Advancing Value-Based Academic-Clinical Partnership Evaluation in Physical Therapy Education: Multiattribute Utility Analysis as a Contextual Methodological Approach.

Abstract

Introduction: There is a need to investigate the application of systematic, scholarly methods to develop and implement a sustainable, flexible process for evaluating academic-clinical partnership effectiveness. The purpose of this study was to explore the potential for multiattribute utility analysis (MAUA) methodology to be applied in the context of academic-clinical partnership evaluation.

Review of the literature: Persistent systemic challenges related to academic-clinical partnership volume and quality require intentional strategies addressing the inherent complexities of the clinical learning environment and contextual differences between academic institutions. Multiattribute utility analysis appears to be a viable existing methodological framework based on its successful application in a wide variety of fields.

Subjects: Directors and Co-Directors of Clinical Education in accredited Doctor of Physical Therapy programs.

Methods: The MAUA methodological framework was used to identify and quantify weighted priorities in factors contributing to partnership effectiveness as perceived by academic-clinical education programs across the United States. Survey participants were invited to share their perspectives regarding priority characteristics and assessment approaches to advance value-based partnership evaluation in physical therapy education.

Results: The products resulting from this contemporary analysis, coupled with the previous applied MAUA simulation, offer a methodology and flexible framework that may be utilized by academic-clinical education faculty to perform a value-based partnership evaluation and make decisions within the context of their institution. Clinical educator survey results also provide a new depth of insight regarding trends in the collective degree of attribute prioritization and the complexity and intersectionality across partnership priorities.

Discussion and conclusion: The proposed processes may allow academic programs to narrow the large number of possible partnership criteria to a manageable subset, offering a way forward for those interested in pursuing a quantitative method for practical decision making. The ability to assess partnership quality using an evidence-based framework such as MAUA may allow partners to maintain, enhance, or discontinue partnerships based on a shared understanding of attribute alignment, rather than reactively coming together in practice to address challenges needing resolution.