Hospital factors and racial disparities in mortality after surgery for breast and colon cancer.

PURPOSE: Black patients have worse prognoses than whites with breast or colorectal cancer. Mechanisms underlying such disparities have not been fully explored. We examined the role of hospital factors in racial differences in late mortality after surgery for breast or colon cancer. METHODS: Patients undergoing surgery after new diagnosis of breast or colon cancer were identified using the Surveillance Epidemiology and End Results-Medicare linked database (1995 to 2005). The main outcome measure was mortality at 5 years. Proportional hazards models were used to assess relationships between race and late mortality, accounting for patient factors, socioeconomic measures, and hospital factors. Fixed and random effects models were used to account for quality differences across hospitals. RESULTS: Black patients, compared with white patients, had lower 5-year overall survival rates after surgery for breast (62.1% v 70.4%, respectively; P < .001) and colon cancer (41.3% v 45.4%, respectively; P < .001). After controlling for age, comorbidity, and stage, black race remained an independent predictor of mortality for breast (adjusted hazard ratio [HR] = 1.25; 95% CI, 1.16 to 1.34) and colon cancer (adjusted HR = 1.13; 95% CI, 1.07 to 1.19). After risk adjustment, hospital factors explained 36% and 54% of the excess mortality for black patients with breast cancer and colon cancer, respectively. Hospitals with large minority populations had higher late mortality rates independent of race. CONCLUSION: Hospital factors, including quality, are important mediators of the association between race and mortality for breast and colon cancer. Hospital-level quality improvement should be a major component of efforts to reduce disparities in cancer outcomes.

Reaction time performance in upper airway resistance syndrome versus obstructive sleep apnea syndrome.

BACKGROUND: Patients with obstructive sleep apnea syndrome (OSAS) are known to have an increased risk for motor vehicle crashes. They suffer from sleep-related respiratory abnormality causing repetitive arousal leading to daytime sleepiness. In turn, it has been demonstrated that sleepiness can impair human psychomotor performance causing slowing of reaction times (RTs). Patients with OSAS present with RTs comparable to young adults under the influence of blood alcohol concentrations above the legally permitted level to drive a motor vehicle. Vigilance related risk levels in patients with upper airway resistance syndrome (UARS) and potential deficits in psychomotor performance are unknown. METHODS: We designed a study to compare psychomotor performance in UARS and compared it to patients with OSAS. Forty-seven UARS patients were matched by gender and age with 47 OSAS patients. All subjects completed a standardized vigilant attention task utilizing reaction time before undergoing polygraphic sleep studies. RESULTS: Patients with UARS presented worse psychomotor performance on most test metrics than patients with OSAS. CONCLUSIONS: Our study results may suggest that patients with UARS may also present an increased risk for motor vehicle crashes as previously demonstrated in OSAS patients.

Hospital volume, length of stay, and readmission rates in high-risk surgery.

OBJECTIVE: Aimed at reducing surgical deaths, several recent initiatives have attempted to establish volume-based referral strategies in high-risk surgery. Although payers are leading the most visible of these efforts, it is unknown whether volume standards will also reduce resource use. METHODS: We studied postoperative length of stay and 30-day readmission rate after 14 cardiovascular and cancer procedures using the 1994-1999 national Medicare database (total n = 2.5 million). We used regression techniques to examine the relationship between length of stay, 30-day readmission, and hospital volume, adjusting for age, gender, race, comorbidity score, admission acuity, and mean social security income. RESULTS: Mean postoperative length of stay ranged from 3.4 days (carotid endarterectomy) to 19.6 days (esophagectomy). There was no consistent relationship between volume and mean length of stay; it significantly increased across volume strata for 7 of the 14 procedures and significantly decreased across volume strata for the other 7. Mean length of stay at very-low-volume and very-high-volume hospitals differed by more than 1 day for 6 procedures. Of these, the mean length of stay was shorter in high-volume hospitals for 3 procedures (pancreatic resection, esophagectomy, cystectomy), but longer for other procedures (aortic and mitral valve replacement, gastrectomy). The 30-day readmission rate also varied widely by procedure, ranging from 9.9% (nephrectomy) to 22.2% (mitral valve replacement). However, volume was not related to 30-day readmission rate with any procedure. CONCLUSION: Although hospital volume may be an important predictor of operative mortality, it is not associated with resource use as reflected by length of stay or readmission rates.

