Abstract
The use of data in decision making and planning in primary health care settings is critical for improving efficiency and health outcomes for patients and communities. Implementation research can be used to fully understand the effects, context, challenges, and facilitators of data use, as well as how to scale up data use interventions. However, in the context of low resource settings, little is known about how implementation research can be employed to assess the implementation and impact of data use interventions. We will conduct a hybrid type 2 effectiveness-implementation study employing a mixed method controlled before and after design to measure the effects of data use interventions while simultaneously understanding the implementation of those initiatives. The controlled before and after entails measurement of the effects of the interventions at baseline and end line in a matched intervention and control health facilities using structured questionnaire to health workers (n = 440) and existing patients (n = 422) while also extracting selected health outcome variable from routine data in all participating health facilities (n = 80). The mixed methods component entails measuring the implementation outcomes (adoption, acceptability, fidelity and maintenance) and their moderators entails the integration of both quantitative and qualitative data collection, analysis, and interpretation (i.e. mixed methods) approach by using a structured questionnaire to implementers (health workers and managers) (n = 400). Experiential dimensions of implementation processes and moderators will be explored using qualitative interviews. Guided by implementation research theories and frameworks, a theory of change (TOC) is developed first to guide the evaluation of implementation processes and effects of the interventions. Descriptive and inferential statistics will be employed to analyze quantitative data whereas thematic analysis approach will be employed for qualitative data. This study is one of the first to test the simultaneous measurement of effects and implementation processes of data use interventions in the primary health care settings. Findings will support efforts to improve quality of services by optimizing scale up and sustainability of the data use initiatives in primary health care settings.
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