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Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits

To examine user uptake and experience with a clinical chatbot that automates hereditary cancer risk triage by collecting personal and family cancer history in routine women's health care settings. METHODS: We conducted a multicenter, retrospective observational study of patients who used a web-...

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Autores principales: Nazareth, Shivani, Hayward, Laura, Simmons, Emilie, Snir, Moran, Hatchell, Kathryn E., Rojahn, Susan, Slotnick, Robert Nathan, Nussbaum, Robert L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8594498/
https://www.ncbi.nlm.nih.gov/pubmed/34735417
http://dx.doi.org/10.1097/AOG.0000000000004596
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author Nazareth, Shivani
Hayward, Laura
Simmons, Emilie
Snir, Moran
Hatchell, Kathryn E.
Rojahn, Susan
Slotnick, Robert Nathan
Nussbaum, Robert L.
author_facet Nazareth, Shivani
Hayward, Laura
Simmons, Emilie
Snir, Moran
Hatchell, Kathryn E.
Rojahn, Susan
Slotnick, Robert Nathan
Nussbaum, Robert L.
author_sort Nazareth, Shivani
collection PubMed
description To examine user uptake and experience with a clinical chatbot that automates hereditary cancer risk triage by collecting personal and family cancer history in routine women's health care settings. METHODS: We conducted a multicenter, retrospective observational study of patients who used a web-based chatbot before routine care appointments to assess their risk for hereditary breast and ovarian cancer, Lynch syndrome, and adenomatous polyposis syndromes. Outcome measures included uptake and completion of the risk-assessment and educational section of the chatbot interaction and identification of hereditary cancer risk as evaluated against National Comprehensive Cancer Network criteria. RESULTS: Of the 95,166 patients invited, 61,070 (64.2%) engaged with the clinical chatbot. The vast majority completed the cancer risk assessment (89.4%), and most completed the genetic testing education section (71.4%), indicating high acceptability among those who opted to engage. The mean duration of use was 15.4 minutes (SD 2 hours, 56.2 minutes) when gaps of inactivity longer than 5 minutes were excluded. A personal history of cancer was reported by 19.1% (10,849/56,656) and a family history of cancer was reported by 66.7% (36,469/54,652) of patients who provided the relevant information. One in four patients (14,850/54,547) screened with the chatbot before routine care appointments met National Comprehensive Cancer Network criteria for genetic testing. Among those who were tested, 5.6% (73/1,313) had a disease-causing pathogenic variant. CONCLUSION: A chatbot digital health tool can help identify patients at high risk for hereditary cancer syndromes before routine care appointments. This scalable intervention can effectively provide cancer risk assessment, engage patients with educational information, and facilitate a path toward preventive genetic testing. FUNDING SOURCE: Implementation of the chatbot in clinics was funded by industry support from commercial genetic testing laboratories Ambry, Invitae, and Progenity.
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spelling pubmed-85944982021-11-19 Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits Nazareth, Shivani Hayward, Laura Simmons, Emilie Snir, Moran Hatchell, Kathryn E. Rojahn, Susan Slotnick, Robert Nathan Nussbaum, Robert L. Obstet Gynecol Contents To examine user uptake and experience with a clinical chatbot that automates hereditary cancer risk triage by collecting personal and family cancer history in routine women's health care settings. METHODS: We conducted a multicenter, retrospective observational study of patients who used a web-based chatbot before routine care appointments to assess their risk for hereditary breast and ovarian cancer, Lynch syndrome, and adenomatous polyposis syndromes. Outcome measures included uptake and completion of the risk-assessment and educational section of the chatbot interaction and identification of hereditary cancer risk as evaluated against National Comprehensive Cancer Network criteria. RESULTS: Of the 95,166 patients invited, 61,070 (64.2%) engaged with the clinical chatbot. The vast majority completed the cancer risk assessment (89.4%), and most completed the genetic testing education section (71.4%), indicating high acceptability among those who opted to engage. The mean duration of use was 15.4 minutes (SD 2 hours, 56.2 minutes) when gaps of inactivity longer than 5 minutes were excluded. A personal history of cancer was reported by 19.1% (10,849/56,656) and a family history of cancer was reported by 66.7% (36,469/54,652) of patients who provided the relevant information. One in four patients (14,850/54,547) screened with the chatbot before routine care appointments met National Comprehensive Cancer Network criteria for genetic testing. Among those who were tested, 5.6% (73/1,313) had a disease-causing pathogenic variant. CONCLUSION: A chatbot digital health tool can help identify patients at high risk for hereditary cancer syndromes before routine care appointments. This scalable intervention can effectively provide cancer risk assessment, engage patients with educational information, and facilitate a path toward preventive genetic testing. FUNDING SOURCE: Implementation of the chatbot in clinics was funded by industry support from commercial genetic testing laboratories Ambry, Invitae, and Progenity. Lippincott Williams & Wilkins 2021-12 2021-11-04 /pmc/articles/PMC8594498/ /pubmed/34735417 http://dx.doi.org/10.1097/AOG.0000000000004596 Text en © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) , where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
spellingShingle Contents
Nazareth, Shivani
Hayward, Laura
Simmons, Emilie
Snir, Moran
Hatchell, Kathryn E.
Rojahn, Susan
Slotnick, Robert Nathan
Nussbaum, Robert L.
Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits
title Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits
title_full Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits
title_fullStr Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits
title_full_unstemmed Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits
title_short Hereditary Cancer Risk Using a Genetic Chatbot Before Routine Care Visits
title_sort hereditary cancer risk using a genetic chatbot before routine care visits
topic Contents
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8594498/
https://www.ncbi.nlm.nih.gov/pubmed/34735417
http://dx.doi.org/10.1097/AOG.0000000000004596
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