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 (2013-2015) to support country plans to advance the RMNCH and commodity agenda.

Objectives: To document how Malawi (ministries, partners, working groups) used evidence to inform decision making and RMNCH investments; 2) to identify barriers to utilising information and evidence in the planning and prioritisation 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: A qualitative case study utilising a rapid-appraisal 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 proposal utilised an evidence-based and equity-focused process for prioritisation of investments. Data-informed decision making permeates similar commodity-focused working groups. However, common health information system (HIS) weaknesses, such as data quality and timeliness, 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 prioritisation. 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 Quality of Care Network) provide opportunities to further improve evidence-informed decision making.