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. 2010 Oct;19(5):435-9.
doi: 10.1136/qshc.2008.031393. Epub 2010 Aug 25.

Identifying causes of adverse events detected by an automated trigger tool through in-depth analysis

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Identifying causes of adverse events detected by an automated trigger tool through in-depth analysis

S E Muething et al. Qual Saf Health Care. 2010 Oct.

Abstract

Objectives: To describe how in-depth analysis of adverse events can reveal underlying causes.

Methods: Triggers for adverse events were developed using the hospital's computerised medical record (naloxone for opiate-related oversedation and administration of a glucose bolus while on insulin for insulin-related hypoglycaemia). Triggers were identified daily. Based on information from the medical record and interviews, a subject expert determined if an adverse drug event had occurred and then conducted a real-time analysis to identify event characteristics. Expert groups, consisting of frontline staff and specialist physicians, examined event characteristics and determined the apparent cause.

Results: 30 insulin-related hypoglycaemia events and 34 opiate-related oversedation events were identified by the triggers over 16 and 21 months, respectively. In the opinion of the experts, patients receiving continuous-infusion insulin and those receiving dextrose only via parenteral nutrition were at increased risk for insulin-related hypoglycaemia. Lack of standardisation in insulin-dosing decisions and variation regarding when and how much to adjust insulin doses in response to changing glucose levels were identified as common causes of the adverse events. Opiate-related oversedation events often occurred within 48 h of surgery. Variation in pain management in the operating room and post-anaesthesia care unit was identified by the experts as potential causes. Variations in practice, multiple services writing orders, multidrug regimens and variations in interpretation of patient assessments were also noted as potential contributing causes.

Conclusions: Identification of adverse drug events through an automated trigger system, supplemented by in-depth analysis, can help identify targets for intervention and improvement.

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