Comparison of HIV Screening Strategies in the Emergency Department: A Randomized Clinical Trial.

Importance: The National HIV Strategic Plan for the US recommends HIV screening in emergency departments (EDs). The most effective approach to ED-based HIV screening remains unknown. Objective: To compare strategies for HIV screening when integrated into usual ED practice. Design, Setting, and Participants: This randomized clinical trial included patients visiting EDs at 4 US urban hospitals between April 2014 and January 2016. Patients included were ages 16 years or older, not critically ill or mentally altered, not known to have an HIV positive status, and with an anticipated length of stay 30 minutes or longer. Data were analyzed through March 2021. Interventions: Consecutive patients underwent concealed randomization to either nontargeted screening, enhanced targeted screening using a quantitative HIV risk prediction tool, or traditional targeted screening as adapted from the Centers for Disease Control and Prevention. Screening was integrated into clinical practice using opt-out consent and fourth-generation antigen-antibody assays. Main Outcomes and Measures: New HIV diagnoses using intention-to-treat analysis, absolute differences, and risk ratios (RRs). Results: A total of 76 561 patient visits were randomized; median (interquartile range) age was 40 (28-54) years, 34 807 patients (51.2%) were women, and 26 776 (39.4%) were Black, 22 131 (32.6%) non-Hispanic White, and 14 542 (21.4%) Hispanic. A total of 25 469 were randomized to nontargeted screening; 25 453, enhanced targeted screening; and 25 639, traditional targeted screening. Of the nontargeted group, 6744 participants (26.5%) completed testing and 10 (0.15%) were newly diagnosed; of the enhanced targeted group, 13 883 participants (54.5%) met risk criteria, 4488 (32.3%) completed testing, and 7 (0.16%) were newly diagnosed; and of the traditional targeted group, 7099 participants (27.7%) met risk criteria, 3173 (44.7%) completed testing, and 7 (0.22%) were newly diagnosed. When compared with nontargeted screening, targeted strategies were not associated with a higher rate of new diagnoses (enhanced targeted and traditional targeted combined: difference, -0.01%; 95% CI, -0.04% to 0.02%; RR, 0.7; 95% CI, 0.30 to 1.56; P = .38; and enhanced targeted only: difference, -0.01%; 95% CI, -0.04% to 0.02%; RR, 0.70; 95% CI, 0.27 to 1.84; P = .47). Conclusions and Relevance: Targeted HIV screening was not superior to nontargeted HIV screening in the ED. Nontargeted screening resulted in significantly more tests performed, although all strategies identified relatively low numbers of new HIV diagnoses. Trial Registration: ClinicalTrials.gov Identifier: NCT01781949.

Evaluation of a computer-based and counseling support intervention to improve HIV patients' viral loads.

We sought to integrate a brief computer and counseling support intervention into the routine practices of HIV clinics and evaluate effects on patients' viral loads. The project targeted HIV patients in care whose viral loads exceeded 1000 copies/ml at the time of recruitment. Three HIV clinics initiated the intervention immediately, and three other HIV clinics delayed onset for 16 months and served as concurrent controls for evaluating outcomes. The intervention components included a brief computer-based intervention (CBI) focused on antiretroviral therapy adherence; health coaching from project counselors for participants whose viral loads did not improve after doing the CBI; and behavioral screening and palm cards with empowering messages available to all patients at intervention clinics regardless of viral load level. The analytic cohort included 982 patients at intervention clinics and 946 patients at control clinics. Viral loads were assessed at 270 days before recruitment, at time of recruitment, and +270 days later. Results indicated that both the control and intervention groups had significant reductions in viral load, ending with approximately the same viral level at +270 days. There was no evidence that the CBI or the targeted health coaching was responsible for the viral reduction in the intervention group. Results may stem partially from statistical regression to the mean in both groups. Also, clinical providers at control and intervention clinics may have taken action (e.g., conversations with patients, referrals to case managers, adherence counselors, mental health, substance use specialists) to help their patients reduce their viral loads. In conclusion, neither a brief computer-based nor targeted health coaching intervention reduced patients' viral loads beyond levels achieved with standard of care services available to patients at well-resourced HIV clinics.

Motivation as a Mechanism for Daily Experiences' Effects on HIV Medication Adherence.

Medication adherence is a challenge for people living with HIV (PLWH), who may experience a gap between their intentions and everyday behaviors. We measured PLWH's (n = 87) daily experiences and tested a model to explain the intention-behavior gap. Participants completed baseline questionnaires, then used a smartphone-based survey and an electronic pill bottle to provide daily data for the next 10 weeks. These PLWH, with generally well-controlled HIV, were nevertheless adherent on only 73% of study days. Multilevel analyses were used to test predicted relationships between variables (n = 58). Four of five theory-based daily measures predicted motivation for antiretroviral therapy (betas = 0.06-0.10), and motivation, in turn, predicted adherence. Consistent with our theory, control beliefs, mood, and social support had indirect effects on adherence. However, stress and coping did not. Daily experiences affect adherence, even in PLWH with well-controlled HIV. Providers should ask about everyday changes in motivation.

Prospective State and Trait Predictors of Daily Medication Adherence Behavior in HIV.

BACKGROUND: Many persons living with HIV (PLWH) are nonadherent to medication. Trait level measures that ask about predictors of adherence in the abstract may not adequately capture state level daily variability that more directly impacts adherence. OBJECTIVES: This preliminary study was designed to test six predictors of electronically monitored adherence at both the state and trait levels and to compare their relative effects. METHODS: Using a smartphone, 87 PLWH completed randomly cued daily surveys on thoughts, mood, stress, coping, social support, and treatment motivation. All participants also completed baseline surveys on each construct. These state and trait variables were tested as prospective predictors of next-day adherence in multilevel models, and their relative importance was quantified. The analysis sample consisted of 53 PLWH who stored their most frequent antiretroviral medication in a bottle that time-stamped openings to measure adherence. RESULTS: Higher state level motivation, OR = 1.55, 95% CI [1.07, 2.24], and negative mood, OR = 1.33, 95% CI [1.07, 1.63], predicted greater adherence the following day. Importantly, these effects were only found at the state level. Trait level control beliefs predicted greater adherence, OR = 1.65, 95% CI [1.17, 2.35], but contrary to prediction, validated trait level measures of mood, stress, coping, social support, and motivation did not. DISCUSSION: Trait and state level measures predicted adherence, but there were differences between them. Motivation for treatment and negative mood predicted adherence when measured the preceding day, but not as aggregate measures. At the trait level, only control beliefs predicted adherence. Researchers should consider state level variations in mood and motivation as possible explanations for nonadherence. Interventions could be developed to target state level variables.