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Related Experiment Videos

Studying the human-computer-terminology interface.

J J Cimino1, V L Patel, A W Kushniruk

  • 1Department of Medical Informatics, Columbia-Presbyterian Medical Center, 622 West 168th Street, VC-5, New York, NY 10032, USA. jjc7@columbia.edu

Journal of the American Medical Informatics Association : JAMIA
|March 7, 2001
PubMed
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This study assessed clinician data entry using a cognitive approach, finding most entries successful. The method effectively identified issues related to terminology and user interface problems in electronic health records.

Area of Science:

  • Medical Informatics
  • Human-Computer Interaction
  • Clinical Data Management

Background:

  • Accurate clinical data entry is crucial for patient care and research.
  • Understanding the causes of data entry errors is essential for improving electronic health record (EHR) systems.
  • Existing methods may not fully capture the nuances of clinician data entry in real-world settings.

Purpose of the Study:

  • To evaluate an observational, cognitive-based approach for assessing clinical data entry success.
  • To differentiate between successful, suboptimal, and failed data entries.
  • To identify the root causes of unsuccessful data capture, including terminology content, representation, and user interface issues.

Main Methods:

  • An observational study was conducted in an outpatient clinic.

Related Experiment Videos

  • Videotaping and subsequent coding of data entry events were employed.
  • Clinicians (physicians and nurse practitioners) used the Medical Entities Dictionary (MED) for data input.

    • Main Results:

    • Analysis of 238 data entry events showed a 71.0% success rate, 6.3% suboptimal, and 22.7% failed.
    • Unsuccessful entries were attributed to content (13.0%), representation (10.1%), and usability (5.9%) problems.
    • Tasks involving drug dose and frequency terms had an 82% overall success rate.

    Conclusions:

    • Clinical data entry using the outpatient system and MED was generally successful and efficient.
    • The cognitive-based observational approach effectively identified suboptimal and failed data entries.
    • The study highlights the utility of this approach for detecting user interface and terminology-related data entry issues.