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

doi:10.1186/s43058-022-00300-7

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

Implement Sci Commun. 2022 May 14;3(1):52. doi: 10.1186/s43058-022-00300-7.

Authors

Ramzi G Salloum^{1

2}, Jeffrey R Bishop^{3

4}, Amanda L Elchynski⁵, D Max Smith⁶, Elizabeth Rowe⁷, Kathryn V Blake⁸, Nita A Limdi⁹, Christina L Aquilante¹⁰, Jill Bates¹¹, Amber L Beitelshees¹², Amber Cipriani¹³, Benjamin Q Duong¹⁴, Philip E Empey¹⁵, Christine M Formea¹⁶, J Kevin Hicks¹⁷, Pawel Mroz³, David Oslin¹⁸, Amy L Pasternak¹⁹, Natasha Petry²⁰, Laura B Ramsey²¹, Allyson Schlichte²², Sandra M Swain⁶, Kristen M Ward¹⁹, Kristin Wiisanen⁵, Todd C Skaar⁷, Sara L Van Driest²³, Larisa H Cavallari^{1

5}, Sony Tuteja²⁴

Affiliations

¹ University of Florida Clinical and Translational Science Institute, Gainesville, FL, USA.
² University of Florida College of Medicine, Gainesville, FL, USA.
³ University of Minnesota Medical School, Minneapolis, MN, USA.
⁴ University of Minnesota College of Pharmacy, Minneapolis, MN, USA.
⁵ University of Florida College of Pharmacy, Gainesville, FL, USA.
⁶ MedStar Health, Georgetown University Medical Center, Washington, DC, USA.
⁷ Indiana University School of Medicine, Indianapolis, IN, USA.
⁸ Nemours Children's Health, Jacksonville, FL, USA.
⁹ University of Alabama Heersink School of Medicine, Birmingham, AL, USA.
¹⁰ School of Medicine and Pharmacy, University of Colorado, Aurora, CO, USA.
¹¹ Durham VA Healthcare System, Durham, NC, USA.
¹² University of Maryland School of Medicine, Baltimore, MD, USA.
¹³ University of North Carolina Medical Center, Chapel Hill, NC, USA.
¹⁴ Nemours Children's Health, Wilmington, DE, USA.
¹⁵ University of Pittsburgh School of Pharmacy, Pittsburgh, PA, USA.
¹⁶ Intermountain Healthcare, Salt Lake City, UT, USA.
¹⁷ Moffitt Cancer Center, Tampa, FL, USA.
¹⁸ Corporal Michael J. Cresenz VA Medical Center, Philadelphia, PA, USA.
¹⁹ University of Michigan College of Pharmacy, Ann Arbor, MI, USA.
²⁰ North Dakota State University/Sanford Health, Fargo, ND, USA.
²¹ Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
²² Fairview Pharmacy Services, Minneapolis, MN, USA.
²³ Vanderbilt University Medical Center, Nashville, TN, USA.
²⁴ University of Pennsylvania Perelman School of Medicine, Smilow Center for Translational Research, 3400 Civic Center Boulevard, Bldg. 421 11th Floor, Room 143, Philadelphia, PA, 19104-5158, USA. sonyt@pennmedicine.upenn.edu.

Abstract

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.

Keywords: Best–worst scaling; Consolidated Framework for Implementation Research; Pharmacogenetic testing.

Abstract

Grants and funding