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dc.contributor.advisorKahn, Michael G.
dc.contributor.advisorHaugen, Heather
dc.contributor.authorTrinkley, Katy E.
dc.contributor.committeememberMatlock, Daniel D.
dc.contributor.committeememberMalone, Daniel C.
dc.contributor.committeememberLin, Chen Tan
dc.date.accessioned2020-01-14T15:44:30Z
dc.date.available2022-01-06T15:44:31Z
dc.date.submitted2019
dc.descriptionIncludes bibliographical references.
dc.descriptionFall
dc.description.abstractClinical decision support (CDS) within electronic health records (EHR) is one approach to optimize healthcare outcomes, but the full potential is unrealized. Others have hypothesized that CDS design best practices can improve CDS outcomes of adoption and effectiveness, but there is limited empirical evidence nor direction on how to apply best practices. Understanding the influence of best practices on CDS outcomes is critical given resource limitations and need to improve healthcare. To study the impact of the best practices on CDS implementation success, we created a process model that integrates an evidence-based implementation science framework and applied the model to design and implement a “customized” CDS. The customized CDS was compared to an active control in a cluster randomized trial across 28 primary care clinics. The control was a “commercial” vendor-supplied CDS and did not comprehensively apply the best practices. Both CDS aimed to improve prescribing for heart failure. Outcomes included clinician adoption and effectiveness of changing prescribing. Primary care clinicians exposed to each CDS were interviewed to identify salient design features that influence adoption. From March 15, 2019 through August 23, 2019, the customized and commercial CDS respectively alerted for 61 and 26 unique patients (106 versus 59 total alerts), was adopted for 62% and 29% of alerts (p<0.0001), and improved prescribing for 14% and 0% of alerts (p=0.006). Of the 21 clinicians interviewed, 71% preferred the customized, one had no preference and the remaining 24% preferred the commercial due to brevity or a dismiss option. Clinician interviews surfaced four salient design features that positively influence adoption: 1) make it easy to do the right thing, 2) right time and relevance, 3) pertinent information, and 4) be respectful. This mixed methods study suggests CDS design best practices lead to improved CDS adoption and effectiveness and that commercially available CDS that do not adhere to the best practices may be suboptimal. We created, tested and refined the first integrated model for CDS implementation that can be adapted by other institutions to maximize CDS efficiency and effectiveness.
dc.identifierTrinkley_ucdenveramc_1639D_10690.pdf
dc.identifier.urihttps://hdl.handle.net/10968/4773
dc.languageEnglish
dc.publisherUniversity of Colorado at Denver, Anschutz Medical Campus. Health Sciences Library
dc.rightsCopyright of the original work is retained by the author.
dc.rights.accessEmbargo Expires: 01/06/2022
dc.subject.meshElectronic Health Records
dc.subject.meshHealth Plan Implementation
dc.titleInvestigation of approaches to implementing effective clinical decision support within electronic health records
dc.typeThesis
dcterms.embargo.expires2022-01-06
thesis.degree.disciplineClinical Sciences
thesis.degree.grantorUniversity of Colorado at Denver, Anschutz Medical Campus
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)


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