Data-informed decision-making for life-saving commodities investments in Malawi: A qualitative case study|
Nemser, Bennett; Aung, Kyaw; Mushamba, Mildred; Chirwa, Samuel; Sera, Diana; Chikhwaza, Owen & Kachale, Fannie
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.
(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.
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.
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.
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.