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.
Highlights
Quality data from Health Management Information Systems (HMIS) are important for tracking the effectiveness of malaria control interventions
Unavailability of commodities influenced functioning of health centres; 56.25% of health centres sampled reported at least one stock-out of rapid diagnostic tests (RDT), with an average of 16.53 days duration (CI 14.54–18.72) across all facilities over the whole study period
The presence of a nurse among clinic staff was associated with lower odds of inaccurate data for children 1 to < 5 years (0.16, 95% confidence intervals (95% CI) 0.04–0.74) whereas we found a higher odds of inaccurate reporting in clinics with a health technician among their staff (11.03, 95% CI 1.65–73.63)
Summary
Quality data from Health Management Information Systems (HMIS) are important for tracking the effectiveness of malaria control interventions. 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. The World Health Organization (WHO) has highlighted the importance of investing in high-quality routine information systems to support malaria surveillance and monitoring of malaria program activities [1], and complement overall malaria elimination efforts [2]. Health Management Information Systems (HMIS) in many resource-limited settings, including Chad, do not currently meet these standards [4, 5]. Trends in malaria incidence can be used to evaluate impact of malaria interventions such as Seasonal Malaria Chemoprevention (SMC) and support decision-making on their introduction and expansion. While HMIS is a convenient and readily-available source for such data, it is important to ensure the HMIS data is sufficiently reliable decision-making
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