Cancer care at the time of the fourth industrial revolution: an insight to healthcare professionals’ perspectives on cancer care and artificial intelligence

Radiation Oncology

Research

Andreas Charalambous¹  Wanda Acampa²  Jasmina Boban³  Maria Lavdaniti⁴  Evangelia Stalika⁵  Debbie-Rose Dolton⁶  Lithin Zacharias⁶  Reem Kayyali⁶  Iman Hesso⁶  Kwanyoung Joo⁶  Shereen Nabhani-Gebara⁶  Tarek Ajami⁷ 

[1] Cyprus University of Technology, Limassol, Cyprus;University of Turku, Turku, Finland;Department of Advanced Biomedical Science, University of Naples Federico II, Naples, Italy;Department of Radiology, Faculty of Medicine, University of Novi Sad, Hajduk Veljkova 3, 21000, Novi Sad, Serbia;Diagnostic Imaging Center, Oncology Institute of Vojvodine, Put Dr Goldmana 4, 21204, Sremska Kamenica, Serbia;International Hellenic University, Thessaloniki, Greece;International Hellenic University, Thessaloniki, Greece;Aristotle University of Thessaloniki, Thessaloniki, Greece;School of Life Sciences, Pharmacy and Chemistry, Kingston University London, Penrhyn Road, KT1 2EE, Kingston Upon Thames, UK;Urology Department, Hospital Clinic de Barcelona, Barcelona, Spain;

关键词: Artificial intelligence;    Cancer care;    Challenges;    Experiences;    Interviews;    Healthcare professionals;    Machine learning;    Perceptions;    Survey;   

DOI  :  10.1186/s13014-023-02351-z

 received in 2023-02-22, accepted in 2023-09-13,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundThe integration of Artificial Intelligence (AI) technology in cancer care has gained unprecedented global attention over the past few decades. This has impacted the way that cancer care is practiced and delivered across settings. The purpose of this study was to explore the perspectives and experiences of healthcare professionals (HCPs) on cancer treatment and the need for AI. This study is a part of the INCISIVE European Union H2020 project's development of user requirements, which aims to fully explore the potential of AI-based cancer imaging technologies.MethodsA mixed-methods research design was employed. HCPs participating in cancer care in the UK, Greece, Italy, Spain, Cyprus, and Serbia were first surveyed anonymously online. Twenty-seven HCPs then participated in semi-structured interviews. Appropriate statistical method was adopted to report the survey results by using SPSS. The interviews were audio recorded, verbatim transcribed, and then thematically analysed supported by NVIVO.ResultsThe survey drew responses from 95 HCPs. The occurrence of diagnostic delay was reported by 56% (n = 28/50) for breast cancer, 64% (n = 27/42) for lung cancer, 76% (n = 34/45) for colorectal cancer and 42% (n = 16/38) for prostate cancer. A proportion of participants reported the occurrence of false positives in the accuracy of the current imaging techniques used: 64% (n = 32/50) reported this for breast cancer, 60% (n = 25/42) for lung cancer, 51% (n = 23/45) for colorectal cancer and 45% (n = 17/38) for prostate cancer. All participants agreed that the use of technology would enhance the care pathway for cancer patients. Despite the positive perspectives toward AI, certain limitations were also recorded. The majority (73%) of respondents (n = 69/95) reported they had never utilised technology in the care pathway which necessitates the need for education and training in the qualitative finding; compared to 27% (n = 26/95) who had and were still using it. Most, 89% of respondents (n = 85/95) said they would be opened to providing AI-based services in the future to improve medical imaging for cancer care.Interviews with HCPs revealed lack of widespread preparedness for AI in oncology, several barriers to introducing AI, and a need for education and training. Provision of AI training, increasing public awareness of AI, using evidence-based technology, and developing AI based interventions that will not replace HCPs were some of the recommendations.ConclusionHCPs reported favourable opinions of AI-based cancer imaging technologies and noted a number of care pathway concerns where AI can be useful. For the future design and execution of the INCISIVE project and other comparable AI-based projects, the characteristics and recommendations offered in the current research can serve as a reference.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

【 图 表 】

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