Details

Autor(en) / Beteiligte

• Kaafarani, Haytham M.A., MD, MPH
• Mavros, Michael N., MD
• Hwabejire, John, MD, MPH
• Fagenholz, Peter, MD
• Yeh, Daniel D., MD, FACS
• Demoya, Marc, MD
• King, David R., MD, FACS
• Alam, Hasan B., MD, FACS
• Chang, Yuchiao, PhD
• Hutter, Matthew, MD, MPH, FACS
• Antonelli, Donna, BS, CPHQ
• Gervasini, Alice, RN, PhD
• Velmahos, George C., MD, PhD, FACS

Titel

Derivation and Validation of a Novel Severity Classification for Intraoperative Adverse Events

Ist Teil von

• Journal of the American College of Surgeons, 2014-06, Vol.218 (6), p.1120-1128

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2014

Quelle

MEDLINE

Beschreibungen/Notizen

• Background There is currently no systematic approach to evaluating the severity of intraoperative adverse events (iAEs). Study Design A 3-phase project was designed to develop and validate a novel severity classification scheme for iAEs. Phase 1 created the severity classification using a modified Delphi process. Phase 2 measured the classification's internal consistency by calculating inter-rater reliability among 91 surgeons using standardized iAEs scenarios. Phase 3 measured the classification's construct validity by testing whether major iAEs (severity class ≥3) correlated with worse 30-day postoperative outcomes compared with minor iAEs (severity class <3). This was achieved by creating a matched database using American College of Surgeons NSQIP and administrative data, querying for iAEs using the Patient Safety Indicator #15 (Accidental Puncture/Laceration), and iAE confirmation by chart review. Results Phase 1 resulted in a 6-point severity classification scheme. Phase 2 revealed an inter-rater reliability of 0.882. Of 9,292 patients, phase 3 included 181 confirmed with iAEs. All preoperative/intraoperative variables, including demographics, comorbidities, type of surgery performed, and operative length, were similar between patients with minor (n = 110) vs major iAEs (n = 71). In multivariable logistic analysis, severe iAEs correlated with higher risks of any postoperative complication (odds ratio [OR] = 3.8; 95% CI, 1.9−7.4; p < 0.001), surgical site infections (OR = 3.7; 95% CI, 1.7−8.2; p = 0.001), systemic sepsis (OR = 6.0; 95% CI, 2.1−17.2; p = 0.001), failure to wean off the ventilator (OR = 3.2; 95% CI, 1.2−8.9; p = 0.022), and postoperative length of stay ≥7 days (OR = 3.0; 95% CI, 1.5−5.9; p = 0.002). Thirty-day mortalities were similar (4.5% vs 7.1%; p = 0.46). Conclusions We propose a novel iAE severity classification system with high internal consistency and solid construct validity. Our classification scheme might prove essential for benchmarking quality of intraoperative care across hospitals and/or individual surgeons.