Factors Affecting Data Quality in the Malawian Health Management Information System

Benjamin Kumwenda, Dickson Jimmy-Gama, Velia Manyonga, Noella Semu-Kamwendo, Beatrice Nindi-Mtotha, and Maureen Chirwa


Data quality, Health service, Feedback, Completeness


Background The health management information system (HMIS) was introduced in Malawi using the district health information system (DHIS) as a tool for collecting, processing, transmission, analysing and providing feedback of health information. Despite these efforts and the importance of data, health related data remains of poor quality. It is either incomplete, inaccurate and at times out-dated when being represented to health managers and policy makers. The aim of the study was to determine factors that affect data quality in the HMIS in Malawi. Methods The study was conducted in purposively selected hospitals of Kamuzu Central Hospital (KCH), Bwaila, Kasungu and Ntcheu hospitals in the central region. Mangochi and Balaka district hospitals were selected in southern region of Malawi. Data quality was assessed by physically assessing data in registers for correctness and completeness over a period of six months to one year. Timeliness of the data was investigated in reports that were made from health facilities to districts and finally the health management unit (HMU) in the ministry of health and visa versa. Semi-structured questionnaire were administered to health workers in addition to focus group discussion for in-depth interview. Stakeholders were interviewed to assess the impact of feedback and the appropriate formats of feedback. Patient flow and management were analysed using turnaround time and throughput at Mangochi and Bwaila district hospitals to determine the efficiency and effectiveness of the health service delivery but also to determine how it affected data quality. Results Higher numbers of discrepancies were observed between data in registers and in HMIS. Data collectors used different standards to measure indicators, which affected its consistency. These were aggravated by lack of training and supervision among data collectors. Programme managers never used the HMIS data due to limited government funding. This was a major limitation in implementing decisions that could be made from the HMIS. The implication of patients flow was that some data elements such as drug stocks were recorded in HMIS before actually being issued at the pharmacy, which affected correctness of the data.

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