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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
The role of standardized data and terminological systems in computerized clinical decision support systems:
Leila Ahmadian1, Mariette van Engen-Verheul, Ferishta Bakhshi-Raiez
1Dept. of Medical Informatics, Academic Medical Center, University of Amsterdam, The Netherlands. l.ahmadian@amc.uva.nl
Introduction:
Clinical decision support systems (CDSSs) should be seamlessly integrated with existing clinical information systems to enable automatic provision of advice at the time and place where decisions are made. It has been suggested that a lack of agreed data standards frequently hampers this integration. We performed a literature review to investigate whether CDSSs used standardized (i.e. coded or numerical) data and which terminological systems have been used to code data. We also investigated whether a lack of standardized data was considered an impediment for CDSS implementation.
Methods:
Articles reporting an evaluation of a CDSS that provided a computerized advice based on patient-specific data items were identified based on a former literature review on CDSS and on CDSS studies identified in AMIA's 'Year in Review'. Authors of these articles were contacted to check and complete the extracted data. A questionnaire among the authors of included studies was used to determine the obstacles in CDSS implementation.
Results:
We identified 77 articles published between 1995 and 2008. Twenty-two percent of the evaluated CDSSs used only numerical data. Fifty one percent of the CDSSs that used coded data applied an international terminology. The most frequently used international terminology were the ICD (International Classification of Diseases), used in 68% of the cases and LOINC (Logical Observation Identifiers Names and Codes) in 12% of the cases. More than half of the authors experienced barriers in CDSS implementation. In most cases these barriers were related to the lack of electronically available standardized data required to invoke or activate the CDSS.
Conclusion:
Many CDSSs applied different terminological systems to code data. This diversity hampers the possibility of sharing and reasoning with data within different systems. The results of the survey confirm the hypothesis that data standardization is a critical success factor for CDSS development.
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