Hospital volume and operative mortality in cancer surgery: a national study.

BACKGROUND: Although initiatives to regionalize cancer surgery are already under way, the relative importance of volume in cancer surgery is disputed. HYPOTHESIS: We examined surgical mortality with 8 cancer resections in the US population to better quantify the influence of hospital volume. METHODS: Using information from the all-payer Nationwide Inpatient Sample (1995-1997), we examined mortality with 8 cancer resections (N = 195 152). After dividing patients into 3 evenly sized volume groups based on hospital procedure volume (low, medium, and high), we used regression techniques to describe relationships between hospital volume and in-hospital mortality, adjusting for patient characteristics. RESULTS: Trends toward lower operative risks at high-volume hospitals were observed for 7 of the 8 procedures. However, differences between low- and high high-volume hospitals were statistically significant for only 3 operations (esophagectomy, 15.0% vs 6.5%; pancreatic resection, 13.1% vs 2.5%; and pulmonary lobectomy, 10.1% vs 8.9%, respectively). Although they did not reach statistical significance, absolute differences in mortality between low- and high-volume hospitals were greater than 1% for the following 3 procedures: gastrectomy, 8.7% vs 6.9%; cystectomy, 3.6% vs 2.5%; and pneumonectomy, 10.6% vs 8.9%, respectively. Mortality reductions for nephrectomy and colectomy were small. In general, in terms of absolute differences in mortality, the effect of volume was greatest in elderly patients. CONCLUSIONS: Operative mortality decreases with increasing hospital volume for several cancer resections. However, volume may be most important in patients who are older and at higher risk.

Effects of hospital volume on life expectancy after selected cancer operations in older adults: a decision analysis.

BACKGROUND: In addition to lower operative mortality, patients undergoing selected cancer operations at high volume centers have improved longterm survival. We sought to determine the overall effect of hospital volume on life expectancy after cancer surgery. STUDY DESIGN: We used a Markov decision analysis model to estimate life expectancy for patients undergoing resection for pancreatic, lung, or colon cancer. Model inputs included probabilities of operative mortality and longterm survival. For input data, we examined operative mortality (in-hospital or within 30 days) stratified by volume in over 400,000 patients undergoing resection for these three cancers using the national Medicare database (1994-1999). Risks of late mortality were abstracted from published studies (MEDLINE, 1966 to present) to model the effect of hospital volume on longterm survival. In analysis, we first calculated life expectancy for patients undergoing surgery at very low, low, medium, high, and very high volume hospitals. We then explored the effects of various regionalization strategies. RESULTS: Life expectancy increased steadily with hospital volume for all three cancers. Life expectancy after pancreatic cancer resection increased linearly with hospital volume: from 1.9 years at very low volume centers to 3.6 years at very high volume centers. For lung cancer, life expectancy ranged from 5.4 to 6.6 years. Increases in life expectancy for colon cancer were not as dramatic: from 6.8 at very low volume hospitals to 7.4 years at very high volume hospitals. Differences in life expectancy across volume strata were largely attributable to differences in longterm survival, not operative mortality. From a policy perspective, regionalizing surgery for colon cancer would produce the greatest overall life-expectancy gains, but it would require moving most patients. CONCLUSIONS: Patients aged 65 and older with pancreatic, lung, and colon cancer have substantially greater life expectancy after cancer resection at higher volume hospitals. Further work is needed to understand the mechanisms underlying differences in performance across hospitals in cancer care.

Adjusting surgical mortality rates for patient comorbidities: more harm than good?

