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. 2010 Oct;19(5):425-9.
doi: 10.1136/qshc.2008.031591. Epub 2010 May 31.

Development of trigger tools for surveillance of adverse events in ambulatory surgery

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Development of trigger tools for surveillance of adverse events in ambulatory surgery

Haytham M A Kaafarani et al. Qual Saf Health Care. 2010 Oct.

Abstract

Background: The trigger tool methodology uses clinical algorithms applied electronically to 'flag' medical records where adverse events (AEs) have most likely occurred. The authors sought to create surgical triggers to detect AEs in the ambulatory care setting.

Methods: Four consecutive steps were used to develop ambulatory surgery triggers. First, the authors conducted a comprehensive literature review for surgical triggers. Second, a series of multidisciplinary focus groups (physicians, nurses, pharmacists and information technology specialists) provided user input on trigger selection. Third, a clinical advisory panel designed an initial set of 10 triggers. Finally, a three-phase Delphi process (surgical and trigger tool experts) evaluated and rated the suggested triggers.

Results: The authors designed an initial set of 10 surgical triggers including five global triggers (flagging medical records for the suspicion of any AE) and five AE-specific triggers (flagging medical records for the suspicion of specific AEs). Based on the Delphi rating of the trigger's utility for system-level interventions, the final triggers were: (1) emergency room visit(s) within 21 days from surgery; (2) unscheduled readmission within 30 days from surgery; (3) unscheduled procedure (interventional radiological, urological, dental, cardiac or gastroenterological) or reoperation within 30 days from surgery; (4) unplanned initial hospital length of stay more than 24 h; and (5) lower-extremity Doppler ultrasound order entry and ICD code for deep vein thrombosis or pulmonary embolus within 30 days from surgery.

Conclusion: The authors therefore propose a systematic methodology to develop trigger tools that takes into consideration previously published work, end-user preferences and expert opinion.

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