Evidence map›Paper›PMID 34809622›Full record

ArticleBMC medical informatics and decision making2021

Health management information system (HMIS) data quality and associated factors in Massaguet district, Chad.

Azoukalné Moukénet, Monica Anna de Cola, Charlotte Ward, Honoré Beakgoubé, Kevin Baker, Laura Donovan, Jean Laoukolé, Sol Richardson

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 pooled it
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Azoukalné MoukénetMalaria Consortium Chad Country Office, Angle Bureau de L'Entente Des Eglises (EEMET), Rue 2175, Porte 0150, B.P. 6180, N'Djamena, Chad.ORCID 0000-0001-7780-366X
Monica Anna de ColaMalaria Consortium, The Green House, 244-254 Cambridge Heath Road, London, E2 9DA, UK.ORCID 0000-0001-9444-8460
Charlotte WardDepartment of Global Health and Development, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.ORCID 0000-0003-4223-7850
Honoré BeakgoubéMalaria Consortium Chad Country Office, Angle Bureau de L'Entente Des Eglises (EEMET), Rue 2175, Porte 0150, B.P. 6180, N'Djamena, Chad.
Kevin BakerMalaria Consortium, The Green House, 244-254 Cambridge Heath Road, London, E2 9DA, UK.ORCID 0000-0002-2040-3662
Laura DonovanMalaria Consortium, The Green House, 244-254 Cambridge Heath Road, London, E2 9DA, UK.ORCID 0000-0001-5557-5539
Jean LaoukoléNational Malaria Control Programme, N'Djamena, Chad.
Sol RichardsonMalaria Consortium, The Green House, 244-254 Cambridge Heath Road, London, E2 9DA, UK. s.richardson@malariaconsortium.org.ORCID 0000-0003-0863-1061

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Data AccuracyManagement Information SystemsChadChildCross-Sectional StudiesHumansInfantSurveys and QuestionnairesChadData qualityHealth management information systemMalaria

Identifiers

PMID34809622
PMCPMC8609810

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.