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Data Warehouse Design from HL7 Clinical Document Architecture Schema.

Fabrizio Pecoraro1, Daniela Luzi1, Fabrizio L Ricci2

  • 1Institute for Research on Population and Social Policies, National Research Council, Italy.

Studies in Health Technology and Informatics
|July 9, 2015
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Summary
This summary is machine-generated.

This study presents a semi-automatic method to convert clinical documents (HL7 Clinical Document Architecture) into a data warehouse dimensional model. This approach facilitates structured data analysis, demonstrated with vital signs from lab tests.

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Area of Science:

  • Health Informatics
  • Data Management

Background:

  • Clinical information is often unstructured, hindering data analysis.
  • Health Level Seven (HL7) Clinical Document Architecture (CDA) is a standard for clinical document exchange.
  • Data warehouses require structured data for efficient querying and analysis.

Purpose of the Study:

  • To propose a semi-automatic method for extracting clinical information from HL7 CDA documents.
  • To transform extracted CDA data into a dimensional model schema for data warehousing.
  • To demonstrate the feasibility of this approach through a case study.

Main Methods:

  • Development of a conceptual framework mapping dimensional model primitives to CDA elements.
  • Implementation of a semi-automatic extraction and transformation process.
  • Case study involving vital signs data from laboratory tests.

Main Results:

  • Successful extraction and transformation of clinical information from HL7 CDA to a dimensional model.
  • Demonstrated feasibility using vital signs data.
  • The approach enables structured data warehousing of clinical information.

Conclusions:

  • The proposed semi-automatic method effectively converts HL7 CDA data into a dimensional model.
  • This facilitates the integration of clinical data into data warehouses for enhanced analysis.
  • The method is applicable to various clinical data types, as shown by the vital signs case study.