Kelley C Wood1,2, Mackenzi Pergolotti3,4, Tim Marshall5, Heather J Leach6,7, Julia L Sharp8, Grace Campbell9,10, Grant R Williams11, Jack B Fu12, Tiffany D Kendig3, Nancy Howe13, Anita Bundy4. 1. ReVital Cancer Rehabilitation, Select Medical, Mechanicsburg, PA, USA. kecovington@selectmedical.com. 2. Department of Occupational Therapy, Colorado State University, Fort Collins, CO, USA. kecovington@selectmedical.com. 3. ReVital Cancer Rehabilitation, Select Medical, Mechanicsburg, PA, USA. 4. Department of Occupational Therapy, Colorado State University, Fort Collins, CO, USA. 5. Ivy Rehab Network, White Plains, NY, USA. 6. Department of Health and Exercise Science, Colorado State University, Fort Collins, USA. 7. Department of Community and Behavioral Health, Colorado School of Public Health, Aurora, USA. 8. Department of Statistics, Colorado State University, Fort Collins, CO, USA. 9. Duquesne University School of Nursing, UPMC Hillman Cancer Center at UPMC Magee Women's Hospital, Pittsburgh, USA. 10. Department of Obstetrics, Gynecology, and Reproductive Science (Adjunct), University of Pittsburgh School of Medicine, Pittsburgh, USA. 11. Department of Medicine, Division of Hematology/Oncology, University of Alabama at Birmingham, Birmingham, AL, USA. 12. Department of Palliative, Rehabilitation & Integrative Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA. 13. Edson College of Nursing and Health Innovation, Arizona State University, Phoenix, AZ, USA.
Abstract
INTRODUCTION: Oncology guidelines recommend participation in cancer rehabilitation or exercise services (CR/ES) to optimize survivorship. Yet, connecting the right survivor, with the right CR/ES, at the right time remains a challenge. The Exercise in Cancer Evaluation and Decision Support (EXCEEDS) algorithm was developed to enhance CR/ES clinical decision-making and facilitate access to CR/ES. We used Delphi methodology to evaluate usability, acceptability, and determine pragmatic implementation priorities. METHODS: Participants completed three online questionnaires including (1) simulated case vignettes, (2) 4-item acceptability questionnaire (0-5 pts), and (3) series of items to rank algorithm implementation priorities (potential users, platforms, strategies). To evaluate usability, we used Chi-squared test to compare frequency of accurate pre-exercise medical clearance and CR/ES triage recommendations for case vignettes when using EXCEEDS vs. without. We calculated mean acceptability and inter-rater agreement overall and in 4 domains. We used the Eisenhower Prioritization Method to evaluate implementation priorities. RESULTS: Participants (N = 133) mostly represented the fields of rehabilitation (69%), oncology (25%), or exercise science (17%). When using EXCEEDS (vs. without), their recommendations were more likely to be guideline concordant for medical clearance (83.4% vs. 66.5%, X2 = 26.61, p < .0001) and CR/ES triage (60.9% vs. 51.1%, X2 = 73.79, p < .0001). Mean acceptability was M = 3.90 ± 0.47; inter-rater agreement was high for 3 of 4 domains. Implementation priorities include 1 potential user group, 2 platform types, and 9 implementation strategies. CONCLUSION: This study demonstrates the EXCEEDS algorithm can be a pragmatic and acceptable clinical decision support tool for CR/ES recommendations. Future research is needed to evaluate algorithm usability and acceptability in real-world clinical pathways.
