Random Follow-up Visits to Generate Timely Data for Annual Program Outcome Monitoring

Data is a powerful tool for evidence-based decision-making, and is critical for adaptive, responsive programming. In Ethiopia, service-based data are the most accessible data for decision-making during a project’s life cycle, it is limited in its practical utility because of day-to-day challenges to the completeness, timeliness, representativeness, and accuracy of the data captured. The Integrated Family Health Program (IFHP) in Ethiopia developed an intervention to foster the generation and use of data for adaptive programming and better health outcomes. The RFUV approach is an internal program monitoring intervention that relies upon the collaboration of different levels of program stakeholders to generate and learn from data, and to produce strategic information for program managers for timely and informed adaptations. A marked increase in some key outcome indicators was observed in the IFHP target areas after eight and half years of program implementation and it is likely that IFHP contributed to these remarkable changes in its catchment areas. This case discusses the design and the contributions of the RFUV approach to enabling the responsive, iterative implementation that has taken place over the IFHP life cycle and continues today.