HIV Care Engagement and Retention Strategies

Effective engagement and retention in HIV care are central to achieving optimal clinical outcomes, reducing transmission and meeting global targets for epidemic control. Strategies span structural, behavioural and technological domains. Structural interventions include transportation support, integrated mental health and substance-use services, and streamlined clinic processes to reduce appointment burdens. Behavioural approaches harness peer support, community outreach and tailored counselling to address stigma, enhance motivation and foster trust. Technological innovations range from mobile health reminders and telemedicine consultations to predictive analytics that identify individuals at risk of disengagement. Across settings, multidisciplinary teams work alongside community health workers to deliver flexible appointment schedules, same-day antiretroviral therapy initiation and patient empowerment programmes. Evaluations demonstrate that combining social enablers with data-driven risk stratification can substantially improve continuity of care, viral suppression rates and quality of life for people living with HIV.

Research from Nature Portfolio

Machine-learning models applied to clinic electronic records and geospatial factors have refined the prediction of patients at highest risk of dropping out of HIV care. By flagging the top decile of risk, these models achieved a positive predictive value exceeding 30 per cent for future non-attendance, outperforming traditional logistic regression. This data-driven approach offers a scalable framework for targeting intensive retention interventions, optimising resource allocation and enhancing viral suppression at both individual and population levels.

HIV Care Engagement and Retention Strategies publication trend

The graph below shows the total number of articles in hiv care engagement and retention strategies across all publications each year (not limited to Nature Index journals).

Technical terms

Care engagement: Active participation by an individual in all stages of the HIV care continuum, from diagnosis through treatment adherence.

Retention in care: Continuous involvement of a person living with HIV in scheduled clinical services over time.

Antiretroviral therapy (ART): Use of medication regimens to suppress HIV replication and preserve immune function.

Viral suppression: Reduction of HIV viral load in the blood to levels below the threshold of detection.

Predictive modelling: Application of statistical or machine-learning techniques to forecast risk of lapses in care based on patient data.

Electronic health record (EHR): Digital system for storing and managing patient medical histories, laboratory results and encounter information.

References

1. Predictive Analytics for Retention in Care in an Urban HIV Clinic. Scientific Reports (2020).
2. Predictive Modeling of Lapses in Care for People Living with HIV in Chicago: Algorithm Development and Interpretation. JMIR Public Health and Surveillance (2023).
3. Exploring the Feasibility of an Electronic Tool for Predicting Retention in HIV Care: Provider Perspectives. International Journal of Environmental Research and Public Health (2024).
4. Barriers and facilitators to patient retention in HIV care. BMC Infectious Diseases (2015).