ArticleBMC medical informatics and decision making2021
Health management information system (HMIS) data quality and associated factors in Massaguet district, Chad.
Article in BMC medical informatics and decision making, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
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Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Common data quality elements for health information systems: a systematic review.BMC medical informatics and decision making · 2024Pooled it
- Augmented Capacity Development Interventions (ACDI) Improved Data Quality Performance in the Routine Health Information System (RHIS): A Cluster Randomized Trial.Inquiry : a journal of medical care organization, provision and financingTrial
- Beyond national household surveys: routine and alternative approaches to sustain robust evidence-based decision making.Malaria journal · 2026Review
- How to design decision-support tools for primary healthcare using a human-centred design approach: the processes and experience of PHISICC in three Sub-Saharan countries.BMJ global health · 2026Article
- Assessing the effectiveness of seasonal malaria chemoprevention on malaria burden among children under 5 in northern Benin: a statistical modelling approach.BMJ public health · 2026Article
- Article
- Optimizing adolescent HIV care: a review of EMR system quality for clinical monitoring in Zambia.Frontiers in public health · 2026Article
- Concordance of rapid diagnostic test results between health facility registers and health management information systems: a multi-country evaluation.Malaria journal · 2025Observational
- Negligence in data recording during institutional birth: exploring health workers' perspectives on the barriers and enablers of data documentation practices.Archives of public health = Archives belges de sante publique · 2025Article
- Utilisation of data and factors affecting the performance of the Health Management Information System (HMIS). The case of six Synods of Livingstonia health facilities in Malawi.Archives of public health = Archives belges de sante publique · 2025Article
- Surgical indicators for obstetrics and family planning in routine health information systems: a landscape analysis.Health policy and planning · 2025Article
- Concordance of data on key malaria indicators between DHIS2 and source documents, and influencing factors at public primary health facilities in eastern Uganda: a mixed methods study.Malaria journal · 2025Article
- Study on external consistency of health management information system data at district level across India.Journal of family medicine and primary care · 2025Article
- Development and implementation of a digital clinical decision support system to increase the quality of primary healthcare delivery in a refugee setting in Chad.BMC primary care · 2025Article
- Maternal health planning and prioritization in Chad: developing a supportive tool.Health policy and planning · 2025Article
- Coaching visits and supportive supervision for primary care facilities to improve malaria service data quality in Ghana: An intervention case study.PLOS global public health · 2025Article
- Towards improving district health information system data consistency, report completeness and timeliness in Neno district, Malawi.BMC medical informatics and decision making · 2024Article
- Assessing the impact of COVID-19 pandemic on maternal healthcare usage: evidence from routine health data in Kenya and Ethiopia.BMJ public health · 2023Article
- Gaps in research and capacity development for malaria surveillance and response in the Asia-Pacific: meeting report.Malaria journal · 2023Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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