Optimizing data visualization for reproductive, maternal, newborn, child health, and nutrition (RMNCH&N) policymaking: data visualization preferences and interpretation capacity among decision-makers in Tanzania.

ABSTRACT:

Background

Reproductive, maternal, newborn, child health, and nutrition (RMNCH&N) data is an indispensable tool for program and policy decisions in low- and middle-income countries. However, being equipped with evidence doesn't necessarily translate to program and policy changes. This study aimed to characterize data visualization interpretation capacity and preferences among RMNCH&N Tanzanian program implementers and policymakers ("decision-makers") to design more effective approaches towards promoting evidence-based RMNCH&N decisions in Tanzania.

Methods

We conducted 25 semi-structured interviews in Kiswahili with junior, mid-level, and senior RMNCH&N decision-makers working in Tanzanian government institutions. We used snowball sampling to recruit participants with differ

SUBMITTER: Aung T 

PROVIDER: S-EPMC6376719 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature