title: Translation of Contextual Control Model to chronic disease management: A paradigm to guide design of cognitive support systems.
abstract: Electronic health records (EHRs) continue to be criticized for providing poor cognitive support. Defining cognitive support has lacked theoretical foundation. We developed a measurement model of cognitive support based on the Contextual Control Model (COCOM), which describes control characteristics of an "orderly" joint system and proposes 4 levels of control: scrambled, opportunistic, tactical, and strategic.
  
  
  
  35 clinicians (5 centers) were interviewed pre and post outpatient clinical visits and audiotaped during the visit. Behaviors pertaining to hypertension management were systematically mapped to the COCOM control characteristics of: (1) time horizon, (2) uncertainty assessment, (3) consideration of multiple goals, (4) causal model described, and (5) explicitness of plan. Each encounter was classified for overall mode of control. Visits with deviation versus no deviation from hypertension goals were compared.
  
  
  
  Reviewer agreement was high. Control characteristics differed significantly between deviation groups (Wilcox rank sum p<.01). K-means cluster analysis of control characteristics, stratified by deviation were distinct, with higher goal deviations associated with more control characteristics.
  
  
  
  The COCOM control characteristics appear to be areas of potential yield for improved user-experience design.
authors.affiliation: Department of Veterans Affairs, Salt Lake City, UT, United States; Department of Internal Medicine, University of Utah, Salt Lake City, UT, United States. Electronic address: Molly.Leecaster@va.gov.
authors.forename: Molly K
authors.initials: MK
authors.lastname: Leecaster
authors.affiliation: Department of Veterans Affairs, Salt Lake City, UT, United States; Department of Bio-Medical Informatics, University of Utah, Salt Lake City, UT, United States.
authors.forename: Charlene R
authors.initials: CR
authors.lastname: Weir
authors.affiliation: Department of Veterans Affairs, Salt Lake City, UT, United States; Department of Psychology, University of Utah, Salt Lake City, UT, United States.
authors.forename: Frank A
authors.initials: FA
authors.lastname: Drews
authors.affiliation: Department of Veterans Affairs, Salt Lake City, UT, United States; Department of Bio-Medical Informatics, University of Utah, Salt Lake City, UT, United States.
authors.forename: James L
authors.initials: JL
authors.lastname: Hellewell
authors.affiliation: Department of Veterans Affairs, Salt Lake City, UT, United States; Department of Internal Medicine, University of Utah, Salt Lake City, UT, United States.
authors.forename: Daniel
authors.initials: D
authors.lastname: Bolton
authors.affiliation: Department of Veterans Affairs, Salt Lake City, UT, United States; Department of Internal Medicine, University of Utah, Salt Lake City, UT, United States.
authors.forename: Makoto M
authors.initials: MM
authors.lastname: Jones
authors.affiliation: Department of Veterans Affairs, Salt Lake City, UT, United States; Department of Internal Medicine, University of Utah, Salt Lake City, UT, United States.
authors.forename: Jonathan R
authors.initials: JR
authors.lastname: Nebeker
mesh_terms: D002908:Chronic Disease; D016000:Cluster Analysis; D003071:Cognition; D020000:Decision Support Systems, Clinical; D019468:Disease Management; D057286:Electronic Health Records; D006801:Humans; D006973:Hypertension / Q000628:therapy
keywords: Clinical decision-making; Cognitive support; Health IT; Modes of control