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Drivers and Barriers to Improved Data Quality and Data-Use Practices: An Interpretative Qualitative Study in Addis Ababa, Ethiopia

September 15, 2022

Introduction: An objective of the Information Revolution Roadmap of Ethiopia's Health Sector Transformation Plan was to improve health management information system (HMIS) data quality and data use at the point of health service delivery. We aimed to assess drivers of and barriers to improving HMIS data quality and use, focusing on key Information Revolution strategies including Connected Woreda, capacity building, performance monitoring teams, and motivational incentives.Methods: We conducted an interpretative qualitative study across all 11 health centers in 3 subcities of Addis Ababa, Ethiopia: Yeka, Akaki-Kaliti, and Ledeta. A total of 40 key informant interviews and 6 focus group discussions with a total of 43 discussants were conducted. We coded information gathered line-by-line and grouped responses under thematic codes as they emerged. Findings were triangulated and validated.Results: Our findings indicate that the main drivers of data quality and use at the point of service delivery were the use of the Connected Woreda strategy and its tools, capacity-building activities including mentorship, performance monitoring-team activities that led to active leadership engagement, and motivational incentives for data producers and users. Barriers to optimal data-use practices were the use of duplicative data collection tools at health facilities, under-developed health information system infrastructure, inadequate health information technician staffing and capacity limitations at the health facility level, insufficient leadership commitment, and unfavorable health worker attitudes toward data.Discussion: Improvements in quality and use of HMIS data at health facilities are expected to result in delivering better-quality health services to the community as data enable health workers to identify gaps in health care, fix them, and monitor improvements. Future investments should focus on strengthening the promising data-use practices, resolving bottlenecks caused by duplicative data collection tools, enhancing individual and institutional capacity, addressing suboptimal health worker attitudes toward data, and overcoming infrastructure and connectivity challenges.

Lessons Learned From the Capacity-Building and Mentorship Program to Improve Health Information Systems in 11 Districts of Ethiopia

September 15, 2022

Introduction: Health information systems (HIS) performance in Ethiopia is currently insufficient, and improvements are required to ensure that decision making is data driven. We share our experiences from the early-stage implementation of a package of HIS capacity-strengthening interventions as part of an innovative academic-government collaboration that addresses challenges in HIS performance.Methods: We used routine program data to assess HIS performance using the Performance of Routine Information System Management (PRISM) assessment tools. The assessment employed a pre-post design and was conducted in a total of 24 selected health facilities (6 hospitals and 18 health centers) from 11 districts in Ethiopia at project baseline (2018) and midline (2020).Results: Source document completeness rate reached less than 80% for the majority of the assessed data elements. Improvements were observed in quarterly report completeness (26% vs. 83%) and timeliness (17% vs. 48%). Though data inaccuracies are noted for all assessed data elements in 2020, the majority (83%) of skilled birth attendance and HIV reports (68%) fall within the acceptable range of reporting accuracy. The identification of performance-related problems, using performance monitoring team (PMT) meetings, improved between 2018 and 2020 (67% vs 89%). Similar improvements were also observed in developing action plans to solve identified problems via the PMT (52% in 2018 vs. 89% in 2020). Data use for planning and target setting (65% in 2018 vs. 90% in 2020), reviewing performance (58% in 2018 vs. 60% in 2020), and supervision (51% in 2018 vs. 53% in 2020) all improved among assessed health facilities.Discussion: This study showed that a capacity-building and mentorship program that engages experts from multiple disciplines and sectors can improve the quality and use of health data. This partnership enabled engagement between government and academic stakeholders and allowed for a more robust exchange of resources and expertise toward HIS improvement.

Maternal Service Coverage and Its Relationship To Health Information System Performance: A Linked Facility and Population-Based Survey in Ethiopia

September 15, 2022

Background: Studies in Ethiopia show an increasing trend in maternal health service use, such as having at least 4 visits of antenatal care (ANC4+) and skilled birth attendance (SBA). Improving the health information system (HIS) is an intervention that can improve service uptake and quality. We conducted a baseline study to measure current maternal service coverage, HIS performance status, and their relationship.Methods: We conducted a linked health facility-level and population-based survey from September 2020 to October 2020. The study covers all regions of Ethiopia. For the population-based survey, 3,016 mothers were included. Overall, 81 health posts, 71 health centers, and 15 hospitals were selected for the facility survey. A two-stage sampling procedure was applied to select target households. The study used modified Performance of Routine Information System Management tools for the facility survey and a structured questionnaire for the household survey. Multilevel logistic regression was employed to account for clustering and control for likely confounders.Results: Maternal service indicators, ANC4+ visits (54.0%), SBA (75.8%), postnatal care (70.6%), and cesarean delivery (9%) showed good service uptake. All data quality and use indicators showed lower performance compared to the national target of 90%. Maternal education and higher levels of wealth index were significantly and positively associated with all selected maternal service indicators. Longer distance from health facilities was significantly and negatively associated with SBA and the maternal care composite indicator. Among HIS-related indicators, availability of electronic HIS tools was significantly associated with maternal care composite indicator and ANC4+.Conclusions: Maternal service indicators showed promising performance. However, current HIS performance is suboptimal. Both service user and HIS-related factors were associated with maternal service uptake. Conducting similar research outside of the project sites will be helpful to have a wider understanding and better coverage.