The rapid growth in quality indicators (QIs) has increased complexity in selecting those that are effective for monitoring provider quality and patient outcomes. Existing selection methodologies are often insufficiently transparent or standardised and influenced by subjective opinions. To develop an instrument for evidence-based collection and evaluation of QIs that are suitable for quality monitoring, and which can be applied to various healthcare areas (HCAs; defined by care setting). The instrument was developed with HCA-specific experts, who provided feedback on its components and piloted its use in the Swiss context. We conducted a literature search with snowballing to identify prioritisation criteria and weighted these using the Analytic Hierarchy Process (AHP). We developed a template to facilitate data collection and the QI evaluation. The final QUALICATOR instrument consists of five steps: (1) definition of search scope; (2) utilisation of 12 prioritisation criteria across four dimensions (relevance, scientific soundness, usability, feasibility); (3) application of a data collection template objectifying the prioritisation criteria; (4) preselection via knockout criteria and (5) final prioritisation via weighting multicriteria decision analysis. Final criteria weights derived via the AHP varied substantially across HCAs (eg, relevance: 19.16%–57.10%; scientific soundness: 5.50%–39.50%; usability: 13.17%–33.75%; feasibility: 11.78%–45.57%), reflecting HCA-specific priorities. A web-based prototype is available to support a user-friendly application. This QUALICATOR instrument provides a transparent, scalable approach to navigate through a growing body of QIs with further validation needed. It provides a methodological framework and proof of concept, rather than a ready-to-use solution. It shows policymakers, providers and payers a path to make informed decisions about which QIs to prioritise, monitor, invest in and act on.
Backes et al. (Wed,) studied this question.