Assessment of implementation of the health management information system at the district level in southern Malawi

Background:
Despite Malawi’s introduction of a health management information system (HMIS) in 1999, the country’s health sector still lacks accurate, reliable, complete, consistent and timely health data to inform effective planning and resource management.
Methods:
A cross-sectional survey was conducted wherein qualitative and quantitative data were collected through in-depth interviews, document review, and focus group discussions. Study participants comprised 10 HMIS officers and 10 district health managers from 10 districts in the Southern Region of Malawi. The study was conducted from March to April 2012. Quantitative data were analysed using Microsoft Excel and qualitative data were summarised and analysed using thematic analysis.
Results:
The study established that, based on the Ministry of Health’s minimum requirements, 1 out of 10 HMIS officers was qualified for the post. The HMIS officers stated that HMIS data collectors from the district hospital, health facilities, and the community included medical assistants, nurse–midwives, statistical clerks, and health surveillance assistants. Challenges with the system included inadequate resources, knowledge gaps, inadequacy of staff, and lack of training and refresher courses, which collectively contribute to unreliable information and therefore poorly informed decision-making, according to the respondents. The HMIS officers further commented that missing values arose from incomplete registers and data gaps. Furthermore, improper comprehension of some terms by health surveillance assistants (HSAs) and statistical clerks led to incorrectly recorded data.
Conclusions:
The inadequate qualifications among the diverse group of data collectors, along with the varying availability and utilisation different data collection tools, contributed to data inaccuracies. Nevertheless, HMIS was useful for the development of District Implementation Plans (DIPs) and planning for other projects. To reduce data inconsistencies, HMIS indicators should be revised and data collection tools should be harmonised.