Identifying Health Care Services Offered in the HIV Care Continuum via a Machine Learning-Based Topic Modeling...

Area of Science:

• Public Health
• Infectious Diseases
• Health Services Research

Background:

• Existing healthcare services may not fully align with the HIV care continuum, necessitating integrated care beyond viral suppression.
• There is a need to understand trends and knowledge structures in healthcare services for people living with HIV.

Purpose of the Study:

• To analyze the literature on healthcare services for people living with HIV.
• To enhance understanding of trends and knowledge structures in HIV care.

Main Methods:

• A literature review was conducted using BERTopic, a machine learning-based topic modeling technique.
• Searched PubMed, CINAHL, EMBASE, and Cochrane databases for English-language studies published between 2013 and 2023.
• Analyses were performed twice: first for a broad understanding, then for specific healthcare service details.

Main Results:

• 204 studies out of 11,269 screened met inclusion criteria.
• Most studies focused on treatment retention; limited studies addressed long-term HIV management.
• Key topics included "ART adherence" and "ART adherence and counseling," with decreasing diversity of healthcare services in later HIV care continuum stages.

Conclusions:

• Current HIV care literature overemphasizes medication treatment, overlooking multifaceted health needs.
• Research disparities exist, particularly for vulnerable populations, highlighting the need for inclusive studies.
• Efforts are needed to bridge gaps, ensure equitable care, and foster collaboration for people living with HIV.