Methodological Evaluation and Clinical Outcomes of Urban Primary Care Networks in Uganda: A Difference-in-Differences Meta-Analysis

{ "background": "Urban primary care networks are a critical but under-evaluated component of health system strengthening in sub-Saharan Africa. There is a lack of synthesised evidence on the methodological rigour and effectiveness of these networks in improving clinical outcomes.", "purpose and objectives": "This meta-analysis aimed to systematically evaluate the methodological quality of difference-in-differences (DiD) studies assessing urban primary care networks in Uganda and to quantitatively synthesise their estimated effects on key clinical outcomes.", "methodology": "We conducted a systematic review and meta-analysis of quasi-experimental studies employing a DiD design. Methodological quality was appraised using a modified checklist for DiD studies. Pooled effect sizes for clinical outcomes were calculated using random-effects models. The core DiD model was specified as $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\beta3 (\\text{Treat}i \\times \\text{Post}t) + \\epsilon{it}$, with inference based on cluster-robust standard errors.", "findings": "Methodological appraisal revealed that only 35% of included studies adequately addressed the parallel trends assumption. The pooled analysis showed a significant increase in the completion rate for antenatal care visits, with a risk ratio of 1.28 (95% CI: 1.12 to 1.47). No significant pooled effect was found for childhood immunisation coverage.", "conclusion": "While evidence suggests urban primary care networks can improve specific maternal health service utilisation, the methodological quality of evaluations is inconsistent. The positive effect on antenatal care completion is promising but not generalisable to all clinical domains.", "recommendations": "Future evaluations must prioritise rigorous testing of DiD assumptions and explore heterogeneous effects across different patient subgroups and network governance models. Policy implementation should be accompanied by dedicated funding for robust impact evaluation.", "key words": "primary health care, health systems, quasi-exper