Development of an evidence-based decision pathway for vestibular schwannoma treatment options

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• 作者：Faina Linkov ; PhD^a ; ^b ; ^{linkfy@mail.upmc.edu} ; Benita Valappil ; MPH^d ; Jacob McAfee ; MD^d ; Sharon L. Goughnour ; MPH^a ; Douglas M. Hildrew ; MD^d ; Andrew A. McCall ; MD^d ; Igor Linkov ; PhD^c ; Barry Hirsch ; MD^d ; Carl Snyderman ; MD ; MBA^d
• 刊名：American Journal of Otolaryngology
• 出版年：2017
• 出版时间：January-February 2017
• 年：2017
• 卷：38
• 期：1
• 页码：57-64
• 全文大小：564 K
• 卷排序：38

文摘

To integrate multiple sources of clinical information with patient feedback to build evidence-based decision support model to facilitate treatment selection for patients suffering from vestibular schwannomas (VS).MethodsThis was a mixed methods study utilizing focus group and survey methodology to solicit feedback on factors important for making treatment decisions among patients. Two 90-minute focus groups were conducted by an experienced facilitator. Previously diagnosed VS patients were recruited by clinical investigators at the University of Pittsburgh Medical Center (UPMC). Classical content analysis was used for focus group data analysis. Providers were recruited from practices within the UPMC system and were surveyed using Delphi methods. This information can provide a basis for multi-criteria decision analysis (MCDA) framework to develop a treatment decision support system for patients with VS.ResultsEight themes were derived from these data (focus group + surveys): doctor/health care system, side effects, effectiveness of treatment, anxiety, mortality, family/other people, quality of life, and post-operative symptoms. These data, as well as feedback from physicians were utilized in building a multi-criteria decision model.DiscussionThe study illustrated steps involved in the development of a decision support model that integrates evidence-based data and patient values to select treatment alternatives.ConclusionsStudies focusing on the actual development of the decision support technology for this group of patients are needed, as decisions are highly multifactorial. Such tools have the potential to improve decision making for complex medical problems with alternate treatment pathways.