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• W3118466408 abstract "Abstract Background Shared decision making (SDM) for life-critical diseases or conditions is a crucial type of SDM. This type of SDM is still greatly underdeveloped and it faces a number of key challenges. The main goal of this study is to identify the challenges that impede the development and use of life-critical SDM. Methods This is a hybrid research and systematic / narrative review paper. Its results were derived by analyzing reviews already conducted by the authors when they were working on six recently published papers. These papers had collectively required two systematic reviews and four narrative reviews. The topics covered in the six published papers were related to computer-aided diagnosis (CAD) in medicine, the analysis of health state utilities, and the selection of the best treatment for life-critical diseases / conditions. A new narrative review was also executed to explore some new issues. Results The key challenges for life-critical SDM relate to the following aspects: The mathematical models used to make the decisions, the data used to feed these models, the role the patient plays within the SDM framework, and finally, the role healthcare professionals play along with the pertinent rules and regulations that guide the use of this type of SDM today. Conclusions Life-critical SDM is the most important type of SDM. However, some challenges impede its successful development and use. A number of developments and enhancements need to be made urgently for this type of SDM to become widely acceptable and useful. The seven key challenges identified in this study and the suggested directions for future research offer a compelling path towards elevating life-critical SDM to the next level and do so both effectively and efficiently." @default.
• W3118466408 created "2021-01-18" @default.
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• W3118466408 date "2021-04-01" @default.
• W3118466408 modified "2023-09-28" @default.
• W3118466408 title "The seven key challenges for life-critical shared decision making systems" @default.
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• W3118466408 doi "https://doi.org/10.1016/j.ijmedinf.2021.104377" @default.
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