Maturity Assessment of District Health Information System Version 2 Implementation in Ethiopia: Current Status and Improvement Pathways.

BACKGROUND: Although Ethiopia has made remarkable progress in the uptake of the District Health Information System version 2 (DHIS2) for national aggregate data reporting, there has been no comprehensive assessment of the maturity level of the system. OBJECTIVE: This study aims to assess the maturity level of DHIS2 implementation in Ethiopia and propose a road map that could guide the progress toward a higher level of maturity. We also aim to assess the current maturity status, implementation gaps, and future directions of DHIS2 implementation in Ethiopia. The assessment focused on digital health system governance, skilled human resources, information and communication technology (ICT) infrastructure, interoperability, and data quality and use. METHODS: A collaborative assessment was conducted with the engagement of key stakeholders through consultative workshops using the Stages of Continuous Improvement tool to measure maturity levels in 5 core domains, 13 components, and 39 subcomponents. A 5-point scale (1=emerging, 2=repeatable, 3=defined, 4=managed, and 5=optimized) was used to measure the DHIS2 implementation maturity level. RESULTS: The national DHIS2 implementation's maturity level is currently at the defined stage (score=2.81) and planned to move to the manageable stage (score=4.09) by 2025. The domain-wise maturity score indicated that except for ICT infrastructure, which is at the repeatable stage (score=2.14), the remaining 4 domains are at the defined stage (score=3). The development of a standardized and basic DHIS2 process at the national level, the development of a 10-year strategic plan to guide the implementation of digital health systems including DHIS2, and the presence of the required competencies at the facility level to accomplish specific DHIS2-related tasks are the major strength of the Ministry of Health of Ethiopia so far. The lack of workforce competency guidelines to support the implementation of DHIS2; the unavailability of core competencies (knowledge, skills, and abilities) required to accomplish DHIS2 tasks at all levels of the health system; and ICT infrastructures such as communication network and internet connectivity at the district, zonal, and regional levels are the major hindrances to effective DHIS2 implementation in the country. CONCLUSIONS: On the basis of the Stages of Continuous Improvement maturity model toolkit, the implementation status of DHIS2 in Ethiopia is at the defined stage, with the ICT infrastructure domain being at the lowest stage as compared to the other 4 domains. By 2025, the maturity status is planned to move from the defined stage to the managed stage by improving the identified gaps. Various action points are suggested to address the identified gaps and reach the stated maturity level. The responsible body, necessary resources, and methods of verification required to reach the specified maturity level are also listed.

Acceptability and use of the electronic community health information system and its determinants among health extension workers in Ethiopia: a retrospective cross-sectional observational study.

BACKGROUND: The electronic community health information system has been increasingly developed and deployed to quantify and support quality health service delivery by community health workers in Ethiopia. However, the success and failure of the electronic community health information system depend on the acceptability and use by its users. This study assessed the acceptability and use of the electronic community health information system and its determinants among health extension workers in Ethiopia. METHODS: A retrospective cross-sectional observational study was conducted among 587 randomly selected health extension workers from six regions of Ethiopia. The Revised Technology Acceptance Model was used as a theoretical framework for the study. Descriptive statistics, structural equation modeling, and principal component analysis techniques were used to analyze the data. For all significance tests, multiple comparison adjustments were made using the Bonferroni Correction Method. RESULTS: There was near universal acceptance of the electronic community health information system, ranging from 94.4 to 97.4% among health extension workers. However, actual use of the system was considerably lower, at 50%. Perceived usefulness of the electronic community health information system had a direct and positive effect on acceptability (ß3 = 0.415, p < 0.001). Perceived ease of use had both direct and indirect positive effects on electronic community health information system acceptability (ß2 = 0.340, p < 0.001 and ß1*ß3 = 0.289, p < 0.001, respectively), while acceptability had a direct and positive effect on the use of the electronic community health information system (ß3 = 0.297, p < 0.001). CONCLUSIONS: Despite the very high acceptability of the electronic community health information system among health extension workers, actual use of the system is considerably lower. Hence, an integrated and coordinated approach is required to close the acceptance-use gap.

Vaccination Utilization and Subnational Inequities during the COVID-19 Pandemic: An Interrupted Time-Series Analysis of Administrative Data across 12 Low- and Middle-Income Countries.

