Common Features of Selection Processes of Health System Performance Indicators in Primary Healthcare: A Systematic Review.

Background: Health system performance indicators are widely used to assess primary healthcare (PHC) performance. Despite the numerous tools and some convergence on indicator criteria, there is not a clear understanding of the common features of indicator selection processes. We aimed to review the literature to identify papers that document indicator selection processes for health system performance indicators in PHC. Methods: We searched the online databases Scopus, Medline, and CINAHL, as well as the grey literature, without time restrictions, initially on July 31, 2019 followed by an update November 13, 2020. Empirical studies or reports were included if they described the selection of health system performance indicators or frameworks, that included PHC indicators. A combination of the process focused research question and qualitative analysis meant a quality appraisal tool or assessment of bias could not meaningfully be applied to assess individual studies. We undertook an inductive analysis based on potential indicator selection processes criteria, drawn from health system performance indicator appraisal tools reported in the literature. Results: We identified 16 503 records of which 28 were included in the review. Most studies used a descriptive case study design. We found no consistent variations between indicator selection processes of health systems of high income and low- or lower-middle income countries. Identified common features of selection processes for indicators in PHC include literature review or adaption of an existing framework as an initial step; a consensus building process with stakeholders; structuring indicators into categories; and indicator criteria focusing on validity and feasibility. The evidence around field testing with utility and consideration of reporting burden was less clear. Conclusion: Our findings highlight several characteristics of health system indicator selection processes. These features provide the groundwork to better understand how to value indicator selection processes in PHC. [ABSTRACT FROM AUTHOR]

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