Patient perspectives on AI-based decision support in surgery.

IF 2.1 Q2 SURGERY
BMJ Surgery Interventions Health Technologies Pub Date : 2025-04-02 eCollection Date: 2025-01-01 DOI:10.1136/bmjsit-2024-000365
Sara Ben Hmido, Houssam Abder Rahim, Corrette Ploem, Saskia Haitjema, Olga Damman, Geert Kazemier, Freek Daams
{"title":"Patient perspectives on AI-based decision support in surgery.","authors":"Sara Ben Hmido, Houssam Abder Rahim, Corrette Ploem, Saskia Haitjema, Olga Damman, Geert Kazemier, Freek Daams","doi":"10.1136/bmjsit-2024-000365","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Predictive machine learning in healthcare, especially in surgical decisions, is advancing swiftly. Yet, literature on patient views regarding predictive machine learning, specifically its use throughout the clinical course, is scarce. Views among patients who underwent colorectal surgery (CRS) on the use of intra-operative predictive machine learning (IPML) by surgeons, particularly those aiming to predict colorectal anastomotic leakage (CAL), were explored in this study.</p><p><strong>Objective: </strong>This study investigated the views of patients who previously underwent CRS on the implementation of IPML models. Domains of interest were perceptions of IPML, perceived role in decision-making and information provided in the clinical encounter.</p><p><strong>Methods: </strong>A qualitative research design was employed, using focus groups and semi-structured interviews with patients who had undergone CRS. Descriptive thematic analysis was used to analyse data and identify prevailing themes and attitudes. The associations in the code tree were established based on a co-occurrence table. The patient sample size was determined using a saturation analysis.</p><p><strong>Results: </strong>A study with n=19 participants across four focus groups and seven interviews found a generally positive perception regarding the use of IPML models in CRS. Participants recognised their potential to enhance surgical decision-making but stressed the surgeon's role as the primary decision-maker, suggesting IPML models act as advisory tools, with surgeons able to override recommendations. Personalised communication and consideration of quality of life were emphasised, highlighting the need for a balanced integration of IPML models to support clinical judgement and the construction of patient preferences.</p><p><strong>Conclusion: </strong>IPML in CRS is well-received by participants, provided that surgeons retain the ability to override model recommendations and document their decisions transparently. Trust in the surgeon remains a key factor in patient acceptance of IPML, reinforcing the need for clear explanations during consultation sessions. Regardless of the use of IPML, tailoring patient communication and addressing the quality-of-life impacts of anastomosis vs stoma are also critical.</p>","PeriodicalId":33349,"journal":{"name":"BMJ Surgery Interventions Health Technologies","volume":"7 1","pages":"e000365"},"PeriodicalIF":2.1000,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11966983/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Surgery Interventions Health Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/bmjsit-2024-000365","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"SURGERY","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Predictive machine learning in healthcare, especially in surgical decisions, is advancing swiftly. Yet, literature on patient views regarding predictive machine learning, specifically its use throughout the clinical course, is scarce. Views among patients who underwent colorectal surgery (CRS) on the use of intra-operative predictive machine learning (IPML) by surgeons, particularly those aiming to predict colorectal anastomotic leakage (CAL), were explored in this study.

Objective: This study investigated the views of patients who previously underwent CRS on the implementation of IPML models. Domains of interest were perceptions of IPML, perceived role in decision-making and information provided in the clinical encounter.

Methods: A qualitative research design was employed, using focus groups and semi-structured interviews with patients who had undergone CRS. Descriptive thematic analysis was used to analyse data and identify prevailing themes and attitudes. The associations in the code tree were established based on a co-occurrence table. The patient sample size was determined using a saturation analysis.

Results: A study with n=19 participants across four focus groups and seven interviews found a generally positive perception regarding the use of IPML models in CRS. Participants recognised their potential to enhance surgical decision-making but stressed the surgeon's role as the primary decision-maker, suggesting IPML models act as advisory tools, with surgeons able to override recommendations. Personalised communication and consideration of quality of life were emphasised, highlighting the need for a balanced integration of IPML models to support clinical judgement and the construction of patient preferences.

Conclusion: IPML in CRS is well-received by participants, provided that surgeons retain the ability to override model recommendations and document their decisions transparently. Trust in the surgeon remains a key factor in patient acceptance of IPML, reinforcing the need for clear explanations during consultation sessions. Regardless of the use of IPML, tailoring patient communication and addressing the quality-of-life impacts of anastomosis vs stoma are also critical.

求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
2.80
自引率
0.00%
发文量
22
审稿时长
17 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信