Browse by author
Lookup NU author(s): Professor Sarah SlightORCiD
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
© Schattauer 2016. Background: Adverse sensitivity (e.g., allergy and intolerance) information is a critical component of any electronic health record system. While several standards exist for structured entry of adverse sensitivity information, many clinicians record this data as free text. Objectives: This study aimed to 1) identify and compare the existing common adverse sensitivity information models, and 2) to evaluate the coverage of the adverse sensitivity information models for representing allergy information on a subset of inpatient and outpatient adverse sensitivity clinical notes. Methods: We compared four common adverse sensitivity information models: Health Level 7 Allergy and Intolerance Domain Analysis Model, HL7-DAM; the Fast Healthcare Interoperability Resources, FHIR; the Consolidated Continuity of Care Document, C-CDA; and OpenEHR, and evaluated their coverage on a corpus of inpatient and outpatient notes (n = 120). Results: We found that allergy specialists’ notes had the highest frequency of adverse sensitivity attributes per note, whereas emergency department notes had the fewest attributes. Overall, the models had many similarities in the central attributes which covered between 75% and 95% of adverse sensitivity information contained within the notes. However, representations of some attributes (especially the value-sets) were not well aligned between the models, which is likely to present an obstacle for achieving data interoperability. Also, adverse sensitivity exceptions were not well represented among the information models. Conclusions: Although we found that common adverse sensitivity models cover a significant portion of relevant information in the clinical notes, our results highlight areas needed to be reconciled between the standards for data interoperability.
Author(s): Topaz M, Seger DL, Goss F, Lai K, Slight SP, Lau JJ, Nandigam H, Zhou L
Publication type: Article
Publication status: Published
Journal: Methods of Information in Medicine
Online publication date: 24/02/2016
Acceptance date: 30/01/2016
ISSN (print): 0026-1270
Publisher: Schattauer GmbH
PubMed id: 26905461
Altmetrics provided by Altmetric