{"title":"建造没有地基的房屋?关于重症监护医学人工智能的 24 国定性访谈研究","authors":"Stuart McLennan, Amelia Fiske, Leo Anthony Celi","doi":"10.1136/bmjhci-2024-101052","DOIUrl":null,"url":null,"abstract":"Objectives To explore the views of intensive care professionals in high-income countries (HICs) and lower-to-middle-income countries (LMICs) regarding the use and implementation of artificial intelligence (AI) technologies in intensive care units (ICUs). Methods Individual semi-structured qualitative interviews were conducted between December 2021 and August 2022 with 59 intensive care professionals from 24 countries. Transcripts were analysed using conventional content analysis. Results Participants had generally positive views about the potential use of AI in ICUs but also reported some well-known concerns about the use of AI in clinical practice and important technical and non-technical barriers to the implementation of AI. Important differences existed between ICUs regarding their current readiness to implement AI. However, these differences were not primarily between HICs and LMICs, but between a small number of ICUs in large tertiary hospitals in HICs, which were reported to have the necessary digital infrastructure for AI, and nearly all other ICUs in both HICs and LMICs, which were reported to neither have the technical capability to capture the necessary data or use AI, nor the staff with the right knowledge and skills to use the technology. Conclusion Pouring massive amounts of resources into developing AI without first building the necessary digital infrastructure foundation needed for AI is unethical. Real-world implementation and routine use of AI in the vast majority of ICUs in both HICs and LMICs included in our study is unlikely to occur any time soon. ICUs should not be using AI until certain preconditions are met. Data are available upon reasonable request. Our data include pseudonymised transcripts of interviews, which cannot be made publicly available in their entirety because of (1) the terms of our ethics approval; and (2) because participants could be identifiable if placed in the context of the entire transcript. This is in line with current ethical expectations for qualitative interview research. We provide anonymised quotes within the paper to illustrate our findings (corresponding to transcript excerpts), and the complete interview guide used in the study has been included as a Supplementary Information.","PeriodicalId":9050,"journal":{"name":"BMJ Health & Care Informatics","volume":"38 1","pages":""},"PeriodicalIF":4.1000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Building a house without foundations? A 24-country qualitative interview study on artificial intelligence in intensive care medicine\",\"authors\":\"Stuart McLennan, Amelia Fiske, Leo Anthony Celi\",\"doi\":\"10.1136/bmjhci-2024-101052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objectives To explore the views of intensive care professionals in high-income countries (HICs) and lower-to-middle-income countries (LMICs) regarding the use and implementation of artificial intelligence (AI) technologies in intensive care units (ICUs). Methods Individual semi-structured qualitative interviews were conducted between December 2021 and August 2022 with 59 intensive care professionals from 24 countries. Transcripts were analysed using conventional content analysis. Results Participants had generally positive views about the potential use of AI in ICUs but also reported some well-known concerns about the use of AI in clinical practice and important technical and non-technical barriers to the implementation of AI. Important differences existed between ICUs regarding their current readiness to implement AI. However, these differences were not primarily between HICs and LMICs, but between a small number of ICUs in large tertiary hospitals in HICs, which were reported to have the necessary digital infrastructure for AI, and nearly all other ICUs in both HICs and LMICs, which were reported to neither have the technical capability to capture the necessary data or use AI, nor the staff with the right knowledge and skills to use the technology. Conclusion Pouring massive amounts of resources into developing AI without first building the necessary digital infrastructure foundation needed for AI is unethical. Real-world implementation and routine use of AI in the vast majority of ICUs in both HICs and LMICs included in our study is unlikely to occur any time soon. ICUs should not be using AI until certain preconditions are met. Data are available upon reasonable request. Our data include pseudonymised transcripts of interviews, which cannot be made publicly available in their entirety because of (1) the terms of our ethics approval; and (2) because participants could be identifiable if placed in the context of the entire transcript. This is in line with current ethical expectations for qualitative interview research. We provide anonymised quotes within the paper to illustrate our findings (corresponding to transcript excerpts), and the complete interview guide used in the study has been included as a Supplementary Information.\",\"PeriodicalId\":9050,\"journal\":{\"name\":\"BMJ Health & Care Informatics\",\"volume\":\"38 1\",\"pages\":\"\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMJ Health & Care Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1136/bmjhci-2024-101052\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Health & Care Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/bmjhci-2024-101052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
Building a house without foundations? A 24-country qualitative interview study on artificial intelligence in intensive care medicine
Objectives To explore the views of intensive care professionals in high-income countries (HICs) and lower-to-middle-income countries (LMICs) regarding the use and implementation of artificial intelligence (AI) technologies in intensive care units (ICUs). Methods Individual semi-structured qualitative interviews were conducted between December 2021 and August 2022 with 59 intensive care professionals from 24 countries. Transcripts were analysed using conventional content analysis. Results Participants had generally positive views about the potential use of AI in ICUs but also reported some well-known concerns about the use of AI in clinical practice and important technical and non-technical barriers to the implementation of AI. Important differences existed between ICUs regarding their current readiness to implement AI. However, these differences were not primarily between HICs and LMICs, but between a small number of ICUs in large tertiary hospitals in HICs, which were reported to have the necessary digital infrastructure for AI, and nearly all other ICUs in both HICs and LMICs, which were reported to neither have the technical capability to capture the necessary data or use AI, nor the staff with the right knowledge and skills to use the technology. Conclusion Pouring massive amounts of resources into developing AI without first building the necessary digital infrastructure foundation needed for AI is unethical. Real-world implementation and routine use of AI in the vast majority of ICUs in both HICs and LMICs included in our study is unlikely to occur any time soon. ICUs should not be using AI until certain preconditions are met. Data are available upon reasonable request. Our data include pseudonymised transcripts of interviews, which cannot be made publicly available in their entirety because of (1) the terms of our ethics approval; and (2) because participants could be identifiable if placed in the context of the entire transcript. This is in line with current ethical expectations for qualitative interview research. We provide anonymised quotes within the paper to illustrate our findings (corresponding to transcript excerpts), and the complete interview guide used in the study has been included as a Supplementary Information.