Complications in surgical patients.
ABSTRACT Complications are common in hospitalized surgical patients. Provider error contributes to a significant proportion of these complications.
Surgical patients were concurrently observed for the development of explicit complications. All complications were reviewed by the attending surgeon and other members of the service and evaluated for the severity of sequelae (major or minor) and for whether the complication resulted from medical error (avoidable) or not.
University teaching hospital with a level I trauma designation.
All inpatients (operative or nonoperative) from 4 different surgical services: general surgery, combined general surgery and trauma, vascular surgery, and cardiothoracic surgery.
Total complication rate (number of complications divided by the number of patients) and the number of patients with complications. Complications were separated into those with major or minor sequelae and the proportion of each type that were due to medical error (avoidable). Rates of complications in a recent Institute of Medicine report were used as a criterion standard.
The data for the respective groups (general surgery, vascular surgery, combined general surgery and trauma, and cardiothoracic surgery) are as follows. The number of patients was 1363, 978, 914, and 1403; number of complications, 413, 409, 295, and 378; total complication rate, 30.3%, 42.4%, 32.3%, and 26.9%; minor complication rate, 13.3%, 19.9%, 13.5%, and 13.0% (percentage of minor complications that were avoidable, 37.4%, 59.0%, 51.2%, and 49.5%); major complication rate, 16.2%, 21.1%, 18.1%, and 12.9% (percentage of major complications that were avoidable, 53.4%, 60.7%, 38.8%, and 38.7%); and mortality rate, 1.83%, 3.33%, 2.28%, and 3.34% (percentage of mortality that was avoidable, 28.0%, 44.1%, 19.0%, and 25.0%).
Despite mortality rates that compare favorably with national benchmarks, a prospective examination of surgical patients reveals complication rates that are 2 to 4 times higher than those identified in an Institute of Medicine report. Almost half of these adverse events were judged contemporaneously by peers to be due to provider error (avoidable). Errors in care contributed to 38 (30%) of 128 deaths. Recognition that provider error contributes significantly to adverse events presents significant opportunities for improving patient outcomes.
Conference Paper: Automated prediction of adverse post-surgical outcomes[Show abstract] [Hide abstract]
ABSTRACT: Patients undergoing surgery can experience a range of adverse events, such as renal and cardiac injury, respiratory failure, and death. This study focuses on discovering relationships between perioperative physiological data and adverse post-surgical outcomes, with the goal of developing strategies to reduce the severity and frequency of these conditions. Analyzing the patient's preoperative demographic data, such as age and race, and perioperative physiologic data, such as blood pressure and anesthesia dosage, we use statistical models to predict whether a patient under anesthesia will develop renal or cardiac injury, respiratory failure, or death. Specifically, we compare generalized linear models, random forest models, and L1 regularized logistic regression models in predicting these adverse events. For each event, the random forest model generally outperformed its competitors, as shown in receiver operating characteristic (ROC) curves and evidenced by the higher area under the curve (AUC) values of 0.85, 0.86, 0.85, and 0.82 for death, renal injury, respiratory failure, and cardiac injury, respectively. However, score tables indicate that at certain thresholds, the L1 regularized logistic regression predicts fewer false negatives than the random forest models. In general, our findings show the existence of a relationship between perioperative predictors and post-surgical complications. This relationship could provide the foundation for a surveillance and alert system.2014 Systems and Information Engineering Design Symposium (SIEDS); 04/2014
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ABSTRACT: Surgery is one of the high-risk areas for the occurrence of adverse events (AE). The purpose of this study is to know the percentage of hospitalisation-related AE that are detected by the «Global Trigger Tool» methodology in surgical patients, their characteristics and the tool validity. Retrospective, observational study on patients admitted to a general surgery department, who underwent a surgical operation in a third level hospital during the year 2012. The identification of AE was carried out by patient record review using an adaptation of «Global Trigger Tool» methodology. Once an AE was identified, a harm category was assigned, including the grade in which the AE could have been avoided and its relation with the surgical procedure. The prevalence of AE was 36,8%. There were 0,5 AE per patient. 56,2% were deemed preventable. 69,3% were directly related to the surgical procedure. The tool had a sensitivity of 86% and a specificity of 93,6%. The positive predictive value was 89% and the negative predictive value 92%. Prevalence of AE is greater than the estimate of other studies. In most cases the AE detected were related to the surgical procedure and more than half were also preventable. The adapted «Global Trigger Tool» methodology has demonstrated to be highly effective and efficient for detecting AE in surgical patients, identifying all the serious AE with few false negative results. Copyright © 2014 AEC. Published by Elsevier Espana. All rights reserved.Cirugía Española 10/2014; 93(2). DOI:10.1016/j.cireng.2014.12.005 · 0.89 Impact Factor
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ABSTRACT: La cirugía supone una de las áreas de alto riesgo para la aparición de efectos adversos (EA). El objetivo de este estudio es conocer el porcentaje de EA en hospitalización que se detectan mediante la metodología «Global Trigger Tool» en pacientes de cirugía general, las características de los mismos y la validez de la herramienta.Cirugía Española 10/2014; 93(2). DOI:10.1016/j.ciresp.2014.08.007 · 0.89 Impact Factor