The Effect of Preexisting Conditions on Hospital Quality Measurement for Injured Patients

Department of Anesthesiology, University of Rochester School of Medicine, Rochester, NY 14642, USA.
Annals of surgery (Impact Factor: 8.33). 03/2010; 251(4):728-34. DOI: 10.1097/SLA.0b013e3181d56770
Source: PubMed

ABSTRACT To determine whether adjusting for comorbidities significantly affects hospital quality measurement compared with adjusting for injury severity alone.
Pre-existing conditions have a significant impact on mortality after injury. The impact of including comorbidities on hospital quality measurement is not well understood.
Retrospective cohort study using the Healthcare Cost and Utilization Project Nationwide Inpatient Sample (2005-2006). The Trauma Mortality Probability Model (TMPM-ICD9) was re-estimated with and without the addition of the comorbidity measures in the Agency for Health Research and Quality comorbidity algorithm. Hospital quality was measured using an adjusted odds ratio (OR) obtained using hierarchical logistic regression modeling. The OR quantifies the likelihood that trauma patients treated at a specific hospital are more or less likely to die compared with patients treated at an average hospital. Hospitals with an adjusted OR significantly greater than, or less than 1 were classified as low-quality or high-quality outliers, respectively. Pairwise comparison of hospital quality based on TMPM-ICD9 with and without comorbidity information were performed using the intraclass correlation coefficient, the Spearman correlation coefficient, the Bland-Altman Plot, and the kappa statistic.
There was nearly perfect agreement between hospital ranking based on TMPM-ICD9 and TMPM-ICD9 with comorbidities. The intraclass correlation coefficient was 0.943 (95% CI, 0.931-0.951), the Spearman correlation coefficient was 0.953 (95% CI, 0.944-0.960), and the kappa statistic was 0.863 (95% CI, 0.792-0.934). The odds of a patient dying in the worst 5% hospitals was 1.73 (95% CI, 1.61-1.86), whereas the odds of a patient dying in the best 5% of the hospitals was 0.37 (95% CI, 0.31-0.44).
In this large study of 148,280 trauma patients in 511 hospitals, we found no evidence that adding comorbidites to the risk-adjustment model used to benchmark hospital performance changes hospital ranking. In addition, there appears to be significant variability in mortality outcomes between the best and worst performing hospitals. This difference in outcomes across hospitals may represent a significant opportunity to improve health outcomes for injured patients.

