title: The evolution of eProtocols that enable reproducible clinical research and care methods.
abstract: 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.
authors.affiliation: Pulmonary, Division, Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA. denitza.blagev@imail.org
authors.forename: Denitza P
authors.initials: DP
authors.lastname: Blagev
authors.forename: Eliotte L
authors.initials: EL
authors.lastname: Hirshberg
authors.forename: Katherine
authors.initials: K
authors.lastname: Sward
authors.forename: B Taylor
authors.initials: BT
authors.lastname: Thompson
authors.forename: Roy
authors.initials: R
authors.lastname: Brower
authors.forename: Jonathon
authors.initials: J
authors.lastname: Truwit
authors.forename: Duncan
authors.initials: D
authors.lastname: Hite
authors.forename: Jay
authors.initials: J
authors.lastname: Steingrub
authors.forename: James F
authors.initials: JF
authors.lastname: Orme
authors.forename: Terry P
authors.initials: TP
authors.lastname: Clemmer
authors.forename: Lindell K
authors.initials: LK
authors.lastname: Weaver
authors.forename: Frank
authors.initials: F
authors.lastname: Thomas
authors.forename: Colin K
authors.initials: CK
authors.lastname: Grissom
authors.forename: Dean
authors.initials: D
authors.lastname: Sorenson
authors.forename: Dean F
authors.initials: DF
authors.lastname: Sittig
authors.forename: C Jane
authors.initials: CJ
authors.lastname: Wallace
authors.forename: Thomas D
authors.initials: TD
authors.lastname: East
authors.forename: Homer R
authors.initials: HR
authors.lastname: Warner
authors.forename: Alan H
authors.initials: AH
authors.lastname: Morris
mesh_terms: D000328:Adult; D035843:Biomedical Research / Q000379:methods; D003660:Decision Support Systems, Management / Q000458:organization & administration*; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D006801:Humans; D006943:Hyperglycemia / Q000175:diagnosis* / Q000188:drug therapy*; D007328:Insulin / Q000008:administration & dosage*; D020407:Internet; D011381:Programming Languages; D012680:Sensitivity and Specificity; D014481:United States
chemical_list: D007328:Insulin