Understanding Data Demand and Use in Kenya – Successes and Challenges in Kakamega, Kilifi, and Kisumu Counties

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Author(s): MEASURE Evaluation PIMA

Year: 2017

Understanding Data Demand and Use in Kenya – Successes and Challenges in Kakamega, Kilifi, and Kisumu Counties Abstract:

Evidence-based decision making is essential for the success of health systems, programs, and services. Global commitments to improving health systems and outcomes have led to improved monitoring and evaluation (M&E) and better health information systems, thus providing an opportunity to use data for decision making and not simply for reporting. MEASURE Evaluation has developed a conceptual approach and logic model that guides the health sector in adopting best practices in data-informed decision making and data use.

Overall, the relationship between improved information, demand for data and continued data use creates a cycle that leads to improved health programs and policies. Improving data demand and use is necessary to make a health system more effective and sustainable.

Data demand and use (DDU) is a core component of MEASURE Evaluation PIMA’s objectives to strengthen M&E at the national and subnational levels of Kenya’s health care system. The DDU strategic approach is the foundation of the overall goal of the PIMA project to build sustainable M&E capacity to use quality health data for evidence-based decisions and program planning in the following six areas: malaria; civil registration and vital statistics; reproductive health; referral systems strengthening; disease surveillance; and orphans and vulnerable children.

At the beginning of the PIMA project, the M&E Capacity Assessment Tool (MECAT) was used to determine the M&E capacity of PIMA beneficiaries at the national and county levels. Findings from the MECAT showed that across all counties where PIMA was going to provide support over the project lifetime, no data use strategies existed and some counties only had a data use approach mentioned in a strategic plan or draft M&E work plans. At the national level, data use infrastructure was weak since most national programs did not have guidelines or plans on data use.

Following the mid-term review of the project in Year 3, PIMA set out to conduct a DDU learning exercise in Year 4 to provide data on the extent to which select counties have integrated data for decision making into routine programming and planning processes.

PIMA provided extensive technical assistance and support to each of the three counties selected for this exercise. This support included the formation of M&E technical working groups (TWGs), assistance with data review meetings, assistance with program planning and budgeting, and training in data demand and use tools and approaches.

This document is not available in print from MEASURE Evaluation.

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