Determinant Risk Factors for Continuous Quality Improvement (CQI) in Primary Health Care (PHC) Systems in Kogi State

Abstract

Continuous Quality Improvement (CQI) is a systems-based, Kaizen-inspired approach that strengthens Primary Health Care (PHC) through iterative Plan-Do-Study-Act (PDSA) cycles, routine data use, and stakeholder engagement. In Kogi State, Nigeria, a cross-sectional mixed-methods assessment of n=96 PHC facilities applied epidemiologic and implementation science methods to identify determinant risk factors for CQI performance. Data sources included IMPACT RISS supervision reports, DHIS2 extracts, and program documents (2023–2025), analyzed using chi-square tests, Pearson correlations, logistic regression, multilevel mixed-effects models, and MANOVA.
Facility readiness was operationalized as a composite index of WASH, power, and cold-chain infrastructure was strongly correlated with immunization coverage (r = 0.62), and each 10-point increase in readiness raised the odds of high CQI uptake by ~35% (aOR ≈ 1.35). Cold-chain failure nearly doubled zero-dose risk (RR ≈ 1.90; aOR ≈ 1.8), functioning as a critical control point in the CQI pathway. Workforce stability, proxied by staff accommodation, was associated with a two-fold increase in CQI uptake (aOR ≈ 2.05), reinforcing its role as a sustaining factor. Process innovations such as geo-tagged supervision (aOR ≈ 1.6) and settlement-level monitoring emerged as mediators that translated readiness into improved service delivery. Environmental risk (aOR ≈ 0.70) and LGA-level clustering (ICC ≈ 0.16) moderated CQI effectiveness, highlighting the importance of context in shaping outcomes.
These findings support a causal logic in which structural readiness enables process improvements, workforce stability sustains gains, and socio-ecological alignment enhances resilience. The study’s Theory of Change posits that CQI success is conditional on the interaction between readiness, process fidelity, and contextual adaptation. Translating these coefficients into program targets such as cold-chain uptime, staff retention, and geo-tagged supervision coverage can guide scalable, equity-focused CQI strategies. Institutionalizing the data-to-action loop, embedding environmental risk into microplanning, and formalizing PDSA cycles at the facility level are essential for sustaining improvements. This study offers a replicable framework for implementing Kaizen-based CQI in PHC systems across similar low-resource settings.