Imperial College London
Alternate

Professor the Lord Darzi of Denham PC KBE FRS FMedSci HonFREng

Faculty of Medicine, Department of Surgery & Cancer

Co-Director of the IGHI, Professor of Surgery
 
 
 
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Contact

 

+44 (0)20 3312 1310a.darzi

 
 
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Location

 

Queen Elizabeth the Queen Mother Wing (QEQM)St Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Gardner:2022:10.1177/14604582221087890,
author = {Gardner, C and Halligan, J and Fontana, G and Fernandez, Crespo R and Prime, M and Guo, C and Ekinci, O and Ghafur, S and Darzi, A},
doi = {10.1177/14604582221087890},
journal = {Health Informatics Journal},
title = {Evaluation of a clinical decision support tool for matching cancer patients to clinical trials using simulation-based research},
url = {http://dx.doi.org/10.1177/14604582221087890},
volume = {28},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - There is a growing need for alternative methodologies to evaluate digital health solutions in a short timeframe and at relatively low cost. Simulation-based research (SBR) methods have been proposed as an alternative methodology for evaluating digital health solutions; however, few studies have described the applicability of SBR methods to evaluate such solutions. This study used SBR to evaluate the feasibility and user experience of a clinical decision support (CDS) tool used for matching cancer patients to clinical trials. Twenty-five clinicians and research staff were recruited to match 10 synthetic patient cases to clinical trials using both the CDS tool and publicly available online trial databases. Participants were significantly more likely to report having sufficient time (p = 0.020) and to require less mental effort (p = 0.001) to complete trial matching with the CDS tool. Participants required less time for trial matching using the CDS tool, but the difference was not significant (p = 0.093). Most participants reported that they had sufficient guidance to participate in the simulations (96%). This study demonstrates the use of SBR methods is a feasible approach to evaluate digital health solutions and to collect valuable user feedback without the need for implementation in clinical practice. Further research is required to demonstrate the feasibility of using SBR to conduct remote evaluations of digital health solutions.
AU  - Gardner,C
AU  - Halligan,J
AU  - Fontana,G
AU  - Fernandez,Crespo R
AU  - Prime,M
AU  - Guo,C
AU  - Ekinci,O
AU  - Ghafur,S
AU  - Darzi,A
DO  - 10.1177/14604582221087890
PY  - 2022///
SN  - 1460-4582
TI  - Evaluation of a clinical decision support tool for matching cancer patients to clinical trials using simulation-based research
T2  - Health Informatics Journal
UR  - http://dx.doi.org/10.1177/14604582221087890
UR  - https://journals.sagepub.com/doi/10.1177/14604582221087890
UR  - http://hdl.handle.net/10044/1/95385
VL  - 28
ER  -
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