Study protocol for: Compliance Assessment of the District Health Management Information System: Supervision of Data Management Processes for HIV Care in Public Healthcare Facilities in South Africa

As South Africa strives to meet the Joint United Nations Programme on HIV/AIDS (UNAIDS) 95-95-95, targets require adequate patient data to track people living with HIV (PLHIV) and link them to care. The National District Health Management Information System (DHMIS) Facility Report Standard Operating Procedures (SOP) aims to standardise data collection and use across health facilities. However, data quality issues persist after a decade of implementing the DHMIS-SOP. Currently, there is limited evidence on DHMIS-SOP compliance at the facility level. This study will explore healthcare managers compliance with DHMIS-SOP in HIV data management, identify facilitators and barriers to compliance, and develop strategies to improve adherence. MethodsA multimethod study will be conducted in 46 selected HIV clinics in the uMgungundlovu District, KwaZulu-Natal. A scoping review will identify compliance frameworks for HIV data management. The PRISM Organisational Behavioural Assessment Tool (OBAT) and Management Assessment Tool (MAT) will assess 161 healthcare professionals knowledge of DHMIS-SOP content, motivations, and data supervision by the district management team. The results will inform in-depth interviews (IDIs) with 10-12 key informants to explore perceptions and experiences of DHMIS-SOP compliance and identify barriers and facilitators. A compliance framework will be developed to support SOP adherence in HIV data management. AnalysisThe scoping review will synthesise concepts and compliance frameworks/tools for SOP adherence. Descriptive statistics will report the percentages and proportions for categorical data, while mean, standard deviation (SD), median, and interquartile range (IQR) will report findings for continuous data. Frequency distributions, univariate and bivariate analyses, and multiple regression will describe and examine the strength of the relationship between facility managers and the district office on HIV data management processes, challenges and strategies for SOP compliance. For dichotomous data, 95% confidence limits will be calculated. A general inductive method driven by key barriers or facilitators of compliance will analyse the qualitative data. Two reviewers will independently translate transcripts and create a structured coding framework. The source quotes will be assessed and agreed upon, and a robust thematic report will be generated based on the combined analyses. A comparative analysis between and within interviews will develop coded information categories linked to broader themes evolving across interviews. This will guide data analysis in the ATLAS.ti software. Qualitative and quantitative data are integrated where appropriate. The findings of these phases will inform an expert panel workshop where an SOP compliance framework will be developed to improve SOP adherence in HIV data management in primary healthcare settings.