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Best–worst scaling methodology to evaluate constructs of the Consolidated Framework for Implementation Research: application to the implementation of pharmacogenetic testing for antidepressant therapy

  • Ramzi G. Salloum
  • , Jeffrey R. Bishop
  • , Amanda L. Elchynski
  • , D. Max Smith
  • , Elizabeth Rowe
  • , Kathryn V. Blake
  • , Nita A. Limdi
  • , Christina L. Aquilante
  • , Jill Bates
  • , Amber L. Beitelshees
  • , Amber Cipriani
  • , Benjamin Q. Duong
  • , Philip E. Empey
  • , Christine M. Formea
  • , J. Kevin Hicks
  • , Pawel Mroz
  • , David Oslin
  • , Amy L. Pasternak
  • , Natasha Petry
  • , Laura B. Ramsey
  • Allyson Schlichte, Sandra M. Swain, Kristen M. Ward, Kristin Wiisanen, Todd C. Skaar, Sara L. Van Driest, Larisa H. Cavallari, Sony Tuteja
  • University of Florida
  • University of Minnesota Twin Cities
  • Georgetown University
  • Indiana University Bloomington
  • Alfred I. duPont Hospital for Children
  • University of Alabama at Birmingham
  • University of Colorado Anschutz Medical Campus
  • Durham VA Health Care System
  • University of Maryland, Baltimore
  • University of North Carolina at Chapel Hill
  • University of Pittsburgh
  • Primary Children's Medical Center
  • University of South Florida
  • VA Medical Center
  • University of Michigan, Ann Arbor
  • North Dakota State University
  • Cincinnati Children's Hospital Medical Center
  • Fairview Pharmacy Services
  • Vanderbilt University
  • University of Pennsylvania

Producción científicarevisión exhaustiva

12 Citas (Scopus)

Resumen

Background: Despite the increased demand for pharmacogenetic (PGx) testing to guide antidepressant use, little is known about how to implement testing in clinical practice. Best–worst scaling (BWS) is a stated preferences technique for determining the relative importance of alternative scenarios and is increasingly being used as a healthcare assessment tool, with potential applications in implementation research. We conducted a BWS experiment to evaluate the relative importance of implementation factors for PGx testing to guide antidepressant use. Methods: We surveyed 17 healthcare organizations that either had implemented or were in the process of implementing PGx testing for antidepressants. The survey included a BWS experiment to evaluate the relative importance of Consolidated Framework for Implementation Research (CFIR) constructs from the perspective of implementing sites. Results: Participating sites varied on their PGx testing platform and methods for returning recommendations to providers and patients, but they were consistent in ranking several CFIR constructs as most important for implementation: patient needs/resources, leadership engagement, intervention knowledge/beliefs, evidence strength and quality, and identification of champions. Conclusions: This study demonstrates the feasibility of using choice experiments to systematically evaluate the relative importance of implementation determinants from the perspective of implementing organizations. BWS findings can inform other organizations interested in implementing PGx testing for mental health. Further, this study demonstrates the application of BWS to PGx, the findings of which may be used by other organizations to inform implementation of PGx testing for mental health disorders.

Idioma originalEnglish
Número de artículo52
PublicaciónImplementation Science Communications
Volumen3
N.º1
DOI
EstadoPublished - dic 2022

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