A core outcome set of patient-reported experience measures for primary care
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Published on: August 1, 2019
Marie-Eve Poitras1,2, Anne-Sophie Langlois1, Marie-Eve Perron1,3
1Université de Sherbrooke, Sherbrooke, Canada.
Background:
Patient-Reported Experience Measures (PREMs) are validated self-reported perceptions of how patients experience care in a given context. Despite their recognized value, their integration in clinical settings is limited by conceptual heterogeneity and measurement inconsistency. To enhance comparability and operational clarity, this study aimed to develop a consensus-based core set of constructs representing the essential dimensions of patient experience in primary care.
Methods:
We conducted a three-round Delphi study in accordance with the COS-STAD and ACCORD methodological standards. We purposively recruited experts into three groups: patients, clinicians/decision-makers, and researchers. Sixteen constructs derived from a prior scoping review of validated PREMs were rated for inclusion in a core measurement set. Consensus thresholds were defined a priori as a positive median, interquartile range < 1, and < 5% negative ratings.
Results:
Eighty-nine experts participated across rounds (24 patients, 31 clinicians/decision-makers, 34 researchers). Of the sixteen constructs evaluated, six reached global consensus: accessibility, continuity, coordination, communication, comprehensiveness, and patient engagement. Subgroup analyses revealed convergence between patients and clinicians on these constructs in round 2, suggesting disciplinary heterogeneity in conceptualizing experience domains. Ten constructs did not achieve consensus, reflecting contextual or normative variability: including equity, advocacy, organization, professional competencies, family context, and community context.
Conclusion:
This Delphi-derived core set provides a consensus-informed basis for measuring patient experience in primary care. It offers a parsimonious, conceptually grounded framework to guide PREM development, support data comparability, and enhance responsiveness within learning health systems. Context-dependent constructs should complement the core set where local priorities or populations warrant expanded assessment.
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