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dc.contributor.advisorJayakanth Srinivasan.en_US
dc.contributor.authorFingerhut, Henry Alan.en_US
dc.contributor.otherMassachusetts Institute of Technology. Institute for Data, Systems, and Society.en_US
dc.date.accessioned2020-11-24T17:32:34Z
dc.date.available2020-11-24T17:32:34Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/128641
dc.descriptionThesis: Ph. D. in Engineering Systems: Technology, Management, and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, February, 2020en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 135-145).en_US
dc.description.abstractIn the three decades since its introduction, Evidence-Based Practice (EBP) has become standard clinical practice and the subject of targeted interventions at all levels of the health system. Despite its prevalence, EBP is frequently challenged on philosophical, practical, empirical, and normative grounds. And EBP is often underused in practice relative to the considerable investment in training and sophisticated organizational interventions to implement EBP. In this dissertation, I identify what the concept of EBP means to health system stakeholders as a partial explanation for this persistent gap in EBP use and implementation outcomes. Through interviews with clinicians and healthcare administrators, I identify how providers and organizations use EBP in practice to clinical ends and in inter-professional relationships. First, I find that in contrast to the theoretical model, stakeholders vary in how they operationalize EBP for individual-level clinical use.en_US
dc.description.abstractStakeholders endorse a range of what I call implicit mental models of EBP that imply different approaches to clinical decision-making. Respondents' implicit mental models of EBP each emphasize an incomplete aspect of the full EBP model: Resource-Based EBP emphasizes specific evidence artifacts, Decision-Making EBP emphasizes the decision-making process, and EBT-Based EBP emphasizes specific Evidence-Based Treatments. These implicit models represent the decision inputs, process, and outputs, respectively. Second, I describe how and why healthcare organizations conduct EBP interventions, despite its initial design as an individual-level clinical decision-making model. I document a range of different organizational EBP activities and interventions, including disseminating resources, training providers, and implementing local standards. These organizational EBP activities both support individual EBP use and address broader organizational ends, which may conflict.en_US
dc.description.abstractFinally, EBP takes on social and inter-professional meanings beyond its intended scope as a clinical decision-making model, which emerge in context and affect how providers understand and use EBP. Specifically, providers may renounce their standing to evaluate evidence, demonstratively use EBP, and administrators claim standing to evaluate evidence. This dissertation therefore demonstrates the varied uses of EBP that emerge in practice, contributing to our understanding of the challenges and contradictions that arise in applying general knowledge to individual cases and systematizing strategies for the same at the organization level.en_US
dc.description.statementofresponsibilityby Henry Alan Fingerhut.en_US
dc.format.extent149 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectInstitute for Data, Systems, and Society.en_US
dc.titleIndividual and organizational Uses of Evidence-Based Practice in healthcare settingsen_US
dc.title.alternativeIndividual and organizational Uses of EBP in healthcare settingsen_US
dc.typeThesisen_US
dc.description.degreePh. D. in Engineering Systems: Technology, Management, and Policyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Institute for Data, Systems, and Societyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Division
dc.identifier.oclc1223518121en_US
dc.description.collectionPh.D.inEngineeringSystems:Technology,Management,andPolicy Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Societyen_US
dspace.imported2020-11-24T17:32:33Zen_US
mit.thesis.degreeDoctoralen_US
mit.thesis.departmentESDen_US
mit.thesis.departmentIDSSen_US


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