Beyond binary retention in HIV care: predictors of the dynamic processes of patient engagement, disengagement, and re-entry into care in a US clinical cohort.

OBJECTIVES: Studies examining engagement in HIV care often capture cross-sectional patient status to estimate retention and identify predictors of attrition, which ignore longitudinal patient care-seeking behaviors. We describe the cyclical nature of (dis)engagement and re-entry into HIV care using the state transition framework. DESIGN: We represent the dynamic patterns of patient care-retention using five states: engaged in care, missed one, two, three, or more expected visits, and deceased. Then we describe various care-seeking behaviors in terms of transitioning from one state to another (e.g. from disengaged to engaged). This analysis includes 31 009 patients enrolled in the Center for AIDS Research Network of Integrated Systems (CNICS) in the United States from 1996 to 2014. METHOD: Multistate models for longitudinal data were used to identify barriers to retention and subgroups at higher risk of falling out of care. RESULTS: The initial 2 years following primary engagement in care were a crucial time for improving retention. Patients who had not initiated antiretroviral therapy, with lower CD4 cell counts, higher viral load, or not having an AIDS-defining illness were less likely to be retained in care. CONCLUSION: Beyond the individual patient characteristics typically used to characterize retention in HIV care, we identified specific periods of time and points in the care continuum associated with elevated risk of transitioning out of care. Our findings can contribute to evidence-based recommendations to enhance long-term retention in CNICS. This approach can also be applied to other cohort data to identify retention strategies tailored to each population.

Associations with Unprotected Sexual Behavior Among HIV-Infected Drinkers in Western Kenya.

Approximately 71% of HIV-infected individuals live in sub-Saharan Africa. Alcohol use increases unprotected sex, which can lead to HIV transmission. Little research examines risky sex among HIV-infected individuals in East Africa who are not sex workers. The study purpose was to examine associations with unprotected sex in a high-risk sample of 507 HIV-infected sexually active drinkers in western Kenya. They were enrolled in a trial to reduce alcohol use. Past-month baseline alcohol use and sexual behavior were assessed using the Timeline Followback. A zero-inflated negative binomial model examined associations with occurrence and frequency of unprotected sex. Results showed heavy drinking days were significantly associated with unprotected sex occurrence across gender, and with unprotected sex frequency among women. Among women, transactional sex, alcohol-related sexual expectations, condom use self-efficacy, drinking-and-protected-sex days and age were associated with unprotected sex occurrence while alcohol-related sexual expectations, depressive symptoms and condom use self-efficacy were associated with unprotected sex frequency. Among men, alcohol-related sexual expectations, condom use self-efficacy, and age were associated with unprotected sex occurrence, while drinking-and-protected-sex days were associated with unprotected sex occurrence and frequency. Findings suggest robust relationships between heavy drinking and unprotected sex. Further research is needed elucidating the temporal relationships between drinking and unprotected sex in this population.

Point of Diagnosis and Patient Retention in HIV Care in Western Kenya.

BACKGROUND: Home-based counseling and testing (HBCT) achieves earlier HIV diagnosis than other testing modalities; however, retention in care for these healthier patients is unknown. The objective of this study was to determine the association between point of HIV testing and retention in care and mortality. SETTING: Academic Model Providing Access to Healthcare (AMPATH) has provided HIV care in western Kenya since 2001. METHODS: AMPATH initiated HBCT in 2007. This retrospective analysis included individuals 13 years and older, enrolled in care between January 2008 and September 2016, with data on point of testing. Discrete-time multistate models were used to estimate the probability of transition between the following states: engaged, disengaged, transfer, and death, and the association between point of diagnosis and transition probabilities. RESULTS: Among 77,358 patients, 67% women, median age: 35 years and median baseline CD4: 248 cells/mm. Adjusted results demonstrated that patients from HBCT were less likely to disengage [relative risk ratio (RRR) = 0.87, 95% CI: 0.83 to 0.91] and die (RRR = 0.65, 95% CI: 0.55 to 0.75), whereas those diagnosed through provider-initiated counseling and testing were more likely to disengage (RRR = 1.09, 95% CI: 1.07 to 1.12) and die (RRR = 1.13, 95% CI: 1.06 to 1.20), compared with patients from voluntary counseling and testing. Once disengaged, patients from HBCT were less likely to remain disengaged, compared with patients from voluntary counseling and testing. CONCLUSIONS: Patients entering care from different HIV-testing programs demonstrate differences in retention in HIV care over time beyond disease severity. Additional research is needed to understand the patient and system level factors that may explain the associations between testing program, retention, and mortality.

A state transition framework for patient-level modeling of engagement and retention in HIV care using longitudinal cohort data.

The human immunodeficiency virus (HIV) care cascade is a conceptual model used to outline the benchmarks that reflects effectiveness of HIV care in the whole HIV care continuum. The models can be used to identify barriers contributing to poor outcomes along each benchmark in the cascade such as disengagement from care or death. Recently, the HIV care cascade has been widely applied to monitor progress towards HIV prevention and care goals in an attempt to develop strategies to improve health outcomes along the care continuum. Yet, there are challenges in quantifying successes and gaps in HIV care using the cascade models that are partly due to the lack of analytic approaches. The availability of large cohort data presents an opportunity to develop a coherent statistical framework for analysis of the HIV care cascade. Motivated by data from the Academic Model Providing Access to Healthcare, which has provided HIV care to nearly 200,000 individuals in Western Kenya since 2001, we developed a state transition framework that can characterize patient-level movements through the multiple stages of the HIV care cascade. We describe how to transform large observational data into an analyzable format. We then illustrate the state transition framework via multistate modeling to quantify dynamics in retention aspects of care. The proposed modeling approach identifies the transition probabilities of moving through each stage in the care cascade. In addition, this approach allows regression-based estimation to characterize effects of (time-varying) predictors of within and between state transitions such as retention, disengagement, re-entry into care, transfer-out, and mortality. Copyright © 2017 John Wiley & Sons, Ltd.