Piloting the inclusion of the key populations unique identifier code in the South African routine health information management system: Protocol for a mixed methods study (Preprint)

Abstract

The global community has set ambitious goal to end human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) as a public health threat by 2030. Significant progress has been achieved in pursuing these objectives; however, stigma and discrimination against key populations (KPs) continue. Key populations include female sex workers (FSW), transgender (TG) populations, gay men and other men who have sex with men (MSM), people who are incarcerated, and people who use drugs (PWUD). From an epidemiological perspective, KPs play a fundamental role in shaping the dynamics of HIV transmission due to specific behaviors', which put them at higher risk of HIV regardless of the type of epidemic or local context. In South Africa (SA), routine health management information systems (RHMIS) do not include unique identifier code (UIC) for KPs. Therefore, routine data cannot be disaggregated by KPs. There is a need for strengthening the current RHMIS in South Africa to ensure KPs data disaggregation to improve targeted resource allocation reporting and accountability inclusive of KPs. The purpose of this protocol is to develop the framework for improved HIV monitoring and programming through the inclusion of KPs UIC in the South African RHIMS.

This paper aims to describe the protocol for a mixed-methods study to pilot the inclusion of key populations unique identifier code on routine health information management system.

We will conduct a mixed-methods study to pilot the framework for the inclusion of KPs UIC in the RHIMS. This study will have four objectives including a systematic review according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Guidelines (Objective 1). The review is registered with International Prospective Register of Systematic Reviews (PROSPERO) CRD42023440656. Secondly, policy document review and in-depth stakeholder interviews using semi-structured questionnaires (Objective 2). Thirdly, exploratory data analysis of de-identified HIV datasets (Objective 3), and lastly piloting the framework to assess the feasibility of incorporating KPs UIC in RHIMS using findings from objectives 1, 2 and 3 (Objective 4). Qualitative and quantitative data will be analysed using ATLAS.ti v 23.1.1. and Python 3.11.4 programming language respectively.

As of November 2023, we have completed a preliminary literature search examining opportunities and challenges to the incorporation of KPs UIC in the RHIMS. Systematic searches, data extraction and analysis, and writing of the systematic review are expected to be completed by January 2024.

The study will produce a framework to be recommended for the inclusion of KPs UIC national rollout. The study results will contribute to the knowledge base around the inclusion of KPs UIC in RHIMS data. This will lead to data optimization, complete reporting, and programming.