Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Adane A

PROVIDER: S-EPMC7833046 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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

Adane Abyot A Adege Tewabe M TM Ahmed Mesoud M MM Anteneh Habtamu A HA Ayalew Emiamrew S ES Berhanu Della D Berhanu Netsanet N Beyene Misrak G MG Bhattacharya Antoinette A Bishaw Tesfahun T Cherinet Eshetu E Dereje Mamo M Desta Tsega H TH Dibabe Abera A Firew Heven S HS Gebrehiwot Freweini F Gebreyohannes Etenesh E Gella Zenebech Z Girma Addis A Halefom Zuriash Z Jama Sorsa F SF Kemal Binyam B Kiflom Abyi A Källestål Carina C Lemma Seblewengel S Mazengiya Yidnekachew D YD Mekete Kalkidan K Mengesha Magdelawit M Nega Meresha W MW Otoro Israel A IA Schellenberg Joanna J Taddele Tefera T Tefera Gulilat G Teketel Admasu A Tesfaye Miraf M Tsegaye Tsion T Woldesenbet Kidist K Wondarad Yakob Y Yosuf Zemzem M ZM Zealiyas Kidist K Zeweli Mebratom H MH Persson Lars Åke LÅ Janson Annika A

Global health action 20210101 1

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, chil ...[more]

PMID: 33446081

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Project description:Health management information system (HMIS) data are important for guiding the attainment of health targets in low- and middle-income countries. However, the quality of HMIS data is often poor. High-quality information is especially important for populations experiencing high burdens of disease and mortality, such as pregnant women, newborns, and children. The purpose of this study was to assess the quality of maternal and child health (MCH) data collected through the Ethiopian Ministry of Health's HMIS in three districts of Jimma Zone, Oromiya Region, Ethiopia over a 12-month period from July 2014 to June 2015. Considering data quality constructs from the World Health Organization's data quality report card, we appraised the completeness, timeliness, and internal consistency of eight key MCH indicators collected for all the primary health care units (PHCUs) located within three districts of Jimma Zone (Gomma, Kersa and Seka Chekorsa). We further evaluated the agreement between MCH service coverage estimates from the HMIS and estimates obtained from a population-based cross-sectional survey conducted with 3,784 women who were pregnant in the year preceding the survey, using Pearson correlation coefficients, intraclass correlation coefficients (ICC), and Bland-Altman plots. We found that the completeness and timeliness of facility reporting were highest in Gomma (75% and 70%, respectively) and lowest in Kersa (34% and 32%, respectively), and observed very few zero/missing values and moderate/extreme outliers for each MCH indicator. We found that the reporting of MCH indicators improved over time for all PHCUs, however the internal consistency between MCH indicators was low for several PHCUs. We found poor agreement between MCH estimates obtained from the HMIS and the survey, indicating that the HMIS may over-report the coverage of key MCH services, namely, antenatal care, skilled birth attendance and postnatal care. The quality of MCH data within the HMIS at the zonal level in Jimma, Ethiopia, could be improved to inform MCH research and programmatic efforts.

Project description:Mortality statistics form a crucial component of national Health Management Information Systems (HMIS). However, there are limitations in the availability and quality of mortality data at national level in Viet Nam. This study assessed the completeness of recorded deaths and the reliability of recorded causes of death (COD) in the A6 death registers in the national routine HMIS in Viet Nam.1477 identified deaths in 2014 were reviewed in two provinces. A capture-recapture method was applied to assess the completeness of the A6 death registers. 1365 household verbal autopsy (VA) interviews were successfully conducted, and these were reviewed by physicians who assigned multiple and underlying cause of death (UCOD). These UCODs from VA were then compared with the CODs recorded in the A6 death registers, using kappa scores to assess the reliability of the A6 death register diagnoses. The overall completeness of the A6 death registers in the two provinces was 89.3% (95%CI: 87.8-90.8). No COD recorded in the A6 death registers demonstrated good reliability. There is very low reliability in recording of cardiovascular deaths (kappa for stroke = 0.47 and kappa for ischaemic heart diseases = 0.42) and diabetes (kappa = 0.33). The reporting of deaths due to road traffic accidents, HIV and some cancers are at a moderate level of reliability with kappa scores ranging between 0.57-0.69 (p<0.01). VA methods identify more specific COD than the A6 death registers, and also allow identification of multiple CODs.The study results suggest that data completeness in HMIS A6 death registers in the study sample of communes was relatively high (nearly 90%), but triangulation with death records from other sources would improve the completeness of this system. Further, there is an urgent need to enhance the reliability of COD recorded in the A6 death registers, for which VA methods could be effective. Focussed consultation among stakeholders is needed to develop a suitable mechanism and process for integrating VA methods into the national routine HMIS A6 death registers in Viet Nam.