BACKGROUND: During and after the SARS-CoV-2 (COVID-19) pandemic, many countries experienced declines in immunization that have not fully recovered to pre-pandemic levels. This study uses routine health facility immunization data to estimate variability between and within countries in post-pandemic immunization service recovery for BCG, DPT1, and DPT3. METHODS: After adjusting for data reporting completeness and outliers, interrupted time series regression was used to estimate the expected immunization service volume for each subnational unit, using an interruption point of March 2020. We assessed and compared the percent deviation of observed immunizations from the expected service volume for March 2020 between and within countries. RESULTS: Six countries experienced significant service volume declines for at least one vaccine as of October 2022. The shortfall in BCG service volume was ~6% (95% CI -1.2%, -9.8%) in Guinea and ~19% (95% CI -16%, 22%) in Liberia. Significant cumulative shortfalls in DPT1 service volume are observed in Afghanistan (-4%, 95% CI -1%, -7%), Ghana (-3%, 95% CI -1%, -5%), Haiti (-7%, 95% CI -1%, -12%), and Kenya (-3%, 95% CI -1%, -4%). Afghanistan has the highest percentage of subnational units reporting a shortfall of 5% or higher in DPT1 service volume (85% in 2021 Q1 and 79% in 2020 Q4), followed by Bangladesh (2020 Q1, 83%), Haiti (80% in 2020 Q2), and Ghana (2022 Q2, 75%). All subnational units in Bangladesh experienced a 5% or higher shortfall in DPT3 service volume in the second quarter of 2020. In Haiti, 80% of the subnational units experienced a 5% or higher reduction in DPT3 service volume in the second quarter of 2020 and the third quarter of 2022. CONCLUSIONS: At least one region in every country has a significantly lower-than-expected post-pandemic cumulative volume for at least one of the three vaccines. Subnational monitoring of immunization service volumes using disaggregated routine health facility information data should be conducted routinely to target the limited vaccination resources to subnational units with the highest inequities.

An investigation of a hundred COVID-19 cases and close contacts in Ethiopia, May to June, 2020: A prospective case-ascertained study.

BACKGROUND: Corona Virus Disease 2019 is a novel respiratory disease commonly transmitted through respiratory droplets. The disease has currently expanded all over the world with differing epidemiologic trajectories. This investigation was conducted to determine the basic clinical and epidemiological characteristics of the disease in Ethiopia. METHODS: A prospective case-ascertained study of laboratory-confirmed COVID-19 cases and their close contacts were conducted. The study included 100 COVID-19 laboratory-confirmed cases reported from May 15, 2020 to June 15, 2020 and 300 close contacts. Epidemiological and clinical information were collected using the WHO standard data collection tool developed first-few cases and contacts investigation. Nasopharyngeal and Oropharyngeal samples were collected by using polystyrene tipped swab and transported to the laboratory by viral transport media maintaining an optimal temperature. Clinical and epidemiological parameters were calculated in terms of ratios, proportions, and rates with 95% CI. RESULT: A total of 400 participants were investigated, 100 confirmed COVID-19 cases and 300 close contacts of the cases. The symptomatic proportion of cases was 23% (23) (95% CI: 15.2%-32.5%), the proportion of cases required hospitalization were 8% (8) (95%CI: 3.5%-15.2%) and 2% (95%CI: 0.24% - 7.04%) required mechanical ventilation. The secondary infection rate, secondary clinical attack rate, median incubation period and median serial interval were 42% (126) (95% CI: 36.4%-47.8%), 11.7% (35) (95% CI: 8.3%-15.9%), 7 days (IQR: 4-13.8) and 11 days (IQR: 8-11.8) respectively. The basic reproduction number (RO) was 1.26 (95% CI: 1.0-1.5). CONCLUSION: The proportion of asymptomatic infection, as well as secondary infection rate among close contacts, are higher compared to other studies. The long serial interval and low basic reproduction number might contribute to the observed slow progression of the pandemic, which gives a wide window of opportunities and time to control the spread. Testing, prevention, and control measures should be intensified.

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.

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

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.

Healthcare utilization and maternal and child mortality during the COVID-19 pandemic in 18 low- and middle-income countries: An interrupted time-series analysis with mathematical modeling of administrative data.

