Concordance of data on key malaria indicators between DHIS 2 and source documents and its influencing factors at health facilities in Mayuge District, Uganda

Abstract

Introduction: Effective malaria surveillance is a key strategy for malaria control in sub-Saharan Africa. Uganda rolled out the District Health Information System, version 2 (DHIS 2) to improve routine malaria surveillance data quality. However, the quality of DHIS 2 reported malaria data surveillance data remains questionable. Objective: To assess the level of concordance of selected data indicators between the DHIS 2 and facility source documents and its influencing factors among health facilities in Mayuge district. Methods: This was a mixed-methods study that included a retrospective review of DHIS 2 data reported between 2021-2022 and corresponding data in the HMIS source documents at 12 lower-level public health facilities (Health Centre IVs, IIIs and IIs) in Mayuge district. In addition, Key Informant Interviews (KIIs) and In-depth Interviews (IDIs) were conducted among health facility heads and health records personnel of the participating facilities. The level of data concordance for the key malaria indicators was determined and expressed as a proportion of weeks with a VF of 0.9 to 1.1 and also assessed using the Bland-Altman analysis. Modified Poisson regression with robust standard errors was used to determine factors associated with data concordance for malaria TPR. Qualitative data were analyzed using deductive thematic analysis. Results: The overall concordance between DHIS 2 and routine data sources was low, and varied by malaria indicator type; (36.7%, 95% confidence interval [CI] 25.2 - 49.9%) for suspected malaria cases; (53.6%, 95% CI 41.7 - 65.1%) for the suspected malaria cases tested, and (56.8 %, 95% CI 43.9 - 68.8%) for the test positivity rate (TPR) indicator. Factors significantly associated with concordance included the presence of dedicated HMIS personnel at the facility [adjusted prevalence ratio (aPR=1.41, 95% CI=1.20 - 1.66, P= <0.001)], stock out of malaria rapid tests (RDTs), (aPR= 0.55, 95% CI=0.35 - 0.86, P= 0.009) and timely reporting (aPR=1.15, 95% CI=1.00 - 1.31, P= 0.049). From qualitative data, regular data verification, value and relevance of HMIS data were the commonly reported facilitators of improved data concordance while insufficient HMIS training and stock out of HMIS forms were reported as barriers to improved data concordance. Conclusion: Data concordance for all selected malaria indicators was below the WHO standard of ≥ 80%. The presence of HMIS personnel at a health facility, stockout of RDTs and timely reporting were significantly associated with data concordance of reported malaria data. The health facility in charges and records people frequently mentioned stock out of HMIS forms and insufficient HMIS trainings as barriers of data concordance. These results highlight the need for investment in hiring and training of HMIS data clerks, maintaining adequate RDT stocks and HMIS forms at public health facilities.