Biomedical subjects

K M Schoeffler

Publications and source records attributed to K M Schoeffler.

3 recordsLinked to original sources

PubMed2001

Standards for the electronic health record, emerging from health care's Tower of Babel.

This paper considers the standardization of an Electronic Health Record (EHR). Relations between several distinct medical datasets and information systems are mapped in order to derive a more precise definition of the EHR. Two international efforts to establish standards for the EHR are presented and critiqued. Strategies for standardizing the EHR are analyzed and recommendations are provided for approaching the standardization process.

Computer Communication Networks↗

PubMed1998

Barriers to evaluation of clinical vocabularies.

BACKGROUND: The importance of standard vocabularies for representing clinical data is widely accepted. The selection of suitable vocabularies for a given task relies upon criteria for systematically differentiating vocabularies. However, methods and measures for comparing vocabularies are only now emerging. Substantial barriers inhibit progress in the development of these measures. METHOD: As part of a larger project, the authors are developing quantitative measures for characteristics of controlled vocabulary as identified in the literature. RESULTS: Seven barriers have been identified that inhibit the development of quantitative measures of the characteristics of controlled vocabularies: 1) application dependence; 2) empirical v. independent assessment; 3) dichotomous v. continuous measures of characteristics; 4) poor definition of characteristics; 5) number of characteristics; 6) multiple levels of significance of characteristics; and 7) interdependence of characteristics. CONCLUSION: Progress toward quantitative assessment of clinical vocabularies is dependent upon overcoming barriers to the development of appropriate measures. Such progress requires innovative solutions and collaboration among investigators.

Evaluation Studies as Topic↗

PubMed1998

Extracting medical knowledge for a coded problem list vocabulary from the UMLS Knowledge Sources.

INTRODUCTION: The Unified Medical Language System (UMLS) Knowledge Sources embody a rich source of medical knowledge. We sought to extract a portion of this knowledge by incorporating information about relationships between UMLS concepts into an existing problem list vocabulary. METHODS: We matched terms from the coded problem list of The Medical Record (TMR), a computer-based patient record system, with those found in the UMLS Metathesaurus. Those UMLS concepts that participate in 'parent' relationships with the matched TMR concepts were translated back into TMR codes and the relationship information was retained for integration into the coded problem list of TMR. RESULTS: Of the coded problems currently in use in TMR, 67% (1627/2436) could be matched by normalized string matches to the UMLS Knowledge Sources. Of these matched TMR concepts, 91% (1488/1627) participated in at least one UMLS-identified parent relationship but only 28% of the matched concepts (454/1627) participated in parent relationships that already matched to a TMR code. As a result, although 67% of TMR codes were matched to UMLS concepts, only 19% of our original problem list (454/2436) could be augmented by relationship information contained in UMLS without improving the rate of matches or adding additional UMLS concepts as coded problems in TMR. CONCLUSION: This study illustrates the rapid decline in overall rates of matching that result from a multiplicative effect of successive matches of terms to concepts, concepts to relationships and concepts back to entry terms. This effect will hamper any effort to extract relationship knowledge from the UMLS for incorporation into an entry vocabulary that is not already one of the source vocabularies of the UMLS Metathesaurus.

Humans↗