Restructuring Routinely Collected Patient Data: ORCA Applied to Andrology

F. H. Pierik; A. M. van Ginneken; T. Timmers’; H. Stam; R. F. A. Weber

doi:10.1055/s-0038-1636842

Methods of Information in Medicine, Table of Contents

Methods Inf Med 1997; 36(03): 184-190
DOI: 10.1055/s-0038-1636842

Original Article

Schattauer GmbH

Restructuring Routinely Collected Patient Data: ORCA Applied to Andrology

F. H. Pierik

¹ Departments of Medical Informatics and

² Departments of Endocrinology and Reproduction, Faculty of Medicine and Health Sciences, Erasmus University Rotterdam

³ Departments of Department of Andrology, University Hospital Dijkzigt, Rotterdam, The Netherlands

,

A. M. van Ginneken

¹ Departments of Medical Informatics and

,

T. Timmers’⁴

¹ Departments of Medical Informatics and

,

H. Stam

¹ Departments of Medical Informatics and

,

R. F. A. Weber

² Departments of Endocrinology and Reproduction, Faculty of Medicine and Health Sciences, Erasmus University Rotterdam

³ Departments of Department of Andrology, University Hospital Dijkzigt, Rotterdam, The Netherlands

› Author Affiliations

Abstract

Hospital information systems do not always cover all required detail per specialty. This may lead to scattering of data over disparate systems and the paper record. The ORCA (Open Record for CAre) CPR offers a generic structure for record sharing, and record keeping tailored to specific needs. We studied whether a semantic integration of existing and new data was possible, using the ORCA structure. Existing andrology data, originating from separate sources, were utilized for this purpose. During normalization, validation and explication steps, latent problems in the source data were exposed and removed, followed by a merge with new data items. By conversion of source data to ORCA, a unique representation of medical concepts in the database was attained, facilitating retrieval of univocal data for multiple purposes. We conclude that the expansion to the andrology domain, including transparent integration of existing data, provides support for the generality of ORCA.

Keywords

Data Modeling - Computerized Medical Record Systems - Data Collection - Ambulatory Care Systems

Full Text

References

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