Evidence-Based Medicine, Best Practices, Transductive Models, and Naturalistic Decision Making: Commentary on Paul R. Falzer, Naturalistic Decision Making and the Practice of Health Care
{"title":"Evidence-Based Medicine, Best Practices, Transductive Models, and Naturalistic Decision Making: Commentary on Paul R. Falzer, Naturalistic Decision Making and the Practice of Health Care","authors":"R. Haynes","doi":"10.1177/1555343418789831","DOIUrl":null,"url":null,"abstract":"Expert and informed decision making is an essential process in all of health care. Evidence-Based Medicine (EBM) purports to support and enhance this process by the timely infusion of high-quality, pertinent evidence from health research, tailored as closely as possible to the individual and their health problem. Doing so is not an easy task for many reasons, beginning with imperfections and incompleteness in the evidence and ending with the complexities of the dual decision making required by individuals and their care providers. EBM needs a lot of help supporting decision-making processes and welcomes further interdisciplinary collaboration. The “conformist principle,” “best practice regimens,” and “transductive models” should not be considered as barriers to such collaboration: These are not part of EBM. Rather, EBM has always seen evidence from health research as but one of many inputs to decision making by providers and patients. An overarching problem for collaboration to address is understanding the decision-making process well enough to develop effective means to bolster it, so that people are consistently offered the current best options for their problems in a way that fits their circumstances and that they can understand and judge.","PeriodicalId":46342,"journal":{"name":"Journal of Cognitive Engineering and Decision Making","volume":"12 1","pages":"194 - 197"},"PeriodicalIF":2.2000,"publicationDate":"2018-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1555343418789831","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cognitive Engineering and Decision Making","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1555343418789831","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 2
Abstract
Expert and informed decision making is an essential process in all of health care. Evidence-Based Medicine (EBM) purports to support and enhance this process by the timely infusion of high-quality, pertinent evidence from health research, tailored as closely as possible to the individual and their health problem. Doing so is not an easy task for many reasons, beginning with imperfections and incompleteness in the evidence and ending with the complexities of the dual decision making required by individuals and their care providers. EBM needs a lot of help supporting decision-making processes and welcomes further interdisciplinary collaboration. The “conformist principle,” “best practice regimens,” and “transductive models” should not be considered as barriers to such collaboration: These are not part of EBM. Rather, EBM has always seen evidence from health research as but one of many inputs to decision making by providers and patients. An overarching problem for collaboration to address is understanding the decision-making process well enough to develop effective means to bolster it, so that people are consistently offered the current best options for their problems in a way that fits their circumstances and that they can understand and judge.