Moving data off the shelf and into action: an intervention to improve data-informed decision making in Côte d'Ivoire - Tara Nutley; Léontine Gnassou; Moussa Traore; Abitche Edwige Bosso; Stephanie Mullen (Taylor & Francis Group, 2014)
Background: Improving a health system requires data, but too often they are unused or under-used by decision makers. Without interventions to improve the use of data in decision making, health systems cannot meet the needs of the populations they serve. In 2008, in Côte d'Ivoire, data were largely unused in health decision-making processes. Objective: To implement and evaluate an intervention to improve the use of data in decision making in Cote d'Ivoire. Design: From 2008 to 2012, Cote d'Ivoire sought to improve the use of national health data through an intervention that broadens participation in and builds links between data collection and decision-making processes; identifies information needs; improves data quality; builds capacity to analyze, synthesize, and interpret data; and develops policies to support data use. To assess the results, a Performance of Routine Information System Management Assessment was conducted before and after the intervention using a combination of purposeful and random sampling. In 2008, the sample consisted of the central level, 12 districts, and 119 facilities, and in 2012, the sample consisted of the central level, 20 districts, and 190 health facilities. To assess data use, we developed dichotomous indicators: discussions of analysis findings, decisions taken based on the analysis, and decisions referred to upper management for action. We aggregated the indicators to generate a composite, continuous index of data use. Results: From 2008 to 2012, the district data-use score increased from 40 to 70%; the facility score remained the same - 38%. The central score is not reported, because of a methodological difference in the two assessments. Conclusions: The intervention improved the use of data in decision making at the district level in Côte d'Ivoire. This study provides an example of, and guidance for, implementing a large-scale intervention to improve data-informed decision making.