"We don't trust all data coming from all facilities": factors influencing the quality of care network data quality in Ethiopia.

BACKGROUND: Good quality data are a key to quality health care. In 2017, WHO has launched the Quality of Care Network (QCN) to reduce maternal, newborn and stillbirth mortality via learning and sharing networks. Guided by the principle of equity and dignity, the network members agreed to implement the programme in 2017-2021. OBJECTIVE: This paper seeks to explore how QCN has contributed to improving data quality and to identify factors influencing quality of data in Ethiopia. METHODS: We conducted a qualitative study in selected QCN facilities in Ethiopia using key informant interview and observation methods. We interviewed 40 people at national, sub-national and facility levels. Non-participant observations were carried out in four purposively selected health facilities; we accessed monthly reports from 41 QCN learning facilities. A codebook was prepared following a deductive and inductive analytical approach, coded using Nvivo 12 and thematically analysed. RESULTS: There was a general perception that QCN had improved health data documentation and use in the learning facilities, achieved through coaching, learning and building from pre-existing initiatives. QCN also enhanced the data elements available by introducing a broader set of quality indicators. However, the perception of poor data quality persisted. Factors negatively affecting data quality included a lack of integration of QCN data within routine health system activities, the perception that QCN was a pilot, plus a lack of inclusive engagement at different levels. Both individual and system capabilities needed to be strengthened. CONCLUSION: There is evidence of QCN's contribution to improving data awareness. But a lack of inclusive engagement of actors, alignment and limited skill for data collection and analysis continued to affect data quality and use. In the absence of new resources, integration of new data activities within existing routine health information systems emerged as the most important potential action for positive change.

Triangulating data sources for further learning from and about the MDSR in Ethiopia: a cross-sectional review of facility based maternal death data from EmONC assessment and MDSR system.

BACKGROUND: Triangulating findings from MDSR with other sources can better inform maternal health programs. A national Emergency Obstetric and Newborn Care (EmONC) assessment and the Maternal Death Surveillance and Response (MDSR) system provided data to determine the coverage of MDSR implementation in health facilities, the leading causes and contributing factors to death, and the extent to which life-saving interventions were provided to deceased women. METHODS: This paper is based on triangulation of findings from a descriptive analysis of secondary data extracted from the 2016 EmONC assessment and the MDSR system databases. EmONC assessment was conducted in 3804 health facilities. Data from interview of each facility leader on MDSR implementation, review of 1305 registered maternal deaths and 679 chart reviews of maternal deaths that happened form May 16, 2015 to December 15, 2016 were included from the EmONC assessment. Case summary reports of 601 reviewed maternal deaths were included from the MDSR system. RESULTS: A maternal death review committee was established in 64% of health facilities. 5.5% of facilities had submitted at least one maternal death summary report to the national MDSR database. Postpartum hemorrhage (10-27%) and severe preeclampsia/eclampsia (10-24.1%) were the leading primary causes of maternal death. In MDSR, delay-1 factors contributed to 7-33% of maternal deaths. Delay-2, related to reaching a facility, contributed to 32% & 40% of maternal deaths in the EmONC assessment and MDSR, respectively. Similarly, delay-3 factor due to delayed transfer of mothers to appropriate level of care contributed for 29 and 22% of maternal deaths. From the EmONC data, 72% of the women who died due to severe pre-eclampsia or eclampsia were given anticonvulsants while 48% of those dying of postpartum haemorrhage received uterotonics. CONCLUSION: The facility level implementation coverage of MDSR was sub-optimal. Obstetric hemorrhage and severe preeclampsia or eclampsia were the leading causes of maternal death. Delayed arrival to facility (Delay 2) was the predominant contributing factor to facility-based maternal deaths. The limited EmONC provision should be the focus of quality improvement in health facilities.