commonly used retention measures in predicting viral load (VL) suppression and the correlation among measures.

Methods: Clinic-wide patient-level data from 6 academic HIV clinics were used for 12 months preceding implementation of the Centers for Disease Control and Prevention/Health Resources and Services Administration (CDC/HRSA) retention in care intervention. Six retention measures were calculated for each patient based on scheduled primary HIV provider visits: count and dichotomous missed visits, visit adherence, 6-month gap, 4-month visit constancy, and the HRSA HIV/AIDS Bureau (HRSA HAB) retention measure. Spearman correlation coefficients and separate unadjusted logistic regression models compared retention measures with one another and with 12-month VL suppression, respectively. The discriminatory capacity of each measure was assessed with the c-statistic.

Results: Among 10,053 patients, 8235 (82%) had 12-month VL measures, with 6304 (77%) achieving suppression (VL <400 copies/mL). All 6 retention measures were significantly associated (P < 0.0001) with VL suppression (odds ratio; 95% CI, c-statistic): missed visit count (0.73; 0.71 to 0.75, 0.67), missed visit dichotomous (3.2; 2.8 to 3.6, 0.62), visit adherence (3.9; 3.5 to 4.3,0.69), gap (3.0; 2.6 to 3.3, 0.61), visit constancy (2.8; 2.5 to 3.0, 0.63), and HRSA HAB (3.8; 3.3 to 4.4, 0.59). Measures incorporating "no-show" visits were highly correlated (Spearman coefficient = 0.83-0.85), as were measures based solely on kept visits (Spearman coefficient = 0.72-0.77). Correlation coefficients were lower across these 2 groups of measures (range = 0.16-0.57).

Conclusions: Six retention measures displayed a wide range of correlation with one another, yet each measure had significant association and modest discrimination for VL suppression. These data suggest there is no clear gold standard and that selection of a retention measure may be tailored to context.