Background. Studies of medical admissions have questioned the validity of using claims data to adjust for preexisting medical conditions (comorbidities), but the impact of using comorbidities from claims data to risk-adjust mortality rates for high-risk surgery is not well characterized. The purpose of this study was to evaluate the relationship between comorbidities and mortality in administrative data in surgical populations and identify better risk-adjustment methods. Methods. Using the national Medicare database (1994-1997), we identified admissions for elective abdominal aortic aneurysm repair (140,577) and pancreaticoduodenectomy (10,530). We calculated the relative risk of mortality (adjusted for age, sex, race, and admission acuity) for 5 chronic conditions that are known (from clinical series) to increase the risk of postoperative mortality and are commonly used in claims-based risk-adjustment models. To explore the potential value of alternative risk-adjustment strategies, we examined relationships between surgical mortality and comorbidities using diagnosis codes identified from previous admissions. Results. Overall, in-hospital mortality for elective abdominal aortic aneurysm (AAA) repair and pancreaticoduodenectomy were 5.1% and 10.4%, respectively. For both procedures, 3 of the 5 comorbidities were associated with decreased risk of mortality: prior myocardial infarction (MI) [RR = 0.38; 95% confidence interval (CI), 0.33-0.43 for AAA; RR = 0.38; 95% CI, 0.21-0.69 for pancreaticoduodenectomy), malignancy (RR = 0.67; 95% CI, 0.59-0.76 for AAA; RR = 0.74; 95% CI, 0.45-1.21 for pancreaticoduodenectomy], and diabetes (RR = 0.76; 95% CI, 0.64-0.84 for AAA; RR = 0.59; 95% CI, 0.49-0.69 for pancreaticoduodenectomy). Using comorbidities identified from prior admissions increased the mortality risk estimates for prior MI (RR = 1.22; 95% CI, 1.08-1.38 for AAA; RR = 0.80; 95% CI, 0.49-1.30 for pancreaticoduodenectomy) and diabetes (RR = 1.41; 95% CI, 1.25-1.59 for AAA; RR = 0.94; 95% CI, 0.78-1.14 for pancreaticoduodenectomy). Conclusions. Because comorbidities coded on the index admission appear protective, incorporating them in risk-adjustment models for studies comparing surgical performance may penalize providers for taking care of sicker patients. When available, comorbidity information from prior hospitalizations may be more useful for risk adjustment.

Hospital volume and surgical mortality in the United States.

BACKGROUND: Although numerous studies suggest that there is an inverse relation between hospital volume of surgical procedures and surgical mortality, the relative importance of hospital volume in various surgical procedures is disputed. METHODS: Using information from the national Medicare claims data base and the Nationwide Inpatient Sample, we examined the mortality associated with six different types of cardiovascular procedures and eight types of major cancer resections between 1994 and 1999 (total number of procedures, 2.5 million). Regression techniques were used to describe relations between hospital volume (total number of procedures performed per year) and mortality (in-hospital or within 30 days), with adjustment for characteristics of the patients. RESULTS: Mortality decreased as volume increased for all 14 types of procedures, but the relative importance of volume varied markedly according to the type of procedure. Absolute differences in adjusted mortality rates between very-low-volume hospitals and very-high-volume hospitals ranged from over 12 percent (for pancreatic resection, 16.3 percent vs. 3.8 percent) to only 0.2 percent (for carotid endarterectomy, 1.7 percent vs. 1.5 percent). The absolute differences in adjusted mortality rates between very-low-volume hospitals and very-high-volume hospitals were greater than 5 percent for esophagectomy and pneumonectomy, 2 to 5 percent for gastrectomy, cystectomy, repair of a nonruptured abdominal aneurysm, and replacement of an aortic or mitral valve, and less than 2 percent for coronary-artery bypass grafting, lower-extremity bypass, colectomy, lobectomy, and nephrectomy. CONCLUSIONS: In the absence of other information about the quality of surgery at the hospitals near them, Medicare patients undergoing selected cardiovascular or cancer procedures can significantly reduce their risk of operative death by selecting a high-volume hospital.