Project description:Using reliable information from routine health information systems over time is an important aid to improving health outcomes, tackling disparities, enhancing efficiency, and encouraging innovation. In Ethiopia, routine health information utilization for enhancing performance is poor among health workers, especially at the peripheral levels of health facilities. Therefore, this study aimed to assess routine health information system utilization and associated factors among health workers at government health institutions in East Gojjam Zone, Northwest Ethiopia.An institution based cross-sectional study was conducted at government health institutions of East Gojjam Zone, Northwest Ethiopia from April to May, 2013. A total of 668 health workers were selected from government health institutions, using the cluster sampling technique. Data collected using a standard structured and self-administered questionnaire and an observational checklist were cleaned, coded, and entered into Epi-info version 3.5.3, and transferred into SPSS version 20 for further statistical analysis. Variables with a p-value of less than 0.05 at multiple logistic regression analysis were considered statistically significant factors for the utilization of routine health information systems.The study revealed that 45.8% of the health workers had a good level of routine health information utilization. HMIS training [AOR = 2.72, 95% CI: 1.60, 4.62], good data analysis skills [AOR = 6.40, 95%CI: 3.93, 10.37], supervision [AOR = 2.60, 95% CI: 1.42, 4.75], regular feedback [AOR = 2.20, 95% CI: 1.38, 3.51], and favorable attitude towards health information utilization [AOR = 2.85, 95% CI: 1.78, 4.54] were found significantly associated with a good level of routine health information utilization.More than half of the health workers working at government health institutions of East Gojjam were poor health information users compared with the findings of others studies. HMIS training, data analysis skills, supervision, regular feedback, and favorable attitude were factors related to routine health information system utilization. Therefore, a comprehensive training, supportive supervision, and regular feedback are highly recommended for improving routine health information utilization among health workers at government health facilities.

Project description:BACKGROUND:The utilization of routine health information is an essential factor of the structural capacity of health departments and public health performance depends on the effectiveness of information use for routine and programed decisions. Considerable research has been conducted in health data collection and ways to improve data quality, but little is known about utilization of routine health information among health workers in Ethiopia in general and in the study area in particular. OBJECTIVES:The aim of this study was to assess level of utilization of routine health information and associated factors among health workers in Hadiya zone, Southern Ethiopia, 2019. METHODS AND MATERIALS:Facility-based cross-sectional study design with both quantitative and qualitative data collection methods was employed at the Hadiya zone from March 10-25, 2019. A total of 480 health workers were included in the study and systematic random sampling was employed to select the health care workers in the study. The results were analyzed and presented in tables and graphs. Finally, the binary logistic regression was used to examine independent predictors. RESULT:Good level of utilization of routine health information was reported by 301 (62.7%, 95% CI: 58.5%-66.9%) of the health workers. Training [AOR = 8.12; 95% CI: (4.33-15.23)], supportive supervision [AOR = 2.34; 95% CI:(1.40-3.92)], good perceived culture of health information [AOR = 5.05; 95% CI: (2.99-8.50], having a standard set of indicators (AOR = 2.05 95%; CI: (1.23-3.41) and competence on routine health information tasks [AOR = 5.85; 95% CI: (3.41-10.02)] were independent predictors. CONCLUSION:Good level of utilization of routine health information was noted in less than two-third of the study participants. Further training, supportive supervision, perceived culture of health information, having standard set of indicators and competence on routine health information task were factors that improve routine health information utilization.

