TY - JOUR
T1 - Usability, acceptability, and implementation strategies for the Exercise in Cancer Evaluation and Decision Support (EXCEEDS) algorithm
T2 - a Delphi study
AU - Wood, Kelley C.
AU - Pergolotti, Mackenzi
AU - Marshall, Tim
AU - Leach, Heather J.
AU - Sharp, Julia L.
AU - Campbell, Grace
AU - Williams, Grant R.
AU - Fu, Jack B.
AU - Kendig, Tiffany D.
AU - Howe, Nancy
AU - Bundy, Anita
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2022/9
Y1 - 2022/9
N2 - 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.
AB - 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.
KW - Algorithm
KW - Cancer
KW - Exercise
KW - Rehabilitation
KW - Survivorship
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U2 - 10.1007/s00520-022-07164-6
DO - 10.1007/s00520-022-07164-6
M3 - Article
C2 - 35614154
AN - SCOPUS:85136139904
SN - 0941-4355
VL - 30
SP - 7407
EP - 7418
JO - Supportive Care in Cancer
JF - Supportive Care in Cancer
IS - 9
ER -