Identification of Patients With Postoperative Complications Who Are at Risk for Failure to Rescue

IMPORTANCE: A minority of patients who experience postoperative complications die (failure to rescue). Understanding the preoperative factors that lead to failure to rescue helps surgeons predict and avoid operative mortality. OBJECTIVE: To provide a mechanism for identifying a high-risk group of pa...

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Veröffentlicht in:JAMA surgery 2014-11, Vol.149 (11), p.1103-1108
Hauptverfasser: Ferraris, Victor A, Bolanos, Michael, Martin, Jeremiah T, Mahan, Angela, Saha, Sibu P
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container_end_page 1108
container_issue 11
container_start_page 1103
container_title JAMA surgery
container_volume 149
creator Ferraris, Victor A
Bolanos, Michael
Martin, Jeremiah T
Mahan, Angela
Saha, Sibu P
description IMPORTANCE: A minority of patients who experience postoperative complications die (failure to rescue). Understanding the preoperative factors that lead to failure to rescue helps surgeons predict and avoid operative mortality. OBJECTIVE: To provide a mechanism for identifying a high-risk group of patients with postoperative complications who are at a substantially increased risk for failure to rescue. DESIGN, SETTING, AND PATIENTS: Observational study evaluating failure to rescue in patients entered into the American College of Surgeons National Surgical Quality Improvement Program database. The large sample of surgical patients included in this study underwent a wide range of operations during a 5-year period in more than 200 acute care hospitals. We examined and identified patients at high risk for failure to rescue using propensity stratification. We also developed a risk-scoring system that allowed preoperative identification of patients at the highest risk for failure to rescue. MAIN OUTCOMES AND MEASURES: Risk-scoring system that predicts failure to rescue. RESULTS: Of the 1 956 002 database patients, there were 207 236 patients who developed serious postoperative complications. Deaths occurred in 21 731 patients with serious complications (10.5% failure to rescue). Stratification of patients into quintiles, according to their propensity for developing serious complications, found that 90% of operative deaths occurred in the highest-risk quintile, usually within a week of developing the initial complication. A risk-scoring system for failure to rescue, based on regression-derived variable odds ratios, predicted patients in the highest-risk quintile with good predictive accuracy. Only 31.8% of failure-to-rescue patients had a single postoperative complication. Perioperative deaths increased exponentially as the number of complications per patient increased. Patients with complications who had surgical residents involved in their care had reduced rates of failure to rescue compared with patients without resident involvement. CONCLUSIONS AND RELEVANCE: Twenty percent of high-risk patients account for 90% of failure to rescue (Pareto principle). More than two-thirds of patients with failure to rescue have multiple complications. On average, a few days elapse before death following a complication. A risk-scoring system based on preoperative variables predicts patients in the highest-risk category of failure to rescue with good accuracy. In high-risk patie
doi_str_mv 10.1001/jamasurg.2014.1338
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Understanding the preoperative factors that lead to failure to rescue helps surgeons predict and avoid operative mortality. OBJECTIVE: To provide a mechanism for identifying a high-risk group of patients with postoperative complications who are at a substantially increased risk for failure to rescue. DESIGN, SETTING, AND PATIENTS: Observational study evaluating failure to rescue in patients entered into the American College of Surgeons National Surgical Quality Improvement Program database. The large sample of surgical patients included in this study underwent a wide range of operations during a 5-year period in more than 200 acute care hospitals. We examined and identified patients at high risk for failure to rescue using propensity stratification. We also developed a risk-scoring system that allowed preoperative identification of patients at the highest risk for failure to rescue. MAIN OUTCOMES AND MEASURES: Risk-scoring system that predicts failure to rescue. RESULTS: Of the 1 956 002 database patients, there were 207 236 patients who developed serious postoperative complications. Deaths occurred in 21 731 patients with serious complications (10.5% failure to rescue). Stratification of patients into quintiles, according to their propensity for developing serious complications, found that 90% of operative deaths occurred in the highest-risk quintile, usually within a week of developing the initial complication. A risk-scoring system for failure to rescue, based on regression-derived variable odds ratios, predicted patients in the highest-risk quintile with good predictive accuracy. Only 31.8% of failure-to-rescue patients had a single postoperative complication. Perioperative deaths increased exponentially as the number of complications per patient increased. Patients with complications who had surgical residents involved in their care had reduced rates of failure to rescue compared with patients without resident involvement. CONCLUSIONS AND RELEVANCE: Twenty percent of high-risk patients account for 90% of failure to rescue (Pareto principle). More than two-thirds of patients with failure to rescue have multiple complications. On average, a few days elapse before death following a complication. A risk-scoring system based on preoperative variables predicts patients in the highest-risk category of failure to rescue with good accuracy. 