Characterising patterns in routinely reported longitudinal HIV data in South Africa using a Bayesian multiplicative interaction model.

ABSTRACT:

Introduction

We consider an analytical problem of characterising patterns and identifying discrepancies between database systems for longitudinal aggregated healthcare data involving multiple facilities.

Methods

We used routinely collected data on the registered number of people living with HIV who initiated antiretroviral treatment (ART) in 69 South African facilities in 2019; reported in the Three Interlinked Electronic register (Tier.net) and the District Health Information System. A Bayesian multiplicative interaction model quantified the average time effect as realised through the heterogeneous facility-specific slopes and quantified discrepancies between the two database sources.

Results

The estimated average trends showed a slight dip in June and a large dip in

SUBMITTER: Nonyane BAS 

PROVIDER: S-EPMC11816978 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature