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Related Experiment Videos

Capturing and using clinical outcome data: implications for information systems design

R D Zielstorff1

  • 1Department of Nursing, Massachusetts General Hospital, Boston 02114, USA.

Journal of the American Medical Informatics Association : JAMIA
|May 1, 1995
PubMed
Summary
This summary is machine-generated.

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Capturing clinical outcome data is vital but challenging due to measurement and system issues. This article outlines essential information system requirements for accurate and effective clinical outcome data management.

Area of Science:

  • Health Informatics
  • Clinical Data Management
  • Patient Outcomes Research

Background:

  • Urgent need exists for capturing and recording clinical outcome data.
  • Barriers include conceptual disagreements, inadequate outcome measures, and insufficient information systems.
  • Existing systems struggle to capture and manipulate outcome data effectively.

Purpose of the Study:

  • To define information system requirements for capturing, storing, and utilizing clinical outcome data.
  • To address challenges in conceptualizing and measuring outcomes.
  • To guide the development of robust data management systems for patient outcomes.

Main Methods:

  • Focus on information system requirements for clinical outcome data.
  • Advocates for direct data capture from patients and families for accuracy.

Related Experiment Videos

  • Proposes system design principles for effective data utilization.

    • Main Results:

    • Outcome data capture should be source-proximal for maximal accuracy.
    • Information systems must support multipurpose databases and cross-platform data sharing.
    • Systems need to link outcome data with influencing factors and ensure authorized access and confidentiality.

    Conclusions:

    • Effective clinical outcome data management requires specific information system capabilities.
    • Direct patient and family data capture enhances accuracy.
    • Well-designed systems are crucial for leveraging outcome data to improve healthcare.
    • Protecting patient confidentiality is paramount in all data handling processes.