Beyond Volume: Does Hospital Complexity Matter? An Analysis of Inpatient Surgical Mortality in the United States
ABSTRACT Hospitals show wide variation in outcomes and systems of care. It is unclear whether hospital complexity-the range of services and technologies provided-affects outcomes and in what direction. We sought to determine whether complexity was associated with inpatient surgical mortality.
Using national Medicare data, we identified all fee-for-service inpatients who underwent 1 of 5 common high-risk surgical procedures in 2008-2009 and measured complexity by the number of unique primary diagnoses admitted to each hospital over the 2-year period. We calculated 30-day postoperative mortality rates, adjusting for patient and hospital characteristics, and used multivariable Poisson regression models to test for an association between hospital complexity and mortality rates. We then used this model to generate predicted mortality rates for low-volume and high-volume hospitals across the spectrum of hospital complexity.
A total of 2691 hospitals were analyzed, representing a total of 382,372 admissions. After adjusting for hospital characteristics, including hospital volume, increasing hospital complexity was associated with lower surgical mortality rates. Patients receiving care at the hospitals in the lowest quintile of unique diagnoses had a 27% higher risk of death than those at the highest quintile. The effect of complexity was largest for low-volume hospitals, which were capable of achieving mortality rates similar to high-volume hospitals when in the most complex quintile.
Hospital complexity matters and is associated with lower surgical mortality rates, independent of hospital volume. The effect of complexity on outcomes for nonsurgical services warrants investigation.
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ABSTRACT: Death within 1 month of surgery is considered treatment related and serves as an important healthcare quality metric. We sought to identify the incidence of and factors associated with 1-month mortality after cancer-directed surgery. We used the Surveillance, Epidemiology and End Results Program to study a cohort of 1,110,236 patients diagnosed from 2004-2011 with cancers that are among the 10 most common or most fatal who received cancer-directed surgery. Multivariable logistic regression analyses were used to identify factors associated with 1-month mortality after cancer-directed surgery. 53,498 patients (4.8%) died within 1 month of cancer-directed surgery. Patients who were married, insured, or who had a top 50th percentile income or educational status had lower odds of 1-month mortality from cancer-directed surgery ([adjusted odds ratio (AOR) 0.80; 95% CI 0.79 - 0.82; P<0.001], [AOR 0.88; (0.82 - 0.94); P<0.001], [AOR 0.95; (0.93 - 0.97); P<0.001], and [AOR 0.98; (0.96 - 0.99); P=0.043], respectively). Patients who were non-white minority, male, or older (per year increase), or who had advanced tumor stage 4 disease all had a higher risk of 1-month mortality after cancer-directed surgery, with AORs of 1.13 (1.11 - 1.15), P<0.001; 1.11 (1.08 - 1.13), P<0.001; 1.02 (1.02 - 1.03), P<0.001; and 1.89 (1.82 - 1.95), P<0.001 respectively. Unmarried, uninsured, non-white, male, older, less educated, and poorer patients were all at a significantly higher risk for death within 1 month of cancer-directed surgery. Efforts to reduce 1-month surgical mortality and eliminate sociodemographic disparities in this adverse outcome could significantly improve survival among patients with cancer. © The Author 2014. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: firstname.lastname@example.org.Annals of Oncology 11/2014; 26(2). DOI:10.1093/annonc/mdu534 · 7.04 Impact Factor
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ABSTRACT: Previous studies reported improved outcomes for bladder cancer patients who had radical cystectomy (RC) performed by surgeons and hospitals with high annual RC volumes. The objective of this study was to determine the effect of high hospital and surgeon volume on overall survival after RC for bladder cancer in Quebec. We conducted a retrospective cohort study using data of patients who underwent RC for bladder cancer from 2000 to 2009. The cohort was obtained with the linkage of two health databases: the RAMQ database (data on medical services) and the ISQ database (vital status data). Hospital and surgeon volumes were defined as the average annual number of RC performed at an institution or by surgeon, respectively, during the study period. We considered high hospital and surgeon volume those found in the third and fourth quartiles of the distribution of hospital and surgeon volumes. The effect of high hospital and surgeon volume on survival was assessed by multivariate Cox proportional hazards models. We analyzed a total of 2,778 patients who met inclusion criteria (75 % males). High hospital volume and surgeons were found to be significantly associated with improved overall survival (HR = 0.87, 95 % CI: 0.78-0.97 and HR = 0.81, 95 % CI: 0.71-0.91, respectively). The combined effect of high-volume hospital and high-volume surgeon decreased by 20 % the risk of long-term mortality (HR = 0.80, 95 % CI: 0.70-0.91). Compared to low-volume providers, having RC for bladder cancer performed in high-volume hospitals or by high-volume surgeon was associated with improved overall survival.World Journal of Urology 12/2014; 33(9). DOI:10.1007/s00345-014-1457-4 · 2.67 Impact Factor
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ABSTRACT: Informed consent for operative procedures performed on children relies on the ability of the surgeon to estimate and describe accurately the risks and benefits of the planned operation to the parents. Understanding patient-specific risks is also an important prerequisite for surgeons and hospital administrators who wish to change hospital processes and improve patient safety. This study tests the feasibility of estimating the risk of death within 30 days of surgery using National Surgical Quality Improvement Program (NSQIP)-Pediatric data from a single children's hospital. Patient data submitted to NSQIP-Pediatric from our hospital were analyzed to identify variables predictive of death within 30 days of operation. A multiple logistic regression model was constructed using 3 years of data and validated using data submitted the following year. The model was then tested using the participant use file provided by NSQIP-Pediatric for 2012. The model identified 7 variables predictive of death: neonatal status, respiratory support, inotropic support, having a blood disorder, cerebrovascular injury, previous cardiac intervention, and the work relative value unit for the procedure. The resulting final model had a c statistic = 0.97. It is possible for a participating children's hospital to use NSQIP-Pediatric data to develop risk models for patient mortality occurring within 30 days of operation at their institution. The model presented may be generalizable to other institutions, but needs further testing and refining. Copyright © 2015 Elsevier Inc. All rights reserved.Surgery 06/2015; DOI:10.1016/j.surg.2015.04.026 · 3.38 Impact Factor