Using DEMATEL Technique to Identify the Key Success Factors of Shared Decision-Making Based on Influential Network Relationship Perspective
Author(s) -
Wenyi Liu,
TaoHsin Tung,
YenChing Chuang,
ChingWen Chien
Publication year - 2021
Publication title -
journal of healthcare engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.509
H-Index - 29
eISSN - 2040-2309
pISSN - 2040-2295
DOI - 10.1155/2021/6618818
Subject(s) - flexibility (engineering) , process (computing) , key (lock) , perspective (graphical) , knowledge management , field (mathematics) , computer science , management science , process management , artificial intelligence , engineering , statistics , mathematics , computer security , pure mathematics , operating system
In the field of medicine, shared decision-making (SDM) is an important issue primarily aimed at resolving the problem of information asymmetry between clinicians and patients in the selection of treatment options and follow-up nursing plans. Most previous studies on this topic have focused on key elements and the development and implementation of SDM scales. This study used the decision-making trial and evaluation laboratory (DEMATEL) method to establish a network of influence relationships among factors that are keys to the success of the SDM process. Survey data were obtained from a well-known brain hospital in China. The key factors of success included tailor information, flexibility approach, check understanding patient, document (discussion about) decision, present evidence, make or explicitly defer decision, and patient values and preferences. We determined that clinicians should provide a series of treatment options and follow-up care plans based on a patientʼs conditions and preferences. Clinicians should also actively communicate with patients and their families to ensure a thorough understanding of the entire treatment and nursing process. This study also highlights the academic value of the cross-disciplinary integration of medical decision issues and multiple attribute decision-making methodologies.
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