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Strategies for problem list implementation in a complex clinical enterprise

J R Campbell1

  • 1University of Nebraska Medical Center, Omaha, USA.

Proceedings. AMIA Symposium
|February 3, 1999
PubMed
Summary
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A well-designed patient problem list in electronic health records is crucial for clinical care. This study outlines key features for effective problem list implementation and reports successful outcomes in a large healthcare system.

Area of Science:

  • Health Informatics
  • Clinical Informatics
  • Electronic Health Records

Background:

  • The Institute of Medicine emphasizes the importance of patient problem lists in electronic health records.
  • Current problem list designs lack universal agreement, leading to inconsistent implementation.
  • Challenges include data standards, user acceptance, and clinician incentives.

Purpose of the Study:

  • To define essential features for an effective patient problem list.
  • To describe implementation strategies for a computerized patient record system.
  • To evaluate the success of the implemented problem list.

Main Methods:

  • Defined key features: clinical focus, codification, problem resolution support, historicity, multiple views, workflow integration, administrative reporting, and clinical tool integration.

Related Experiment Videos

  • Developed and implemented a problem list within a large-scale computerized patient record system.
  • Conducted audits six months post-implementation to assess goal achievement.
  • Main Results:

    • The implemented problem list successfully incorporated all proposed essential features.
    • Audits confirmed the achievement of defined goals for the problem list.
    • The system served a large and complex clinical enterprise.

    Conclusions:

    • A structured approach to patient problem list design and implementation is feasible and effective.
    • Successful integration enhances clinical workflow and administrative reporting.
    • The study demonstrates a model for optimizing problem list functionality in electronic health records.