Effectiveness of the Diagnose-Intervene- Verify-Adjust (DIVA) model for integrated primary healthcare planning and performance improvement: an embedded mixed methods evaluation in Kaduna state, Nigeria
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ObjectivesThis study evaluates the real-world effectiveness of Diagnose-Intervene-Verify-Adjust (DIVA), an innovative quality improvement mode, in improving primary healthcare (PHC) bottlenecks impeding health system performance in Kaduna, a northern Nigerian state.DesignAn embedded mixed method study design involving participant observation.SettingPHCs in 23 local government areas of Kaduna state, Nigeria.Participants138 PHC managers across the state (PHC directors and programme managers in the 23 local governments).InterventionDIVA is a four-step improvement model in which ‘Diagnose’ identifies constraints to effective coverage, ‘Intervene’ develops/implements action plans addressing constraints, while ‘Verify/Adjust’ monitor performance and revise plans.Primary and secondary outcome measuresThe model, as adapted in Nigeria, is designed to evaluate and improve the availability of health commodities, human resources, geographical accessibility, acceptability, continuous utilisation and quality of four PHC interventions (immunisation, integrated management of childhood illnesses, antenatal care and skilled birth attendance).Results183 bottlenecks were identified by local government teams across all interventions in 2013. 41% of bottlenecks concern human resources. Geographical access and availability of commodities ranked least. Availability of commodities was the most improved determinant although among the least constrained, probably indicating skewed implementation of operational plans. 1562 activities were planned to address identified bottlenecks in the state, of which only 568 (36%) were completely implementedConclusionOur study demonstrates that PHC planning using the DIVA model can potentially improve health system performance. However, effective implementation is critical and may require some central government oversight.
