A multicenter prospective study of surgical audit systems
| Autor: | Shoichiro Koike, Masakazu Ikenaga, Toshihiro Saitoh, Yasuo Wada, Masato Koseki, Yoshio Haga, Noriyoshi Akiyama, Koji Ikejiri, Tadateru Takahashi |
|---|---|
| Rok vydání: | 2011 |
| Předmět: |
Adult
Male Pediatrics medicine.medical_specialty Surgical stress Adolescent MEDLINE Audit Risk Assessment Young Adult Postoperative Complications Japan medicine Humans Hospital Mortality Prospective Studies Prospective cohort study Aged Aged 80 and over Medical Audit business.industry Reproducibility of Results Surgical procedures Middle Aged Multicenter study ROC Curve Health Care Surveys Surgical Procedures Operative Emergency medicine Feasibility Studies Surgery Female Risk assessment business Surgical audit |
| Zdroj: | Annals of surgery. 253(1) |
| ISSN: | 1528-1140 |
| Popis: | This study was undertaken to evaluate a modified form of Estimation of Physiologic Ability and Surgical Stress (E-PASS) for surgical audit comparing with other existing models.Although several scoring systems have been devised for surgical audit, no nation-wide survey has been performed yet.We modified our previous E-PASS surgical audit system by computing the weights of 41 procedures, using data from 4925 patients who underwent elective digestive surgery, designated it as mE-PASS. Subsequently, a prospective cohort study was conducted in 43 national hospitals in Japan from April 1, 2005, to April 8, 2007. Variables for the E-PASS and American Society of Anesthesiologists (ASA) status-based model were collected for 5272 surgically treated patients. Of the 5272 patients, we also collected data for the Portsmouth modification of Physiologic and Operative Severity Score for the enUmeration of Mortality and morbidity (P-POSSUM) in 3128 patients. The area under the receiver operative characteristic curve (AUC) was used to evaluate discrimination performance to detect in-hospital mortality. The ratio of observed to estimated in-hospital mortality rates (OE ratio) was defined as a measure of quality.The numbers of variables required were 10 for E-PASS, 7 for mE-PASS, 20 for P-POSSUM, and 4 for the ASA status-based model. The AUC (95% confidence interval) values were 0.86 (0.79-0.93) for E-PASS, 0.86 (0.79-0.92) for mE-PASS, 0.81 (0.75-0.88) for P-POSSUM, and 0.73 (0.63-0.83) for the ASA status-based model. The OE ratios for mE-PASS among large-volume hospitals significantly correlated with those for E-PASS (R = 0.93, N = 9, P = 0.00026), P-POSSUM (R = 0.96, N = 6, P = 0.0021), and ASA status-based model (R = 0.83, N = 9, P = 0.0051).Because of its features of easy use, accuracy, and generalizability, mE-PASS is a candidate for a nation-wide survey. |
| Databáze: | OpenAIRE |
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