Imperial College London
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Dr Tayana Soukup PhD CPsychol FRSPH

Faculty of Medicine, Department of Surgery & Cancer

Research Fellow in Human Factors - Artificial Intelligence
 
 
 
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Contact

 

t.soukup

 
 
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Location

 

508Medical SchoolSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{Soukup:2019:osf.io/qzwf8,
author = {Soukup, T and Morbi, A and Lamb, BW and Gandamihardja, T and Hogben, K and Noyes, K and Skolarus, T and Darzi, A and Sevdalis, N and Green, J},
doi = {osf.io/qzwf8},
title = {A measure of case complexity for cancer multidisciplinary teams: Development and early validation of the MeDiC tool},
url = {http://dx.doi.org/10.31234/osf.io/qzwf8},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - <p>Background and Objective. There is increasing emphasis in cancer care globally for care to be reviewed and managed by multidisciplinary teams (i.e., in tumor boards). Evidence and recommendations suggest that the complexity of each patient case needs to be considered as care is planned, however no tool currently exists for cancer teams to do so. We report the development and early validation of such a tool.Methods. We used a mixed-methods approach involving psychometric evaluation and expert review to develop the Measure of case-Discussion Complexity (MeDiC) between May 2014 and November 2016. The study ran in 6 phases and included ethnographic interviews, observations, surveys, feasibility and reliability testing, expert consensus, and multiple expert-team reviews.Results. Phase-1: case complexity factors identified through literature review and expert interviews; Phase-2: 51 factors subjected to iterative review and content validation by 9 cancer teams across 4 England Trusts with 9 further items identified; Phase 3: 60-items subjected to expert review distilled to the most relevant; Phase 4: item weighing and further content validation through a national UK survey. Phases 5 and 6: excellent inter-assessor reliability between clinical and non-clinical observers, and adequate validity on 903 video case-discussions achieved. A final set of 27 factors, measuring clinical and logistical complexities were integrated into MeDiC.Conclusions. MeDiC is an evidence-based and expert-driven tool that gauges the complexity of cancer cases. MeDiC may be used as a clinical quality assurance and screening tool for tumor board consideration through case selection and prioritization.</p>
AU  - Soukup,T
AU  - Morbi,A
AU  - Lamb,BW
AU  - Gandamihardja,T
AU  - Hogben,K
AU  - Noyes,K
AU  - Skolarus,T
AU  - Darzi,A
AU  - Sevdalis,N
AU  - Green,J
DO  - osf.io/qzwf8
PY  - 2019///
TI  - A measure of case complexity for cancer multidisciplinary teams: Development and early validation of the MeDiC tool
UR  - http://dx.doi.org/10.31234/osf.io/qzwf8
ER  -
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