인공지능 왓슨과 다학제 진료의 치료방법 일치율 평가 및 의료진 만족도 조사Concordance Assessment and Satisfaction of Medical Professionals for the Artificial Intelligence Watson
- Other Titles
- Concordance Assessment and Satisfaction of Medical Professionals for the Artificial Intelligence Watson
- Authors
- 이경아; 김찬희; 백정흠; 심선진; 안희경; 이언; 이선희
- Issue Date
- Dec-2019
- Publisher
- 한국보건의료기술평가학회
- Keywords
- Artificial intelligence · Multidisciplinary care · Analysis effect.
- Citation
- 보건의료기술평가, v.7, no.2, pp.112 - 118
- Journal Title
- 보건의료기술평가
- Volume
- 7
- Number
- 2
- Start Page
- 112
- End Page
- 118
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/19305
- ISSN
- 2288-5811
- Abstract
- The purpose of this prospective study was to examine the concordance rate of diagnosis and treatment between Watson for Oncology(WFO) and multidisciplinary tumor board, and to evaluate the satisfaction of medical professionals about WFO. Methods: The subject of this study was 126 patients with cancer and 54 medical professionals who participate in WFO multidisciplinary care at Gachon University Gil Medical Center in Korea. Concordance rate between the WFO and the multidisciplinary tumor board was measured by the concurrence between the WFO presentation and the final decision of the medical staffs. Satisfaction of medical professionals was measured with a questionnaire that identifies satisfaction, intention of use, and the strengths and weaknesses of WFO. Results: In 121 cases (96.0%), the recommendation and consideration presented by WFO were consistent with the final treatment method. The overall satisfaction for WFO was 6.74±2.08 out of 10. The strength of WFO that medical staffs thought was found to be hospital publicity (4.11±0.78) and patient compliance increase (3.98±0.64). The weakness of WFO was that it did not consider ethnic and cultural differences (3.63±0.98) and that it did not reflect the health insurance cost in Korea (3.61± 0.96). Conclusion: WFO has a high concordance rate when deciding on treatment options, while there are some limitations in the reflection of national racial, regional, cultural and environmental differences and the application of patients in specific situations. It is expected to be used as a basic data for developing Korean artificial intelligence Watson model by grasping the needs and improvement of localized WFO.
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