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JAMIA 2002;9:586-599 doi:10.1197/jamia.M1033
  • Original Investigation
  • Model Formation

Extending the LOINC Conceptual Schema to Support Standardized Assessment Instruments

  1. Thomas M White,
  2. Michael J Hauan
  1. Affiliations of the authors: New York State Office of Mental Health, New York, New York (TMW); University of Missouri School of Medicine, Columbia, Missouri (MJH)
  1. Correspondence and reprints: Thomas M. White, MD, MS, MA, Assistant Director, Bureau of Evidence Based Medicine and Practice Guidelines, New York State Office of Mental Health, 330 Fifth Ave, 9th Floor, New York, NY 10001; e-mail: <tw176{at}columbia.edu>
  • Received 13 October 2001
  • Accepted 24 June 2002

Abstract

Objective To extend the Clinical LOINC (Logical Observation Identifiers, Names, and Codes) semantic schema to support (1) the representation of common types of assessment instruments and (2) the disambiguation of versions and variants that may have differing reliability and validity.

Design Psychometric theory and survey research framework, plus an existing tool for implementing many types of assessment instruments (Dialogix), were used to identify and model the attributes of instruments that affect reliability and validity. Four modifications to the LOINC semantic schema were proposed as a means for completely identifying, disambiguating, and operationalizing a broad range of assessment instruments.

Measurements Assess the feasibility of modeling these attributes within LOINC, with and without the proposed extensions.

Results The existing LOINC schema for supporting assessment instruments was unable to consistently meet either objective. In contrast, the proposed extensions were able to meet both objectives, because they are derived from the Dialogix schema, which already performs those tasks.

Conclusion These extensions to LOINC can facilitate the use, analysis, and improvement of assessment instruments and thereby may improve the detection and management of errors.

Footnotes

  • This work was supported in part by the Research Foundation for Mental Hygiene via a Fellowship in Psychiatric Informatics at the New York State Psychiatric Institute; NIMH Grant MH54601; and the New York State Office of Mental Health.

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