Parimbelli Enea, Szymon Wilk, O'Sullivan Dympna, Kingwell Stephen, Michalowski Wojtek, Michalowski Martin
University of Ottawa, Ottawa, ON, Canada.
Poznan University of Technology, Poznan, Poland.
AMIA Annu Symp Proc. 2020 Mar 4;2019:699-706. eCollection 2019.
When deciding about surgical treatment options, an important aspect of the decision-making process is the potential risk of complications. A risk assessment performed by a spinal surgeon is based on their knowledge of the best available evidence and on their own clinical experience. The objective of this work is to demonstrate the differences in the way spine surgeons perceive the importance of attributes used to calculate risk of post-operative and quantify the differences by building individual formal models of risk perceptions. We employ a preference-learning method - ROR-UTADIS - to build surgeon-specific additive value functions for risk of complications. Comparing these functions enables the identification and discussion of differences among personal perceptions of risk factors. Our results show there exist differences in surgeons' perceived factors including primary diagnosis, type of surgery, patient's age, body mass index, or presence of comorbidities.
在决定手术治疗方案时,决策过程中的一个重要方面是并发症的潜在风险。脊柱外科医生进行的风险评估基于他们对现有最佳证据的了解以及自身的临床经验。这项工作的目的是通过构建个体风险认知的正式模型,展示脊柱外科医生在看待用于计算术后风险的属性的重要性方面的差异,并量化这些差异。我们采用一种偏好学习方法——ROR-UTADIS——来构建针对外科医生的并发症风险附加价值函数。比较这些函数能够识别并讨论个人对风险因素认知的差异。我们的结果表明,外科医生所认知的因素存在差异,包括原发性诊断、手术类型、患者年龄、体重指数或合并症的存在情况。