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Understanding the preoperative factors that lead to failure to rescue helps surgeons predict and avoid operative mortality. OBJECTIVE: To provide a mechanism for identifying a high-risk group of patients with postoperative complications who are at a substantially increased risk for failure to rescue. DESIGN, SETTING, AND PATIENTS: Observational study evaluating failure to rescue in patients entered into the American College of Surgeons National Surgical Quality Improvement Program database. The large sample of surgical patients included in this study underwent a wide range of operations during a 5-year period in more than 200 acute care hospitals. We examined and identified patients at high risk for failure to rescue using propensity stratification. We also developed a risk-scoring system that allowed preoperative identification of patients at the highest risk for failure to rescue. MAIN OUTCOMES AND MEASURES: Risk-scoring system that predicts failure to rescue. RESULTS: Of the 1 956 002 database patients, there were 207 236 patients who developed serious postoperative complications. Deaths occurred in 21 731 patients with serious complications (10.5% failure to rescue). Stratification of patients into quintiles, according to their propensity for developing serious complications, found that 90% of operative deaths occurred in the highest-risk quintile, usually within a week of developing the initial complication. A risk-scoring system for failure to rescue, based on regression-derived variable odds ratios, predicted patients in the highest-risk quintile with good predictive accuracy. Only 31.8% of failure-to-rescue patients had a single postoperative complication. Perioperative deaths increased exponentially as the number of complications per patient increased. Patients with complications who had surgical residents involved in their care had reduced rates of failure to rescue compared with patients without resident involvement. CONCLUSIONS AND RELEVANCE: Twenty percent of high-risk patients account for 90% of failure to rescue (Pareto principle). More than two-thirds of patients with failure to rescue have multiple complications. On average, a few days elapse before death following a complication. A risk-scoring system based on preoperative variables predicts patients in the highest-risk category of failure to rescue with good accuracy. 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Understanding the preoperative factors that lead to failure to rescue helps surgeons predict and avoid operative mortality. OBJECTIVE: To provide a mechanism for identifying a high-risk group of patients with postoperative complications who are at a substantially increased risk for failure to rescue. DESIGN, SETTING, AND PATIENTS: Observational study evaluating failure to rescue in patients entered into the American College of Surgeons National Surgical Quality Improvement Program database. The large sample of surgical patients included in this study underwent a wide range of operations during a 5-year period in more than 200 acute care hospitals. We examined and identified patients at high risk for failure to rescue using propensity stratification. We also developed a risk-scoring system that allowed preoperative identification of patients at the highest risk for failure to rescue. MAIN OUTCOMES AND MEASURES: Risk-scoring system that predicts failure to rescue. RESULTS: Of the 1 956 002 database patients, there were 207 236 patients who developed serious postoperative complications. Deaths occurred in 21 731 patients with serious complications (10.5% failure to rescue). Stratification of patients into quintiles, according to their propensity for developing serious complications, found that 90% of operative deaths occurred in the highest-risk quintile, usually within a week of developing the initial complication. A risk-scoring system for failure to rescue, based on regression-derived variable odds ratios, predicted patients in the highest-risk quintile with good predictive accuracy. Only 31.8% of failure-to-rescue patients had a single postoperative complication. Perioperative deaths increased exponentially as the number of complications per patient increased. Patients with complications who had surgical residents involved in their care had reduced rates of failure to rescue compared with patients without resident involvement. 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subjects Adult
Cause of Death
Databases, Factual
Hospital Mortality
Humans
Odds Ratio
Outcome Assessment (Health Care) - methods
Outcome Assessment (Health Care) - statistics & numerical data
Postoperative Complications - classification
Postoperative Complications - mortality
Risk Assessment - methods
Risk Factors
Survival Analysis
Treatment Failure
title Identification of Patients With Postoperative Complications Who Are at Risk for Failure to Rescue
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