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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http://dx.doi.org/10.1016/j.annfar.2013.06.015DOI Listing

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