Project description:BackgroundQuality data from Health Management Information Systems (HMIS) are important for tracking the effectiveness of malaria control interventions. However, HMIS data in many resource-limited settings do not currently meet standards set by the World Health Organization (WHO). We aimed to assess HMIS data quality and associated factors in Chad.MethodsA cross-sectional study was conducted in 14 health facilities in Massaguet district. Data on children under 15 years were obtained from the HMIS and from the external patient register covering the period January-December 2018. An additional questionnaire was administered to 16 health centre managers to collect data on contextual variables. Patient registry data were aggregated and compared with the HMIS database at district and health centre level. Completeness and accuracy indicators were calculated as per WHO guidelines. Multivariate logistic regressions were performed on the Verification Factor for attendance, suspected and confirmed malaria cases for three age groups (1 to < 12 months, 1 to < 5 years and 5 to < 15 years) to identify associations between health centre characteristics and data accuracy.ResultsHealth centres achieved a high level of data completeness in HMIS. Malaria data were over-reported in HMIS for children aged under 15 years. There was an association between workload and higher odds of inaccuracy in reporting of attendance among children aged 1 to < 5 years (Odds ratio [OR]: 10.57, 95% CI 2.32-48.19) and 5- < 15 years (OR: 6.64, 95% CI 1.38-32.04). Similar association was found between workload and stock-outs in register books, and inaccuracy in reporting of malaria confirmed cases. Meanwhile, we found that presence of a health technician, and of dedicated staff for data management, were associated with lower inaccuracy in reporting of clinic attendance in children aged under five years.ConclusionData completeness was high while the accuracy was low. Factors associated with data inaccuracy included high workload and the unavailability of required data collection tools. The results suggest that improvement in working conditions for clinic personnel may improve HMIS data quality. Upgrading from paper-based forms to a web-based HMIS may provide a solution for improving data accuracy and its utility for future evaluations of health interventions. Results from this study can inform the Ministry of Health and it partners on the precautions to be taken in the use of HMIS data and inform initiatives for improving its quality.

Project description:BackgroundCommunity case management of malaria (CCM) has been expanded in many settings, but there are limited data describing the impact of these services in routine implementation settings or at large scale. Zambia has intensively expanded CCM since 2013, whereby trained volunteer community health workers (CHW) use rapid diagnostic tests and artemether-lumefantrine to diagnose and treat uncomplicated malaria.MethodsThis retrospective, observational study explored associations between changing malaria service point (health facility or CHW) density per 1000 people and severe malaria admissions or malaria inpatient deaths by district and month in a dose-response approach, using existing routine and programmatic data. Negative binomial generalized linear mixed-effect models were used to assess the impact of increasing one additional malaria service point per 1000 population, and of achieving Zambia's interim target of 1 service point per 750 population. Access to insecticide-treated nets, indoor-residual spraying, and rainfall anomaly were included in models to reduce potential confounding.ResultsThe study captured 310,855 malaria admissions and 7158 inpatient malaria deaths over 83 districts (seven provinces) from January 2015 to May 2020. Total CHWs increased from 43 to 4503 during the study period, while health facilities increased from 1263 to 1765. After accounting for covariates, an increase of one malaria service point per 1000 was associated with a 19% reduction in severe malaria admissions among children under five (incidence rate ratio [IRR] 0.81, 95% confidence interval [CI] 0.75-0.87, p < 0.001) and 23% reduction in malaria deaths among under-fives (IRR 0.77, 95% CI 0.66-0.91). After categorizing the exposure of population per malaria service point, there was evidence for an effect on malaria admissions and inpatient malaria deaths among children under five only when reaching the target of one malaria service point per 750 population.ConclusionsCCM is an effective strategy for preventing severe malaria and deaths in areas such as Zambia where malaria diagnosis and treatment access remains challenging. These results support the continued investment in CCM scale-up in similar settings, to improve access to malaria diagnosis and treatment.

Dataset Information

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

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

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