Data-informed decision-making for life-saving commodities investments in Malawi: A qualitative case study

Abstract

Background
During the last 15 years, Malawi has made remarkable progress in reducing child mortality. However, maternal and newborn mortality remains persistently high. To help address these entrenched challenges, the Reproductive, Maternal, Newborn and Child Health (RMNCH) Trust Fund provided short-term catalytic financing of $11.5 million (2013-2016) to support country plans to advance the RMNCH and commodity agenda.
Objectives
(1) To document how Malawi (ministries, partners, working groups) used evidence to inform decision-making and RMNCH investments, (2) To identify barriers to utilizing information and evidence in the planning and prioritization process at national and sub-national levels, and (3) To assess the utility of the RMNCH Landscape Synthesis, which uses existing information to review life-saving RMNCH commodities and services.
Methods
This was a qualitative case study utilizing a Rapid Appraisal (RA) approach, where semi-structured interviews were conducted with staff members from UN agencies, development partners and the Ministry of Health (MoH) at national and district level. The analysis enlists a framework approach for manual qualitative content analysis.
Results
Led by the MoH, the RMNCH Trust Fund grant proposal utilized an evidence-based and equity-focused process for prioritization of investments. Data-informed decision-making permeates similar commodity-focused working groups. However, common health information system (HIS) weaknesses, such as data quality and collection burden, persist and are more prevalent at district-level. The collation of evidence in the RMNCH Landscape Synthesis was a useful and sustainable tool to support planning.
Conclusions
The evidence-based, equity-focused decision-making process for the RMNCH Trust Fund proposal provides an effective model for inter-agency investment prioritization. Strengthening data-informed decision-making will require financial and political commitments to HIS and capacity building for data use, particularly at the district-level. New initiatives (e.g. Health Data Collaborative and QED Network to Improve Quality of Care) provide opportunities to further improve evidence-informed decision-making.