INTRODUCTION: Oncology guidelines recommend participation in cancer rehabilitation or exercise services (CR/ES) to optimize survivorship. Yet, connecting the right survivor, with the right CR/ES, at the right time remains a challenge. The Exercise in Cancer Evaluation and Decision Support (EXCEEDS) algorithm was developed to enhance CR/ES clinical decision-making and facilitate access to CR/ES. We used Delphi methodology to evaluate usability, acceptability, and determine pragmatic implementation priorities. METHODS: Participants completed three online questionnaires including (1) simulated case vignettes, (2) 4-item acceptability questionnaire (0-5 pts), and (3) series of items to rank algorithm implementation priorities (potential users, platforms, strategies). To evaluate usability, we used Chi-squared test to compare frequency of accurate pre-exercise medical clearance and CR/ES triage recommendations for case vignettes when using EXCEEDS vs. without. We calculated mean acceptability and inter-rater agreement overall and in 4 domains. We used the Eisenhower Prioritization Method to evaluate implementation priorities. RESULTS: Participants (N = 133) mostly represented the fields of rehabilitation (69%), oncology (25%), or exercise science (17%). When using EXCEEDS (vs. without), their recommendations were more likely to be guideline concordant for medical clearance (83.4% vs. 66.5%, X2 = 26.61, p < .0001) and CR/ES triage (60.9% vs. 51.1%, X2 = 73.79, p < .0001). Mean acceptability was M = 3.90 ± 0.47; inter-rater agreement was high for 3 of 4 domains. Implementation priorities include 1 potential user group, 2 platform types, and 9 implementation strategies. CONCLUSION: This study demonstrates the EXCEEDS algorithm can be a pragmatic and acceptable clinical decision support tool for CR/ES recommendations. Future research is needed to evaluate algorithm usability and acceptability in real-world clinical pathways.
Authors: Kathryn H Schmitz; Anna M Campbell; Martijn M Stuiver; Bernardine M Pinto; Anna L Schwartz; G Stephen Morris; Jennifer A Ligibel; Andrea Cheville; Daniel A Galvão; Catherine M Alfano; Alpa V Patel; Trisha Hue; Lynn H Gerber; Robert Sallis; Niraj J Gusani; Nicole L Stout; Leighton Chan; Fiona Flowers; Colleen Doyle; Susan Helmrich; William Bain; Jonas Sokolof; Kerri M Winters-Stone; Kristin L Campbell; Charles E Matthews Journal: CA Cancer J Clin Date: 2019-10-16 Impact factor: 508.702
Authors: Sarah J Hardcastle; Chloe Maxwell-Smith; Sviatlana Kamarova; Stephanie Lamb; Lesley Millar; Paul A Cohen Journal: Support Care Cancer Date: 2017-10-31 Impact factor: 3.603
Authors: Michelle Nadler; Daryl Bainbridge; Jennifer Tomasone; Oren Cheifetz; Rosalyn A Juergens; Jonathan Sussman Journal: Support Care Cancer Date: 2017-03-03 Impact factor: 3.603
Authors: Nicole L Stout; Justin C Brown; Anna L Schwartz; Timothy F Marshall; Anna M Campbell; Larissa Nekhlyudov; David S Zucker; Karen M Basen-Engquist; Grace Campbell; Jeffrey Meyerhardt; Andrea L Cheville; Kelley R Covington; Jennifer A Ligibel; Jonas M Sokolof; Kathryn H Schmitz; Catherine M Alfano Journal: Cancer Date: 2020-03-25 Impact factor: 6.860
Authors: Alpa V Patel; Christine M Friedenreich; Steven C Moore; Sandra C Hayes; Julie K Silver; Kristin L Campbell; Kerri Winters-Stone; Lynn H Gerber; Stephanie M George; Janet E Fulton; Crystal Denlinger; G Stephen Morris; Trisha Hue; Kathryn H Schmitz; Charles E Matthews Journal: Med Sci Sports Exerc Date: 2019-11 Impact factor: 5.411
Authors: Kristin L Campbell; Kerri M Winters-Stone; Joachim Wiskemann; Anne M May; Anna L Schwartz; Kerry S Courneya; David S Zucker; Charles E Matthews; Jennifer A Ligibel; Lynn H Gerber; G Stephen Morris; Alpa V Patel; Trisha F Hue; Frank M Perna; Kathryn H Schmitz Journal: Med Sci Sports Exerc Date: 2019-11 Impact factor: 5.411
Authors: Kelley R Covington; Timothy Marshall; Grace Campbell; Grant R Williams; Jack B Fu; Tiffany D Kendig; Nancy Howe; Catherine M Alfano; Mackenzi Pergolotti Journal: Support Care Cancer Date: 2021-04-26 Impact factor: 3.603