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

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Data Quality, Heath Service, Feedback, Correctness,Completeness, Throughput.


The Health Management Information System (HMIS) was introduced in Malawi with the District Health Information System (DHIS) as a tool for collecting, processing, transmitting, analysing and providing feedback of health information to various levels of the health system. Despite this effort among several others, the importance of data use in decision-making remains low and its quality is still poor. It is either incomplete, inaccurate and out-dated when being reported to health managers and policy makers. The aim of this study was to determine factors that affect data quality in the HMIS in Malawi. The study was conducted in various purposively selected hospitals countrywide. These are Kamuzu Central Hospital (KCH), Bwaila, Kasungu and Ntcheu hospitals in the central region of the country. Mangochi and Balaka district hospitals were selected in southern region. Data quality was assessed by physically assessing it in registers for correctness and completeness over a period of six months to one year. Timeliness was investigated in reports that were made from health facilities to districts and finally the Health Management Unit (HMU) in the Ministry of Health (MoH) and visa versa. Semi-structured questionnaires were administered on health workers in addition to conducting focus group discussion for in-depth interview. Stakeholders were interviewed to assess the impact of feedback and the appropriate formats for feedback presentation. Patient flow and management were analysed using turnaround time and throughput as measures at Mangochi and Bwaila district hospitals to determine the efficiency and effectiveness of the health service delivery system to patients but also to determine how it affected data quality. Higher numbers of discrepancies were observed between data in registers and physical reports in comparison to HMIS. Data collectors used different standards to measure indicators, which affected the consistency of the data. These were aggravated by lack of training and supervision among data collectors. Programme managers never used HMIS data due to limited government funding. This was a major limitation in the implementation of informed decisions that could be made from 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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