A diabetes dashboard and physician efficiency and accuracy in accessing data needed for high-quality diabetes care

Ann Fam Med. 2011 Sep-Oct;9(5):398-405. doi: 10.1370/afm.1286.

Abstract

Purpose: 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.

Publication types

  • Evaluation Study
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Attitude of Health Personnel
  • Data Display*
  • Diabetes Mellitus / therapy*
  • Efficiency
  • Electronic Health Records*
  • Female
  • Health Status Indicators
  • Humans
  • Information Seeking Behavior
  • Male
  • Middle Aged
  • Physicians, Primary Care / psychology*
  • Time Factors
  • Time and Motion Studies
  • User-Computer Interface*