Abstract
{ "background": "Community health centres are a cornerstone of primary healthcare delivery, yet their operational effectiveness and the determinants of successful system adoption remain inconsistently evaluated. A comprehensive, methodologically rigorous synthesis of evidence is required to inform policy and practice.", "purpose and objectives": "This meta-analysis aims to methodologically evaluate the determinants influencing the adoption of community health centre systems. The primary objective is to synthesise quantitative evidence on factors at individual, organisational, and community levels using a multilevel modelling framework.", "methodology": "A systematic search identified relevant quantitative studies. A three-level random-effects meta-analysis was conducted, with the core statistical model specified as $y{ij} = \\beta{0} + \\beta{1}X{ij} + u{j} + e{ij}$, where $u_{j}$ represents the study-level random effect. Determinants were analysed via multilevel meta-regression, with inference based on 95% confidence intervals and robust variance estimation.", "findings": "The synthesis identified a strong positive association between frontline health worker training completeness and system adoption (pooled odds ratio 2.45, 95% CI 1.88 to 3.19). Organisational-level factors, particularly supply chain reliability, emerged as a more significant thematic predictor of adoption success than individual clinician attitudes.", "conclusion": "Adoption is predominantly driven by modifiable organisational and systemic factors rather than individual user characteristics. This underscores the need for structural interventions over purely behavioural approaches.", "recommendations": "Policy should prioritise strengthening health system enablers, including supply chains and operational management. Future research must employ standardised, multilevel methodologies to generate comparable evidence on implementation processes.", "key words": "health systems research, implementation science, primary health care, multilevel model, meta-regression, adoption determinants", "contribution statement": "This study provides the first application of a multilevel regression meta-analysis to this domain, generating a novel, hierarchical evidence structure that explicitly distinguishes between individual