An analysis of computer-related patient safety incidents to inform the development of a classification

Farah Magrabi*, Mei Sing Ong, William Runciman, Enrico Coiera

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

122 Citations (Scopus)


Objective: To analyze patient safety incidents associated with computer use to develop the basis for a classification of problems reported by health professionals. Design: Incidents submitted to a voluntary incident reporting database across one Australian state were retrieved and a subset (25%) was analyzed to identify 'natural categories' for classification. Two coders independently classified the remaining incidents into one or more categories. Free text descriptions were analyzed to identify contributing factors. Where available medical specialty, time of day and consequences were examined. Measurements: Descriptive statistics; inter-rater reliability. Results: A search of 42 616 incidents from 2003 to 2005 yielded 123 computer related incidents. After removing duplicate and unrelated incidents, 99 incidents describing 117 problems remained. A classification with 32 types of computer use problems was developed. Problems were grouped into information input (31%), transfer (20%), output (20%) and general technical (24%). Overall, 55% of problems were machine related and 45% were attributed to human-computer interaction. Delays in initiating and completing clinical tasks were a major consequence of machine related problems (70%) whereas rework was a major consequence of human-computer interaction problems (78%). While 38% (n=26) of the incidents were reported to have a noticeable consequence but no harm, 34% (n=23) had no noticeable consequence. Conclusion: Only 0.2% of all incidents reported were computer related. Further work is required to expand our classification using incident reports and other sources of information about healthcare IT problems. Evidence based user interface design must focus on the safe entry and retrieval of clinical information and support users in detecting and correcting errors and malfunctions.

Original languageEnglish
Pages (from-to)663-670
Number of pages8
JournalJournal of the American Medical Informatics Association
Issue number6
Publication statusPublished - Nov 2010
Externally publishedYes


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