A paper authored by IDEAS team member Antoinette Bhattacharya and published as part of a series on High Quality Health Systems in PLOS ONE aims to determine the quality of routine health facility-based data in DHIS2 for maternal and newborn health services in Gombe state, Nigeria.

Good quality routine facility-based data can contribute to reliable estimates showing whether women and newborns are accessing and receiving routine services.

This case study looked at priority maternal and neonatal health indicators in Gombe State, using the World Health Organization data quality review toolkit. Three dimensions of data quality were assessed – namely: completeness and timeliness, internal consistency, and external consistency. Data from three sources were used: facility-reported data in DHIS2, an external facility survey, and an external household survey.

Results from the study show that of 14 priority maternal and neonatal health indicators that could be tracked through facility-based data, 12 were included in Gombe’s DHIS2. During the time period studied, facility-reported data in DHIS2 were incomplete at least 40% of the time, under-reported 10%-60% of the events documented in facility registers, and showed inconsistencies over time, between related indicators, and with an external data source.  The best quality data elements were those that aligned with Gombe’s health program priorities, particularly older health programs, and those that reflected contact indicators rather than indicators related to the provision of commodities or content of care.

The paper concludes that the DHIS2 is potentially highly effective for monitoring of maternal and newborn health care if coordinated actions are taken to maximize the reporting of existing data. Moreover, further work is needed to rationalize data flow; routinize data quality review, feedback, and supervision; and ensure ongoing maintenance of DHIS2.