Abstract
ABSTRACTBackground: Although understanding implementation context is essential, there is a dearth of research on how to systematically explore it in quality improvement (QI) programs. Therefore, in this study, we used the consolidated framework for implementation research (CFIR) to guide a systematic evaluation of the implementation context of an ongoing QI program in order to generate rapid site-specific feedback that can be used to improve subsequent plan-do-study-act (PDSA) cycles.Methods: Formative cross-case evaluation was conducted using convergent mixed methods design. The study was conducted in five primary health care (PHC) facilities (PHC 1, PHC 3, PHC 5, PHC 9 and PHC 10) implementing the QI program. Health workers in those facilities formed the study population. Quantitative data were collected using a self-administered, Likert-based rating tool, while qualitative data collection was guided by an interview guide. The interviews were transcribed verbatim, and thematic analysis was performed. Raw median score and factor scores were computed. Methodological integration occurred at the design, analysis and reporting stage.Results: A total of 165 health workers were included in this study with a mean age of 33.43 years (standard deviation of 7.15). Majority were females and they all had post-secondary education. Health workers in two facilities; PHC 1 and PHC 5, reported higher score for the QI program across all five domains of CFIR. Implementation facilitators included intervention flexibility, relative advantage, self-efficacy among health workers, health workers confidence in the intervention, services integration. While implementation barriers included vaccine stock out, faulty cold chain infrastructure, lack of incentives, and socio-cultural beliefs.Conclusion: This study demonstrated that theory-driven formative evaluation can be integrated in QI programs in a low resource setting. It buttressed the value in conducting such assessment as they can be used to generate rapid feedback on factors that influence implementation success which can then be addressed in subsequent cycles.
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