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

Abstract

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