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    • "This model did not include race as a predictor variable. The empirical-Bayes estimate of the hospital effect was exponentiated to obtain the adjusted mortality odds ratio for each hospital (Glance et al. 2010). Hospitals with an adjusted odds ratio greater than 1 and whose 95 percent confidence interval did not include 1 were classified as lowquality outliers, whereas hospitals with adjusted odds ratios significantly less than 1 were classified as high-quality outliers. "
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    ABSTRACT: Objective To determine whether outcome disparities between black and white trauma patients have decreased over the last 10years. Data SourcePennsylvania Trauma Outcome Study. Study DesignWe performed an observational cohort study on 191,887 patients admitted to 28 Level 1 and Level II trauma centers. The main outcomes of interest were (1) death, (2) death or major complication, and (3) failure-to-rescue. Hospitals were categorized according to the proportion of black patients. Multivariate regression models were used to estimate trends in racial disparities and to assess whether the source of racial disparities was within or between hospitals. Principal FindingsTrauma patients admitted to hospitals with high concentrations of blacks (>20 percent) had a 45 percent higher odds of death (adj OR: 1.45, 95 percent CI: 1.09-1.92) and a 73 percent higher odds of death or major complication (adj OR: 1.73, 95 percent CI: 1.42-2.11) compared with patients admitted to hospitals treating low proportions of blacks. Blacks and whites admitted to the same hospitals had no difference in mortality (adj OR: 1.05, 95 percent CI: 0.87, 1.27) or death or major complications (adj OR: 1.01; 95 percent CI: 0.90, 1.13). The odds of overall mortality, and death or major complications have been reduced by 32 percent (adj OR: 0.68; 95 percent CI: 0.54-0.86) and 28 percent (adj OR: 0.72; 95 percent CI: 0.60-0.85) between 2000 and 2009, respectively. Racial disparities did not change over 10years. Conclusion Despite the overall improvement in outcomes, the gap in quality of care between black and white trauma patients in Pennsylvania has not narrowed over the last 10years. Racial disparities in trauma are due to the fact that black patients are more likely to be treated in lower quality hospitals compared with whites.
    Health Services Research 05/2013; 48(5). DOI:10.1111/1475-6773.12064 · 2.78 Impact Factor
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    • "We controlled for patient demographics (age and gender), injury severity, mechanism of injury, and comorbidities. Injury severity was coded using empirically-derived estimates of injury severity based on the previously validated Trauma Mortality Prediction Model (TMPM) [30,31]. The AHRQ comorbidity algorithm was used to code patient comorbidities [20]. "
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    ABSTRACT: The enormous fiscal pressures facing trauma centers may lead trauma centers to reduce nurse staffing and to make increased use of less expensive and less skilled personnel. The impact of nurse staffing and skill mix on trauma outcomes has not been previously reported. The goal of this study was to examine whether nurse staffing levels and nursing skill mix are associated with trauma patient outcomes. We used data from the Healthcare Cost and Utilization Project Nationwide Inpatient Sample to perform a cross-sectional study of 70,142 patients admitted to 77 Level I and Level II centers. Logistic regression models were used to examine the association between nurse staffing measures and (1) mortality, (2) healthcare associated infections (HAI), and (3) failure-to-rescue. We controlled for patient risk factors (age, gender, injury severity, mechanism of injury, comorbidities) and hospital structural characteristics (trauma center status - Level I versus Level II, hospital size, ownership, teaching status, technology level, and geographic region). A 1% increase in the ratio of licensed practical nurse (LPN) to total nursing time was associated with a 4% increase in the odds of mortality (adj OR 1.04; 95% CI: 1.02-1.06; pā€‰=ā€‰0.001) and a 6% increase in the odds of sepsis (adj OR 1.06: 1.03-1.10; pā€‰<ā€‰0.001). Hospitals in the highest quartile of LPN staffing had 3 excess deaths (95% CI: 1.2, 5.1) and 5 more episodes of sepsis (95% CI: 2.3, 7.6) per 1000 patients compared to hospitals in the lower quartile of LPN staffing. Higher hospital LPN staffing levels are independently associated with slightly higher rates of mortality and sepsis in trauma patients admitted to Level I or Level II trauma centers.
    BMC Health Services Research 08/2012; 12(1):247. DOI:10.1186/1472-6963-12-247 · 1.71 Impact Factor
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    ABSTRACT: To examine the association between trauma center quality and costs. Current efforts to reduce health care costs and improve health care quality require a better understanding of the relationship between cost and quality. Using data from the Healthcare Cost and Utilization Projects Nationwide Inpatient Sample, we performed a retrospective observational study of 67,124 trauma patients admitted to 73 trauma centers. Generalized linear models were used to explore the association between hospital cost and in-hospital mortality, controlling for hospital and patient factors as follows: injury diagnoses, age, gender, mechanism of injury, comorbidities, teaching status, hospital ownership, geographic region, and hospital wages. Patients treated in hospitals with low risk-adjusted mortality rates had significantly lower costs than those treated in average-quality hospitals. The relative cost of patients treated in high-quality hospitals was 0.78 (95% confidence interval: 0.64, 0.95) compared with average-quality hospitals. The cost of treating patients in average- and high-mortality trauma centers was similar. In this study based on the Healthcare Cost and Utilization Project Nationwide Inpatient Sample, the care of injured patients is less expensive in hospitals with lower risk-adjusted mortality rates. Hospitals with low risk-adjusted mortality rates have adjusted mortality rates that are 34% lower while spending nearly 22% less compared with average-quality hospitals.
    Annals of surgery 08/2010; 252(2):217-22. DOI:10.1097/SLA.0b013e3181e623f6 · 8.33 Impact Factor
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