IAIMS and UMLS at Columbia-Presbyterian Medical Center

1991 ◽  
Vol 11 (4_suppl) ◽  
pp. S89-S93 ◽  
Author(s):  
James J. Cimino ◽  
Soumitra Sengupta

The authors use an example to illustrate combining Integrated Academic Information Management System (IAIMS) components (applications) into an integral whole, to facilitate using the components simultaneously or in sequence. They examine a model for classifying IAIMS systems, proposing ways in which the Unified Medical Language System (UMLS) can be exploited in them.

1995 ◽  
Vol 34 (01/02) ◽  
pp. 158-64 ◽  
Author(s):  
J. J. Cimino

Abstract:The Unified Medical Language System (UMLS) project at the United States National Library of Medicine contains and organizes a large number of terms from controlled medical vocabularies. This study examines the suitability of the UMLS for representing patient care information as it exists in the Columbia-Presbyterian Medical Center (CPMC) clinical information system. Comparisons were made between the semantic types, semantic relations and medical concepts of the UMLS and the data model entities, semantic classes, semantic relations and concepts in the CPMC system. Results of the comparison demonstrate that the UMLS structural model is appropriate for representing CPMC vocabularies and patient data and that the UMLS concepts provide excellent coverage of CPMC concepts in many areas. Recommendations are made for enhancing UMLS structure to provide additional coverage of the CPMC model. It is concluded that content expansion to provide better coverage of clinical terminology is possible within the current UMLS model.


2008 ◽  
Vol 109 (5) ◽  
pp. 811-815 ◽  
Author(s):  
David B. Wax ◽  
Yaakov Beilin ◽  
Sabera Hossain ◽  
Hung-Mo Lin ◽  
David L. Reich

Background Anesthesia information management systems allow automatic recording of physiologic and anesthetic data. The authors investigated the prevalence of such data modification in an academic medical center. Methods The authors queried their anesthesia information management system database of anesthetics performed in 2006 and tabulated the counts of data points for automatically recorded physiologic and anesthetic parameters as well as the subset of those data that were manually invalidated by clinicians (both with and without alternate values manually appended). Patient, practitioner, data source, and timing characteristics of recorded values were also extracted to determine their associations with editing of various parameters in the anesthesia information management system record. Results A total of 29,491 cases were analyzed, 19% of which had one or more data points manually invalidated. Among 58 attending anesthesiologists, each invalidated data in a median of 7% of their cases when working as a sole practitioner. A minority of invalidated values were manually appended with alternate values. Pulse rate, blood pressure, and pulse oximetry were the most commonly invalidated parameters. Data invalidation usually resulted in a decrease in parameter variance. Factors independently associated with invalidation included extreme physiologic values, American Society of Anesthesiologists physical status classification, emergency status, timing (phase of the procedure/anesthetic), presence of an intraarterial catheter, resident or certified registered nurse anesthetist involvement, and procedure duration. Conclusions Editing of physiologic data automatically recorded in an anesthesia information management system is a common practice and results in decreased variability of intraoperative data. Further investigation may clarify the reasons for and consequences of this behavior.


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