Patterns of essential health services utilization and routine health information management during Covid-19 pandemic at primary health service delivery point Addis Ababa, Ethiopia.

AbstractBackground: Health information system refers to any system that captures, stores, manages, and transmit information related to health of individuals. The essential health service includes Antenatal care, skilled birth attendant, emergency, outpatient, Inpatient, Pneumonia, and Immunization. The current pandemic of coronavirus disease (COVID-19) has proved devastating in low-income countries, which were already suffering from low access for basic health service utilization. The pandemic might generate disruptive collateral damage to ongoing healthcare services through diverting available healthcare resources to the fight against the pandemics in these countries. This study aimed to assess the pattern of essential health services utilization, data accuracy checking, and information use performance review practice at selected public health center in Addis Ababa Ethiopia. Methods: We employed cross-sectional study and retrospectively reviewed health records to assess the pattern of selected essential health service utilization, data quality, and performance review practice before and during the COVID-19 pandemic. Out of twenty-seven health centers, nine health centers were randomly selected from three sub-cities to review key indicators using a guiding checklist. Data were extracted using record verification protocol. Data was entered, cleaned, and analyzed using STATA version 14. We used average change in proportions to describe the pattern of service utilization, data quality and performance review practice before and during COVID 19. The mean difference before and during COVID 19 was compared using paired T-test statistics. Result: Essential health services utilization has been partially or completely disrupted in the selected health centers. Pneumonia (70%), Upper respiratory diseases (65%), PICT (54%), Out-patient (42%), and 39% for data quality and performance review practice (39%) showed significant reduction during COVID 19 cases reported in the country. ANC1, ANC4, Penta1, and Penta4 service show almost in a similar trend from month to month before and during COVID-19. Conclusion: Service utilization like emergency, out-of-patient, and VCT cases significantly reduced during COVID-19 pandemic. During the COVID-19 pandemic, routine data accuracy checks, and RHIS performance reviews practice were also significantly reduced. [Ethiop. J. Health Dev. 2021; 35(SI-1):90-97] Key words: Data quality, data use, health service utilizatio

Routine health management information system data in Ethiopia: consistency, trends, and challenges.

Background: Ethiopia is investing in the routine Health Management Information System. Improved routine data are needed for decision-making in the health sector. Objective: To analyse the quality of the routine Health Management Information System data and triangulate with other sources, such as the Demographic and Health Surveys. Methods: We analysed national Health Management Information System data on 19 indicators of maternal health, neonatal survival, immunization, child nutrition, malaria, and tuberculosis over the 2012-2018 time period. The analyses were conducted by 38 analysts from the Ministry of Health, Ethiopia, and two government agencies who participated in the Operational Research and Coaching for Analysts (ORCA) project between June 2018 and June 2020. Using a World Health Organization Data Quality Review toolkit, we assessed indicator definitions, completeness, internal consistency over time and between related indicators, and external consistency compared with other data sources. Results: Several services reported coverage of above 100%. For many indicators, denominators were based on poor-quality population data estimates. Data on individual vaccinations had relatively good internal consistency. In contrast, there was low external consistency for data on fully vaccinated children, with the routine Health Management Information System showing 89% coverage but the Demographic and Health Survey estimate at 39%. Maternal health indicators displayed increasing coverage over time. Indicators on child nutrition, malaria, and tuberculosis were less consistent. Data on neonatal mortality were incomplete and operationalised as mortality on day 0-6. Our comparisons with survey and population projections indicated that one in eight early neonatal deaths were reported in the routine Health Management Information System. Data quality varied between regions. Conclusions: The quality of routine data gathered in the health system needs further attention. We suggest regular triangulation with data from other sources. We recommend addressing the denominator issues, reducing the complexity of indicators, and aligning indicators to international definitions

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

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

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

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

Exploring data quality and use of the routine health information system in Ethiopia: a mixed-methods study.

OBJECTIVE: A routine health information system (RHIS) enables decision making in the healthcare system. We aimed to analyse data quality at the district and regional level and explore factors and perceptions affecting the quality and use of routine data. DESIGN: This was a mixed-methods study. We used the WHO toolkit for analysing data quality and interviewed staff at the point of data generation and along with the flow of data. Data were analysed using the Performance of Routine Information System Management framework. SETTING: This study was performed in eight districts in four regions of Ethiopia. The study was nested within a 2-year programme of the Operational Research and Coaching for government Analysts. PARTICIPANTS: We visited 45 health posts, 1 district hospital, 16 health centres and 8 district offices for analysis of routine RHIS data and interviewed 117 staff members for the qualitative assessment. OUTCOME MEASURES: We assessed availability of source documents, completeness, timeliness and accuracy of reporting of routine data, and explored data quality and use perceptions. RESULTS: There was variable quality of both indicator and data element. Data on maternal health and immunisation were of higher quality than data on child nutrition. Issues ranged from simple organisational factors, such as availability of register books, to intricate technical issues, like complexity of indicators and choice of denominators based on population estimates. Respondents showed knowledge of the reporting procedures, but also demonstrated limited skills, lack of supportive supervision and reporting to please the next level. We saw limited examples of the use of data by the staff who were responsible for data reporting. CONCLUSION: We identified important organisational, technical, behavioural and process factors that need further attention to improve the quality and use of RHIS data in Ethiopia