Decision-Making Strategies That Use Health Data at District Level in Low- and Lower-Middle-Income Countries: A Systematic Literature Review

Presentation at the Global Maternal Newborn Health Conference, October 21, 2015

Background: Although large amounts of data about health service provision and population health are produced for health management information systems (HMIS), evidence of using data for decision-making at district level is limited. A district is defined as the lowest administrative unit of health system management with potential to make independent decisions about health service delivery. This study aimed to explore the ways that district administrators and health authorities in low- and lower-middle-income countries make collective decisions using health data; outline their decision-making strategies; and determine any challenges they meet when using these strategies.

Methods: We undertook a systematic literature review, following PRISMA guidelines. Fourteen key databases of peer reviewed and grey literature were searched and the resources found were screened independently. An assessment of the quality of reported evidence was completed and the evidence from the review findings was synthesised according to the nature of the decision-making strategies, the data sources used in those strategies, and specific consensus building strategies identified.

Results: Around 12 examples of tools to assist district-level decision-making were identified. They all followed a generic process of at least two steps – to prioritise the health issues to be addressed, and to develop an action plan. All the strategies were based on the use of locally derived data, with two-thirds specifically including HMIS data and one-third incorporating an additional step – to monitor the action plan. The three main types of challenges to decision-making strategies were: the quality of existing health facility data; maintaining the democratic nature of decision making; and limited financial resources.

Conclusion: Although the evidence was limited, there were examples of good practice and these strategies showed that HMIS can be used for effective shared decision-making at district level. Wider adoption of such strategies would be enhanced by standardisation and pre-testing in diverse settings.