Development of trigger tools for surveillance of adverse events in ambulatory surgery
ABSTRACT 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.
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.
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.
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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ABSTRACT: The objective of this study is to evaluate the performance of 5 triggers to detect adverse events (AEs) associated with outpatient surgery. Triggers use surveillance algorithms derived from clinical logic to flag cases where AEs have most likely occurred. Current efforts to detect AEs have focused primarily on the inpatient setting, despite the increase in outpatient surgery in all health care settings. Using trigger logic, we retrospectively evaluated data from 3 large health care systems' electronic medical records. Patients were eligible for inclusion if they had an outpatient (same-day) surgery in 2007 and at least 1 clinical note in the 6 months after the surgery. Two nurse abstractors reviewed a sample of trigger-flagged cases from each health care system. After reaching interrater reliability targets (κ > 0.60), we calculated the positive predictive value (PPV) of each trigger and the confidence interval of the estimate. The surgical triggers flagged between 1% and 22% of the outpatient surgery cases, with a wide range in PPVs (6.0%-62.0%). The pulmonary embolism and deep vein thrombosis and emergency department triggers had the lowest proportion of flagged cases along with the highest PPVs, showing the most promise for screening cases with a high probability of AE occurrence. Triggers may be useful in identifying a narrow set of surgeries for further review to determine if a surgical AE occurred, complementing existing tools and initiatives used to detect AEs. Improved detection of AEs in outpatient surgery should help target potential areas for quality improvement.Journal of Patient Safety 03/2011; 7(1):45-59. DOI:10.1097/PTS.0b013e31820d164b · 0.88 Impact Factor
- BMJ quality & safety 11/2011; 21(2):89-92. DOI:10.1136/bmjqs-2011-000590 · 3.28 Impact Factor
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ABSTRACT: Diagnostic errors in primary care are harmful but difficult to detect. The authors tested an electronic health record (EHR)-based method to detect diagnostic errors in routine primary care practice. The authors conducted a retrospective study of primary care visit records 'triggered' through electronic queries for possible evidence of diagnostic errors: Trigger 1: A primary care index visit followed by unplanned hospitalisation within 14 days and Trigger 2: A primary care index visit followed by ≥1 unscheduled visit(s) within 14 days. Control visits met neither criterion. Electronic trigger queries were applied to EHR repositories at two large healthcare systems between 1 October 2006 and 30 September 2007. Blinded physician-reviewers independently determined presence or absence of diagnostic errors in selected triggered and control visits. An error was defined as a missed opportunity to make or pursue the correct diagnosis when adequate data were available at the index visit. Disagreements were resolved by an independent third reviewer. Queries were applied to 212 165 visits. On record review, the authors found diagnostic errors in 141 of 674 Trigger 1-positive records (positive predictive value (PPV)=20.9%, 95% CI 17.9% to 24.0%) and 36 of 669 Trigger 2-positive records (PPV=5.4%, 95% CI 3.7% to 7.1%). The control PPV of 2.1% (95% CI 0.1% to 3.3%) was significantly lower than that of both triggers (p≤0.002). Inter-reviewer reliability was modest, though higher than in comparable previous studies (к=0.37 (95% CI 0.31 to 0.44)). While physician agreement on diagnostic error remains low, an EHR-facilitated surveillance methodology could be useful for gaining insight into the origin of these errors.BMJ quality & safety 02/2012; 21(2):93-100. DOI:10.1136/bmjqs-2011-000304 · 3.28 Impact Factor