ASSESSING POLICY CAPACITY: A MIXED-METHODS STUDY OF HEALTH POLICY MAKING IN NOVA SCOTIA
Introduction: Health policies need to be changed to better address health system challenges. However, these changes require many factors in order to succeed. Collectively, these factors are referred to as policy capacity. While important, policy capacity is vaguely defined, limiting its usefulness to policy makers and researchers. A recent conceptual framework breaks policy capacity into nine sub-capacities. Greater clarity of these sub-capacities would improve how policy capacity is understood and applied. This research describes the operationalization of this conceptual framework to create the Health Policy Capacity Assessment Tool (HPCAT). Methods: The HPCAT was created using a sequential explanatory mixed-methods design. First, an online Delphi survey was conducted with provincial health policy experts to validate sub-capacities and clarify their meaning. These were arranged within the framework and rated to identify the best items for the HPCAT. Next, the HPCAT was used to analyze two cases studies of recent provincial health policy changes. Finally, findings from the case studies were compared and synthesized to refine the HPCAT. Results: Seventeen policy experts completed the Delphi survey, producing a HPCAT with 40 factors unevenly distributed across the nine sub-capacities. Guided by the HPCAT, interviews with 22 key informants described how policy capacity was manifested in the two case studies. These findings led to the HPCAT V2 , which contains 47 factors spread across 12 sub-capacities. A new skill type – integrative competencies – was identified, representing the ability to support and integrate the other three skill types. Conclusion: Building on an existing conceptual framework, the HPCAT V2 provides guidance to those interested in understanding and applying the different factors which comprise policy capacity. Future research can explore the usefulness of the HPCAT V2 in different policy environments and how it might inform policy planning.
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