Implementing a model for improving integrated primary healthcare planning and performance: An effectiveness evaluation of DIVA in Kaduna, Nigeria




Poster session 4 Saturday: Evidence implementation and evaluation


Saturday 16 September 2017 - 12:30 to 14:00


All authors in correct order:

Eboreime E1, Nxumalo N1, Eyles J1
1 Center for Health Policy, School of Public Health, University of the Wit watersrand, South Africa
Presenting author and contact person

Presenting author:

Ejemai Eboreime

Contact person:

Abstract text
Background: To ensure improved performance of primary healthcare (PHC) interventions, Nigeria initiated PHC Reviews in 2011. The reviews are facilitated quarterly evaluations of PHC performance with evidence-based operational planning of interventions by local government (LG) PHC managers using routine data.
Methods: PHC reviews employ a 4-step improvement framework: Diagnose-Intervene-Verify-Adjust (DIVA). ‘Diagnose’ identifies constraints to effective coverage (Figure 1). ‘Intervene’ develops/implements action plans addressing constraints. ‘Verify/Adjust’ monitor performance and revise plans.
We evaluated effectiveness of DIVA in improving PHC bottlenecks in Kaduna, 2013-2016. Kaduna state conducts annual reviews involving all 23 LGs since 2013. The reviews focus on determinants for availability of commodities; human resources; geographical accessibility; initial utilisation; continuous utilisation; and quality of four PHC interventions (Immunisation, integrated management of childhood illnesses, antenatal care, and skilled birth attendance). Our findings are analysed and presented on charts (pie, bar, Pareto and run-charts).
Results/Discussion: 183 bottlenecks were identified by LG teams across all interventions in 2013. 41% of bottlenecks relate to human resources. Geographical access and availability of commodities ranked least (Figures 2 and 3). Of 1562 activities planned to address bottlenecks in the state, 568 (36%) were completely implemented. Availability of commodities was the most improved determinant albeit among the least constrained; probably indicating skewed implementation of operational plans (Figure 4).
Effect of DIVA on performance indicators varied across interventions. While indicators for interventions with strong donor support (malaria and immunisation) improved, less supported Antenatal Care slightly declined, suggesting skewed implementation towards donor interests (Figures 5-7).
Conclusion: Our study demonstrates that bottom-up approach to PHC planning using the DIVA model can potentially improve performance in decentralised sub-Saharan African health systems. However, effective implementation requires some central oversight.