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Related Experiment Videos

Expressiveness and query complexity in an electronic health record data model

R H Dolin1

  • 1Kaiser Permanente, Southern California Region, USA. Robert.Dolin@kp.org

Proceedings : a Conference of the American Medical Informatics Association. AMIA Fall Symposium
|January 1, 1996
PubMed
Summary

This study presents a conceptual electronic health record (EHR) data model and a query algorithm. The model is highly expressive, and the algorithm has polynomial time and space complexity.

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Area of Science:

  • Computer Science
  • Health Informatics

Background:

  • Electronic Health Records (EHRs) are crucial for modern healthcare.
  • Developing effective EHR data models is essential for data management and analysis.
  • Existing models may lack the expressiveness needed for complex queries.

Purpose of the Study:

  • To describe a conceptual EHR data model.
  • To evaluate the expressiveness of the proposed model.
  • To present and analyze a query algorithm for the EHR data model.

Main Methods:

  • Utilized Entity-Relationship diagramming to conceptualize the EHR data model.
  • Employed variably nested relations to enhance model expressiveness.
  • Developed a recursive query processing algorithm and analyzed its complexity using Big-O notation.

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Main Results:

  • The proposed EHR data model demonstrates high expressiveness.
  • A tractable recursive query processing algorithm was developed.
  • The algorithm exhibits polynomial time and space complexity.

Conclusions:

  • The study successfully demonstrates formal analysis of EHR model expressiveness and query complexity.
  • Challenges remain in populating the model for live testing.
  • The findings provide a foundation for developing more advanced EHR data management techniques.