title: A diabetes dashboard and physician efficiency and accuracy in accessing data needed for high-quality diabetes care.
abstract: OBJECTIVE
  We compared use of a new diabetes dashboard screen with use of a conventional approach of viewing multiple electronic health record (EHR) screens to find data needed for ambulatory diabetes care.
  
  
  METHODS
  We performed a usability study, including a quantitative time study and qualitative analysis of information-seeking behaviors. While being recorded with Morae Recorder software and "think-aloud" interview methods, 10 primary care physicians first searched their EHR for 10 diabetes data elements using a conventional approach for a simulated patient, and then using a new diabetes dashboard for another. We measured time, number of mouse clicks, and accuracy. Two coders analyzed think-aloud and interview data using grounded theory methodology.
  
  
  RESULTS
  The mean time needed to find all data elements was 5.5 minutes using the conventional approach vs 1.3 minutes using the diabetes dashboard (P <.001). Physicians correctly identified 94% of the data requested using the conventional method, vs 100% with the dashboard (P <.01). The mean number of mouse clicks was 60 for conventional searching vs 3 clicks with the diabetes dashboard (P <.001). A common theme was that in everyday practice, if physicians had to spend too much time searching for data, they would either continue without it or order a test again.
  
  
  CONCLUSIONS
  Using a patient-specific diabetes dashboard improves both the efficiency and accuracy of acquiring data needed for high-quality diabetes care. Usability analysis tools can provide important insights into the value of optimizing physician use of health information technologies.
authors.affiliation: Curtis W. and Ann H. Long Department of Family and Community Medicine, University of Missouri, School of Medicine, Columbia, Missouri 65212, USA. koopmanr@health.missouri.edu
authors.forename: Richelle J
authors.initials: RJ
authors.lastname: Koopman
authors.forename: Karl M
authors.initials: KM
authors.lastname: Kochendorfer
authors.forename: Joi L
authors.initials: JL
authors.lastname: Moore
authors.forename: David R
authors.initials: DR
authors.lastname: Mehr
authors.forename: Douglas S
authors.initials: DS
authors.lastname: Wakefield
authors.forename: Borchuluun
authors.initials: B
authors.lastname: Yadamsuren
authors.forename: Jared S
authors.initials: JS
authors.lastname: Coberly
authors.forename: Robin L
authors.initials: RL
authors.lastname: Kruse
authors.forename: Bonnie J
authors.initials: BJ
authors.lastname: Wakefield
authors.forename: Jeffery L
authors.initials: JL
authors.lastname: Belden
mesh_terms: D000328:Adult; D001291:Attitude of Health Personnel; D003626:Data Display; D003920:Diabetes Mellitus / Q000628:therapy*; D004526:Efficiency; D057286:Electronic Health Records; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D057226:Information Seeking Behavior; D008297:Male; D008875:Middle Aged; D058007:Physicians, Primary Care / Q000523:psychology*; D013997:Time Factors; D013996:Time and Motion Studies; D014584:User-Computer Interface