Effects of Results Based Financing Models on Data Quality Improvement in Benin on 2014

Abstract The performances generated by results based financing (RBF) raise questions about the quality of data used to measure them. This study was carried out to evaluate the RBF contribution to the quality improvement of maternal and child health data. Sixty seven health facilities are sampled randomly in three strata (RBF_PRPSS, RBF_PASS, No_ RBF) gathering health zones in Benin. The strata comparison with maternal and child health data for the first halves 2014 and 2011 revealed that timeliness and completeness have improved in the strata exposed to results based financing compared to unexposed (p <0.05). Compared to No_RBF stratum, accuracy deteriorated in RBF_PRPSS stratum, with a 52% decrease in the proportion of concordance reports between 2011 and 2014. In 2014, recorded discrepancies are largely under-reported in the RBF_PRPSS stratum, and over-reported in RBF_PASS stratum. The accuracy of National Health Information and Management System (SNIGS) data compared to RBF's validated data was low, verification factors varying between 30% and 97%. In total, the data quality was globally poor in most areas in Benin and it is not improved by the results based financing models implemented between 2011 and 2014. There is a need to target data quality in RBF models and to use SNIGS as a unique system of reporting