Applying trigger tools to detect adverse events associated with outpatient surgery

Area of Science:

• Health Services Research
• Patient Safety
• Surgical Outcomes

Background:

• Adverse events (AEs) detection is crucial for improving surgical care quality.
• Outpatient surgery is increasing, yet AE detection methods primarily focus on inpatients.
• Existing AE surveillance tools require enhancement for the outpatient setting.

Purpose of the Study:

• To evaluate the performance of five distinct triggers designed to detect AEs in outpatient surgery.
• To assess the utility of trigger-based surveillance algorithms in identifying potential AEs following same-day surgical procedures.
• To compare the effectiveness of different triggers in flagging cases likely to involve adverse events.

Main Methods:

• Retrospective analysis of electronic medical records from three large health care systems.
• Inclusion criteria: outpatient surgery in 2007 with clinical notes within 6 months post-surgery.
• Nurse abstractors reviewed trigger-flagged cases, calculating positive predictive values (PPVs) after achieving interrater reliability (κ > 0.60).

Main Results:

• Surgical triggers flagged 1%-22% of outpatient surgery cases, with PPVs ranging from 6.0% to 62.0%.
• Triggers for pulmonary embolism, deep vein thrombosis, and emergency department visits demonstrated the highest PPVs.
• These specific triggers showed the most promise for efficiently screening high-risk cases for potential AEs.

Conclusions:

• Trigger tools can aid in identifying specific surgeries for further review to confirm AEs.
• This approach complements existing AE detection initiatives, particularly in the outpatient surgical setting.
• Enhanced AE detection in outpatient surgery can guide quality improvement efforts.