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Updated: May 7, 2026

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
A new process-centered description tool to initiate meta-reporting methodology in healthcare - 7CARECAT™. Feasibility
P Cottet1, A d'Hollander, A Cahana
1Department of Community, Primary Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland.
Background:
In the healthcare domain, different analytic tools focused on accidents appeared to be poorly adapted to sub-accidental issues. Improving local management and intra-institutional communication with simpler methods, allowing rapid and uncomplicated meta-reporting, could be an attractive alternative.
Methods:
A process-centered structure derived from the industrial domain - DEPOSE(E) - was selected and modified for its use in the healthcare domain. The seven exclusive meta-categories defined - Patient, Equipment, Process, Actor, Supplies, work Room and Organization- constitute 7CARECAT™. A collection of 536 "improvement" reports from a tertiary hospital Post anesthesia care unit (PACU) was used and four meta-categorization rules edited prior to the analysis. Both the relevance of the metacategories and of the rules were tested to build a meta-reporting methodology. The distribution of these categories was analyzed with a χ 2 test.
Results:
Five hundred and ninety independent facts were collected out of the 536 reports. The frequencies of the categories are: Organization 44%, Actor 37%, Patient 11%, Process 3%, work Room 3%, Equipment 1% and Supplies 1%, with a p-value <0.005 (χ 2). During the analysis, three more rules were edited. The reproducibility, tested randomly on 200 reports, showed a <2% error rate.
Conclusion:
This meta-reporting methodology, developed with the 7CARECAT™ structure and using a reduced number of operational rules, has successfully produced a stable and consistent classification of sub-accidental events voluntarily reported. This model represents a relevant tool to exchange meta-informations important for local and transversal communication in healthcare institutions. It could be used as a promising tool to improve quality and risk management.
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