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Related Experiment Videos

Transforms of the computerized patient record data model: from transactions to analytical processing

K Canfield1, M Silva, S Zhaohui

  • 1Department of Information Systems, University of Maryland, UMBC, USA.

Proceedings. Symposium on Computer Applications in Medical Care
|January 1, 1995
PubMed
Summary
This summary is machine-generated.

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Computerized Patient Record databases require different designs for transaction processing (daily use) versus analytical processing (research). A methodology transforms transaction databases into analytical ones, proving effective for usability and maintenance.

Area of Science:

  • Health Informatics
  • Database Management
  • Clinical Research Informatics

Background:

  • Computerized Patient Record (CPR) databases serve dual roles: operational transaction processing and cross-patient analytical processing.
  • Distinct design considerations are necessary to optimize CPR databases for either transactional or analytical workloads.
  • Current database designs may not adequately support both operational efficiency and research/management querying.

Purpose of the Study:

  • To define the differing design requirements for CPR databases based on transaction processing versus analytical processing.
  • To present a case study demonstrating a methodology for transforming transaction-oriented CPR databases into analytical ones.
  • To evaluate the usability and maintainability of the resulting analytical database design.

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Main Methods:

  • Defining distinct design principles for transaction processing (single-patient updates) and analytical processing (cross-patient querying).
  • Developing and applying a transformation methodology to convert existing transaction CPR databases into analytical databases.
  • Evaluating the transformed analytical database design using specific criteria for usability and maintainability.

Main Results:

  • The study successfully defined the divergent design needs for transaction and analytical processing in CPR databases.
  • A case study demonstrated a replicable methodology for transforming transaction databases to analytical ones.
  • The resulting analytical database design met predefined criteria for usability and maintainability.

Conclusions:

  • CPR database design must be tailored to either transaction or analytical processing needs for optimal performance.
  • A practical methodology exists to transform existing transaction CPR databases into effective analytical databases.
  • This transformation approach is versatile and applicable across various relational database environments.