Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study
BACKGROUND: There is a growing focus on the development of multi-factorial cancer risk prediction algorithms alongside tools that operationalise them for clinical use. BOADICEA is a breast and ovarian cancer risk prediction model incorporating genetic and other risk factors. A new user-friendly Web-...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7059924/ https://www.ncbi.nlm.nih.gov/pubmed/32142536 http://dx.doi.org/10.1371/journal.pone.0229999 |
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author | Archer, Stephanie Babb de Villiers, Chantal Scheibl, Fiona Carver, Tim Hartley, Simon Lee, Andrew Cunningham, Alex P. Easton, Douglas F. McIntosh, Jennifer G. Emery, Jon Tischkowitz, Marc Antoniou, Antonis C. Walter, Fiona M. |
author_facet | Archer, Stephanie Babb de Villiers, Chantal Scheibl, Fiona Carver, Tim Hartley, Simon Lee, Andrew Cunningham, Alex P. Easton, Douglas F. McIntosh, Jennifer G. Emery, Jon Tischkowitz, Marc Antoniou, Antonis C. Walter, Fiona M. |
author_sort | Archer, Stephanie |
collection | PubMed |
description | BACKGROUND: There is a growing focus on the development of multi-factorial cancer risk prediction algorithms alongside tools that operationalise them for clinical use. BOADICEA is a breast and ovarian cancer risk prediction model incorporating genetic and other risk factors. A new user-friendly Web-based tool (CanRisk.org) has been developed to apply BOADICEA. This study aimed to explore the acceptability of the prototype CanRisk tool among two healthcare professional groups to inform further development, evaluation and implementation. METHOD: A multi-methods approach was used. Clinicians from primary care and specialist genetics clinics in England, France and Germany were invited to use the CanRisk prototype with two test cases (either face-to-face with a simulated patient or via a written vignette). Their views about the tool were examined via a semi-structured interview or equivalent open-ended questionnaire. Qualitative data were subjected to thematic analysis and organised around Sekhon’s Theoretical Framework of Acceptability. RESULTS: Seventy-five clinicians participated, 21 from primary care and 54 from specialist genetics clinics. Participants were from England (n = 37), France (n = 23) and Germany (n = 15). The prototype CanRisk tool was generally acceptable to most participants due to its intuitive design. Primary care clinicians were concerned about the amount of time needed to complete, interpret and communicate risk information. Clinicians from both settings were apprehensive about the impact of the CanRisk tool on their consultations and lack of opportunities to interpret risk scores before sharing them with their patients. CONCLUSIONS: The findings highlight the challenges associated with developing a complex tool for use in different clinical settings; they also helped refine the tool. This prototype may not have been versatile enough for clinical use in both primary care and specialist genetics clinics where the needs of clinicians are different, emphasising the importance of understanding the clinical context when developing cancer risk assessment tools. |
format | Online Article Text |
id | pubmed-7059924 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-70599242020-03-12 Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study Archer, Stephanie Babb de Villiers, Chantal Scheibl, Fiona Carver, Tim Hartley, Simon Lee, Andrew Cunningham, Alex P. Easton, Douglas F. McIntosh, Jennifer G. Emery, Jon Tischkowitz, Marc Antoniou, Antonis C. Walter, Fiona M. PLoS One Research Article BACKGROUND: There is a growing focus on the development of multi-factorial cancer risk prediction algorithms alongside tools that operationalise them for clinical use. BOADICEA is a breast and ovarian cancer risk prediction model incorporating genetic and other risk factors. A new user-friendly Web-based tool (CanRisk.org) has been developed to apply BOADICEA. This study aimed to explore the acceptability of the prototype CanRisk tool among two healthcare professional groups to inform further development, evaluation and implementation. METHOD: A multi-methods approach was used. Clinicians from primary care and specialist genetics clinics in England, France and Germany were invited to use the CanRisk prototype with two test cases (either face-to-face with a simulated patient or via a written vignette). Their views about the tool were examined via a semi-structured interview or equivalent open-ended questionnaire. Qualitative data were subjected to thematic analysis and organised around Sekhon’s Theoretical Framework of Acceptability. RESULTS: Seventy-five clinicians participated, 21 from primary care and 54 from specialist genetics clinics. Participants were from England (n = 37), France (n = 23) and Germany (n = 15). The prototype CanRisk tool was generally acceptable to most participants due to its intuitive design. Primary care clinicians were concerned about the amount of time needed to complete, interpret and communicate risk information. Clinicians from both settings were apprehensive about the impact of the CanRisk tool on their consultations and lack of opportunities to interpret risk scores before sharing them with their patients. CONCLUSIONS: The findings highlight the challenges associated with developing a complex tool for use in different clinical settings; they also helped refine the tool. This prototype may not have been versatile enough for clinical use in both primary care and specialist genetics clinics where the needs of clinicians are different, emphasising the importance of understanding the clinical context when developing cancer risk assessment tools. Public Library of Science 2020-03-06 /pmc/articles/PMC7059924/ /pubmed/32142536 http://dx.doi.org/10.1371/journal.pone.0229999 Text en © 2020 Archer et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Archer, Stephanie Babb de Villiers, Chantal Scheibl, Fiona Carver, Tim Hartley, Simon Lee, Andrew Cunningham, Alex P. Easton, Douglas F. McIntosh, Jennifer G. Emery, Jon Tischkowitz, Marc Antoniou, Antonis C. Walter, Fiona M. Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study |
title | Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study |
title_full | Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study |
title_fullStr | Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study |
title_full_unstemmed | Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study |
title_short | Evaluating clinician acceptability of the prototype CanRisk tool for predicting risk of breast and ovarian cancer: A multi-methods study |
title_sort | evaluating clinician acceptability of the prototype canrisk tool for predicting risk of breast and ovarian cancer: a multi-methods study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7059924/ https://www.ncbi.nlm.nih.gov/pubmed/32142536 http://dx.doi.org/10.1371/journal.pone.0229999 |
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