Stillbirth and newborn data quality and use and related input and process factors
Findings of the Impulse study in Ethiopia
Bibliographic Data
Background: High quality data is mandatory when shaping action-oriented policies aimed at reducing preventable neonatal deaths. Ethiopia has a high a neonatal mortality rate, but there has been limited assessment of the quality and use of newborn data, and its contributing factors. Methods: We conducted a cross-sectional study in Ethiopia from November 2022 to September 2023 in 35 sites: 24 facilities, 10 subnational data offices, and the Ministry of Health. We collected data using Every Newborn - Measurement Improvement for Newborn & Stillbirth Indicators tools and analysed them per the Performance of Routine Information System Management User's Kit. Results: The major strengths identified in our analysis included governance at subnational data offices (80-90%), use of quality improvement standards (100%), supervision quality (100%) in data offices, sites with internet access (92-100%), routine health information system (RHIS) designated staff (100%), data management in data offices (62-100%), data availability and completeness (91-98%) for denominator elements (total births, live births), and use of data to produce reports in data offices (100%). Regarding key gaps, data accuracy (registers vs. District Health Information Software 2) was low on all 10 newborn indicators (11-67%), while data use for performance review was suboptimal (≤90%) at both in facilities (12-66%) and data offices (21-90%). Key weaknesses in input and process factors included only 40% of data offices having a long-term financial plan for supporting RHIS, 8% of data offices and 16% of facilities having the minimum item bundle in working conditions, few sites having supplies of recording/reporting tools (15-68%, depending on the item), and supervision quality (58-62%), staff skills to perform RHIS tasks (16-40%), and data management (46-75%) being particularly low in facilities. An average of 57% of end users reported a need for improvement in the quality and use of newborn data, as well as in the studied enabling factors. Conclusions: Our findings highlight the specific strengths and weaknesses that need to be addressed to improve data quality and use in the assessed sample in Ethiopia.
Christian ministry · Data collection · Data governance · Data management · Data quality · Health care · Quality (philosophy) · Quality management · Raw data · Global Maternal and Child Health · Maternal and fetal healthcare · Maternal and Neonatal Healthcare
The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement
Facility newborn and stillbirth data use and enabling factors at different levels of the health system
Users’ capabilities related to the electronic RHIS for newborn and stillbirth indicators
Functionalities of electronic routine health information systems related to newborn data
Organisational and management factors and related end-users’ perspectives relevant to newborn and stillbirth data at different levels of the health system
Availability and the quality of key newborn data within routine health facility data
Quality of routine health facility data used for newborn indicators in low- and middle-income countries
Routine health management information system data in Ethiopia
“We don’t trust all data coming from all facilities”
PRISM framework
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