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) pandemic has had wide-reaching direct and indirect impacts on population health. In low- and middle-income countries, these impacts can halt progress toward reducing maternal and child mortality. This study estimates changes in health services utilization during the pandemic and the associated consequences for maternal, neonatal, and child mortality. METHODS AND FINDINGS: Data on service utilization from January 2018 to June 2021 were extracted from health management information systems of 18 low- and lower-middle-income countries (Afghanistan, Bangladesh, Cameroon, Democratic Republic of the Congo (DRC), Ethiopia, Ghana, Guinea, Haiti, Kenya, Liberia, Madagascar, Malawi, Mali, Nigeria, Senegal, Sierra Leone, Somalia, and Uganda). An interrupted time-series design was used to estimate the percent change in the volumes of outpatient consultations and maternal and child health services delivered during the pandemic compared to projected volumes based on prepandemic trends. The Lives Saved Tool mathematical model was used to project the impact of the service utilization disruptions on child and maternal mortality. In addition, the estimated monthly disruptions were also correlated to the monthly number of COVID-19 deaths officially reported, time since the start of the pandemic, and relative severity of mobility restrictions. Across the 18 countries, we estimate an average decline in OPD volume of 13.1% and average declines of 2.6% to 4.6% for maternal and child services. We projected that decreases in essential health service utilization between March 2020 and June 2021 were associated with 113,962 excess deaths (110,686 children under 5, and 3,276 mothers), representing 3.6% and 1.5% increases in child and maternal mortality, respectively. This excess mortality is associated with the decline in utilization of the essential health services included in the analysis, but the utilization shortfalls vary substantially between countries, health services, and over time. The largest disruptions, associated with 27.5% of the excess deaths, occurred during the second quarter of 2020, regardless of whether countries reported the highest rate of COVID-19-related mortality during the same months. There is a significant relationship between the magnitude of service disruptions and the stringency of mobility restrictions. The study is limited by the extent to which administrative data, which varies in quality across countries, can accurately capture the changes in service coverage in the population. CONCLUSIONS: Declines in healthcare utilization during the COVID-19 pandemic amplified the pandemic's harmful impacts on health outcomes and threaten to reverse gains in reducing maternal and child mortality. As efforts and resource allocation toward prevention and treatment of COVID-19 continue, essential health services must be maintained, particularly in low- and middle-income countries.

Effect of data quality improvement intervention on health management information system data accuracy: An interrupted time series analysis.

BACKGROUND: As part of a partnership between the Institute for Healthcare Improvement and the Ethiopian Federal Ministry of Health, woreda-based quality improvement collaboratives took place between November 2016 and December 2017 aiming to accelerate reduction of maternal and neonatal mortality in Lemu Bilbilu, Tanqua Abergele and Duguna Fango woredas. Before starting the collaboratives, assessments found inaccuracies in core measures obtained from Health Management Information System reports. METHODS AND RESULTS: Building on the quality improvement collaborative design, data quality improvement activities were added and we used the World Health Organization review methodology to drive a verification factor for the core measures of number of pregnant women that received their first antenatal care visit, number of pregnant women that received antenatal care on at least four visits, number of pregnant women tested for syphilis and number of births attended by skilled health personnel. Impact of the data quality improvement was assessed using interrupted time series analysis. We found accurate data across all time periods for Tanqua Abergele. In Lemu Bilbilu and Duguna Fango, data quality improved for all core metrics over time. In Duguna Fango, the verification factor for number of pregnant women that received their first antenatal care visit improved from 0.794 (95%CI 0.753, 0.836; p<0.001) pre-intervention by 0.173 (95%CI 0.128, 0.219; p<0.001) during the collaborative; and the verification factor for number of pregnant women tested for syphilis improved from 0.472 (95%CI 0.390, 0.554; p<0.001) pre-intervention by 0.460 (95%CI 0.369, 0.552; p<0.001) during the collaborative. In Lemu Bilbilu, the verification factor for number of pregnant women receiving a fourth antenatal visit rose from 0.589 (95%CI 0.513, 0.664; p<0.001) at baseline by 0.358 (95%CI 0.258, 0.458; p<0.001) post-intervention; and skilled birth attendance rose from 0.917 (95%CI 0.869, 0.965) at baseline by 0.083 (95%CI 0.030, 0.136; p<0.001) during the collaborative. CONCLUSIONS: A Data quality improvement initiative embedded within woreda clinical improvement collaborative improved accuracy of data used to monitor maternal and newborn health services in Ethiopia.