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Knowledge management and informatics considerations for comparative effectiveness research: a case-driven

Peter J Embi1, Courtney Hebert, Gayle Gordillo

  • 1Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA. peter.embi@osumc.edu

Medical Care
|June 25, 2013
PubMed
Summary
This summary is machine-generated.

Leveraging electronic clinical data for comparative effectiveness research (CER) presents knowledge management and informatics challenges. Addressing these requires understanding data and organizational factors for successful CER study conduct.

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

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Area of Science:

  • Biomedical Informatics
  • Health Services Research

Background:

  • Electronic clinical data offers significant potential for comparative effectiveness research (CER).
  • Challenges in data reuse and knowledge management hinder the effective utilization of these electronic health records.
  • Understanding these informatics and knowledge management issues is crucial for advancing CER.

Purpose of the Study:

  • To identify and enumerate common knowledge management and informatics challenges in reusing electronic clinical data for CER.
  • To analyze specific research projects to highlight prevalent themes and obstacles in conducting CER studies.
  • To present a formal framework for understanding these emergent challenges.

Main Methods:

  • Literature review of biomedical informatics challenges and best practices for CER.
  • Analysis of two institutional research projects focused on CER.
  • Identification and thematic representation of common challenges encountered.

Main Results:

  • Informatics challenges in CER encompass data information and knowledge management (e.g., data reuse, preparation).
  • Sociotechnical and organizational factors present significant people-related challenges in CER.
  • A formal framework is presented to describe these identified findings.

Conclusions:

  • Diverse and heterogeneous datasets pose significant challenges for CER.
  • Overcoming these challenges requires understanding them and applying informatics best practices.
  • Further research and policy development are needed to fully realize the potential of electronic clinical data for CER.