Factors associated with the quality of routine health management information system data for district level reporting and utilization in Makindye-Division Kampala Capital City Authority

Abstract

Background: Despite the benefits of Health Management Information System (HMIS) data, its quality in low- and middle-income countries remains suboptimal. This study investigated factors influencing HMIS data quality in private and public health facilities in Makindye Division, Kampala. Methods: A concurrent triangulation mixed-methods approach was used. Quantitative data (n=53 facilities) was collected via self-administered surveys, analyzed using descriptive statistics, logistic regression in MS Excel and Stata 15, and directed content analysis for qualitative analysis. Qualitative data was gathered through key informant interviews. Health facilities with an average monthly OPD attendance of 100 patients and routinely reporting in DHIS2 were selected for the study. Results: Only 15.1% of facilities had high-quality data, with 84.9% having low-quality data. Data accuracy was 52.8%, completeness 75%, and timeliness 69.8%. Significant predictors of high data quality included; staff tenure <5 years (aOR 4.142, 95%CI 2.586-6.633, p<0.001), external support policies (aOR 1.477, 95%CI 1.050-2.079, p=0.025). Qualitative findings identified contributors to low data quality; poor handwriting, inadequate staff, stock outs of data tools, slow DHIS2 system , lack of computers.

Conclusion and recommendation: Low data quality was prevalent in most health facilities. Recruitment of more staff with emphasis on data managers, supply of computers, upgrade of the DHIS2 system to improve its speed, upgrade from paper based to electronic based systems, development of clear guidelines and protocols as well as implementation of change overs of staff would improve data quality.