Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Operational Research and Coaching for Analysts (ORCA)- participants & team

PROVIDER: S-EPMC8710857 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Publications

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

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 Getnet Misrak M Bishaw Tesfahun T Busza Joanna J 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 Janson Annika A Kemal Binyam B Kiflom Abiy A 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 Yusuf Zemzem M ZM Zealiyas Kidist K Zeweli Mebratom H MH Persson Lars Åke LÅ Lemma Seblewengel S

BMJ open 20211223 12

<h4>Objective</h4>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.<h4>Design</h4>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 In ...[more]

PMID: 34949613

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Project description: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.

Project description:BackgroundPatients with co-occurring behavioral health and chronic medical conditions frequently overuse inpatient hospital services. This pattern of overuse contributes to inefficient health care spending. These patients require coordinated care to achieve optimal health outcomes. However, the poor exchange of health-related information between various clinicians renders the delivery of coordinated care challenging. Health information exchanges (HIEs) facilitate health-related information sharing and have been shown to be effective in chronic disease management; however, their effectiveness in the delivery of integrated care is less clear. It is prudent to consider new approaches to sharing both general medical and behavioral health information.ObjectiveThis study aims to identify and describe factors influencing the intention to use behavioral health information that is shared through HIEs.MethodsWe used a mixed methods design consisting of two sequential phases. A validated survey instrument was emailed to clinical and nonclinical staff in Alabama and Oklahoma. The survey captured information about the impact of predictors on the intention to use behavioral health data in clinical decision making. Follow-up interviews were conducted with a subsample of participants to elaborate on the survey results. Partial least squares structural equation modeling was used to analyze survey data. Thematic analysis was used to identify themes from the interviews.ResultsA total of 62 participants completed the survey. In total, 63% (n=39) of the participants were clinicians. Performance expectancy (β=.382; P=.01) and trust (β=.539; P<.001) predicted intention to use behavioral health information shared via HIEs. The interviewees (n=5) expressed that behavioral health information could be useful in clinical decision making. However, privacy and confidentiality concerns discourage sharing this information, which is generally missing from patient records altogether. The interviewees also stated that training for HIE use was not mandatory; the training that was provided did not focus specifically on the exchange of behavioral health information.ConclusionsDespite barriers, individuals are willing to use behavioral health information from HIEs if they believe that it will enhance job performance and if the information being transmitted is trustworthy. The findings contribute to our understanding of the role HIEs can play in delivering integrated care, particularly to vulnerable patients.

Project description:BackgroundHigh-quality data are vital for informed decision-making, enhancing population health, and achieving comprehensive insights. However, there is limited understanding of the consistency and reliability of routine Health Management Information System (HMIS) including nutrition data across diverse regions in Ethiopia. This study systematically reviewed the existing literature to address these knowledge gaps.MethodsWe systematically searched PubMed, HINARI, and Google Scholar for studies published from 2015 onwards to assess HMIS, including nutrition data quality in Ethiopia. The evaluations focused on completeness, consistency, and timeliness metrics defined by the WHO. We included diverse regional studies without indicator restrictions, prioritized data quality metrics as primary outcomes, and explored qualitative reasons for poor data quality as secondary outcomes.ResultsOf the 1790 papers screened, 25 met the inclusion criteria. The completeness of reporting varied widely among studies (50%-100%), with only 21% (4 out of 19) exceeding 90%. The consistency ranged from 38.9% to 90.5%, with only 6% of studies reporting internal consistency above 90%. Other consistency issues included lack of external consistency, indicator discrepancies, and outliers. Timeliness ranged from 41.9% to 93.7%, with 54% of studies reporting below 80%. In addition to the lack of studies addressing nutrition data, the quality was no better than other components of HMIS. The major factors contributing to poor data quality were human resource shortages, insufficient capacity building, behavioural influences, and infrastructural deficits.ConclusionThe HMIS including nutrition data in Ethiopia, exhibited deficiencies in completeness, consistency, and timeliness, which were largely, attributed to capacity and resource constraints. Interventions should prioritize resource allocation, staff training, supervision, and feedback mechanisms to enhance data quality, thereby improving decision-making processes and population health outcomes.

Project description:BackgroundA well designed Health management information system is necessary for improving health service effectiveness and efficiency. It also helps to produce quality information and conduct evidence based monitoring, adjusting policy implementation and resource use. However, evidences show that data quality is poor and is not utilized for program decisions in Ethiopia especially at lower levels of the health care and it remains as a major challenge.MethodFacility based cross sectional study design was employed. A total of 18 health centers and 302 health professionals were selected by simple random sampling using lottery method from each selected health center. Data was collected by health professionals who were experienced and had training on HMIS tasks after the tools were pretested. Data quality was assessed using accuracy, completeness and timeliness dimensions. Seven indicators from national priority area were selected to assess data accuracy and monthly reports were used to assess completeness and timeliness. Statistical software SPSS version 20 for descriptive statistics and binary logistic regression was used for quantitative data analysis to identify candidate variable.ResultA total of 291 respondents were participated in the study with response rate of 96%. Overall average data quality was 82.5%. Accuracy, completeness and timeliness dimensions were 76%, 83.3 and 88.4 respectively which was lower than the national target. About 52.2% respondents were trained on HMIS, 62.5% had supervisory visits as per standard and only 55.3% got written feedback. Only 11% of facilities assigned health information technicians. Level of confidence [AOR = 1.75, 95% CI (0.99, 3.11)], filling registration or tally completely [AOR = 3.4, 95% CI (1.3, 8.7)], data quality check, supervision AOR = 1.7 95% CI (0.92, 2.63) and training [AOR = 1.89 95% CI (1.03, 3.45)] were significantly associated with data quality.ConclusionThis study found that the overall data quality was lower than the national target. Over reporting of all indicators were observed in all facilities. It needs major improvement on supervision quality, training status to increase confidence of individuals to do HMIS activities.

Project description:BackgroundSeveral studies have reported inadequate levels of quality of care in the Ethiopian health system. Facility characteristics associated with better quality remain unclear. Understanding associations between patient volumes and quality of care could help organize service delivery and potentially improve patient outcomes.MethodsUsing data from the routine health management information system (HMIS) and the 2014 Ethiopian Service Provision Assessment survey + we assessed associations between daily total outpatient volumes and quality of services. Quality of care at the facility level was estimated as the average of five measures of provider knowledge (clinical vignettes on malaria and tuberculosis) and competence (observations of family planning, antenatal care and sick child care consultations). We used linear regression models adjusted for several facility-level confounders and region fixed effects with log-transformed patient volume fitted as a linear spline. We repeated analyses for the association between volume of antenatal care visits and quality.ResultsOur analysis included 424 facilities including 270 health centers, 45 primary hospitals and 109 general hospitals in Ethiopia. Quality was low across all facilities ranging from only 18 to 56% with a mean score of 38%. Outpatient volume varied from less than one patient per day to 581. We found a small but statistically significant association between volume and quality which appeared non-linear, with an inverted U-shape. Among facilities seeing less than 90.6 outpatients per day, quality increased with greater patient volumes. Among facilities seeing 90.6 or more outpatients per day, quality decreased with greater patient volumes. We found a similar association between volume and quality of antenatal care visits.ConclusionsHealth care utilization and quality must be improved throughout the health system in Ethiopia. Our results are suggestive of a potential U-shape association between volume and quality of primary care services. Understanding the links between volume of patients and quality of care may provide insights for organizing service delivery in Ethiopia and similar contexts.

Dataset Information

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

Objective

Design

Setting

Participants

Outcome measures

Results

Conclusion

Publications

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

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