The evolution of eProtocols that enable reproducible clinical research and care methods.
Unnecessary variation in clinical care and clinical research reduces our ability to determine what healthcare interventions are effective. Reducing this unnecessary variation could lead to further healthcare quality improvement and more effective clinical research. We have developed and used electro...
| Published in: | Journal of Clinical Monitoring & Computing Vol. 26; no. 4; pp. 305 - 318 |
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| Main Authors: | , , , , , , , , , , , , , , , , , , , |
| Format: | research Journal Article |
| Published: |
Springer Nature
Aug2012
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104356404&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104356404 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13871307 OHC jtl: Journal of Clinical Monitoring & Computing issn: 13871307 maglogo: N pubinfo: dt: Aug2012 vid: 26 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104356404 NLM22491960 2011605922 10.1007/s10877-012-9356-y NLM22491960 104356404 ppf: 305 ppct: 13 formats: fmt: @attributes: type: P tig: atl: The evolution of eProtocols that enable reproducible clinical research and care methods. aug: au: Blagev DP Hirshberg EL Sward K Thompson BT Brower R Truwit J Hite D Steingrub J Orme JF Jr Clemmer TP Weaver LK Thomas F Grissom CK Sorenson D Sittig DF Wallace CJ East TD Warner HR Morris AH Blagev, Denitza P affil: Pulmonary, Division, Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA sug: subj: Decision Support Systems, Management Administration Drug Therapy, Computer Assisted Methods Hyperglycemia Diagnosis Hyperglycemia Drug Therapy Insulin Administration and Dosage Internet Programming Languages Adult Research, Medical Methods Human Sensitivity and Specificity United States Adult: 19-44 years ab: Unnecessary variation in clinical care and clinical research reduces our ability to determine what healthcare interventions are effective. Reducing this unnecessary variation could lead to further healthcare quality improvement and more effective clinical research. We have developed and used electronic decision support tools (eProtocols) to reduce unnecessary variation. Our eProtocols have progressed from a locally developed mainframe computer application in one clinical site (LDS Hospital) to web-based applications available in multiple languages and used internationally. We use eProtocol-insulin as an example to illustrate this evolution. We initially developed eProtocol-insulin as a local quality improvement effort to manage stress hyperglycemia in the adult intensive care unit (ICU). We extended eProtocol-insulin use to translate our quality improvement results into usual clinical care at Intermountain Healthcare ICUs. We exported eProtocol-insulin to support research in other US and international institutions, and extended our work to the pediatric ICU. We iteratively refined eProtocol-insulin throughout these transitions, and incorporated new knowledge about managing stress hyperglycemia in the ICU. Based on our experience in the development and clinical use of eProtocols, we outline remaining challenges to eProtocol development, widespread distribution and use, and suggest a process for eProtocol development. Technical and regulatory issues, as well as standardization of protocol development, validation and maintenance, need to be addressed. Resolution of these issues should facilitate general use of eProtocols to improve patient care. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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