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Journal of Clinical Oncology, Vol 26, No 26 (September 10), 2008: pp. 4347-4352 © 2008 American Society of Clinical Oncology. DOI: 10.1200/JCO.2007.15.5291 Racial Composition of Hospitals: Effects on Surgery for Early-Stage Non–Small-Cell Lung Cancer
From the Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA Corresponding author: Christopher S. Lathan, MD, MS, MPH, Center for Outcomes and Policy Research, Dana-Farber Cancer Institute, 44 Binney St, 454-STE 21-24, Boston, MA 02115; e-mail: christopher_lathan{at}dfci.harvard.edu
Purpose Black patients undergo potentially curative surgery for early-stage lung cancer at a lower rate when compared with white patients. Our study examines the relationship between the percentage of black patients treated at a hospital to determine whether it affects the likelihood of obtaining cancer-directed surgery for patients with non–small-cell lung cancer (NSCLC).
Patients and Methods We examined claims data of Medicare-eligible patients with nonmetastatic NSCLC living in areas monitored by the Surveillance, Epidemiology, and End Results program between 1991 and 2001. Hospitals were categorized by the percentage of black patients seen:
Results Among 9,688 patients with NSCLC, 59% of white patients were seen at a hospital that had Conclusion Our study results indicate that patient and hospital characteristics are significant predictors of undergoing surgery for Medicare beneficiaries with localized lung cancer. Further examination of the role of the patient-, provider-, and hospital-level factors, in association with the decision to pursue surgical treatment of localized lung cancers, is needed.
Lung cancer is the leading cause of cancer mortality in the United States, with 157,000 deaths each year.1 During the past 40 years, there has been a decrease in lung cancer incidence and mortality in all races; however, a significant differential between black and white patients remains, with both incidence and mortality rates being highest in black men.2 Access to care, differences in biologic response to tobacco smoke, and patient preferences have all been suggested as possible contributors to the mortality gap in lung cancer.3-6 It has also been suggested that part of the racial disparity in early-stage lung cancer survival is related to the gap in the likelihood of obtaining potentially curative surgery.7 Previous studies have identified several patient-, physician-, and hospital-level factors associated with lower odds of undergoing potentially curative surgery for early-stage lung cancer, even when all patients had similar health insurance.6,7 Our own work has shown that even when patients had similar access to specialist care and showed a willingness to undergo invasive staging, physicians were less likely to offer potentially curative surgical procedures to black versus white patients.8 Other studies have evaluated physician-level factors, such as differential referral rates to surgeons and variation in surgeon specialty training. With respect to hospital-level characteristics, prior studies have focused on hospital volume and found that black patients were more likely to be seen in lower-volume hospitals.9-12 Other hospital-level factors, particularly racial composition of the hospital and hospital ownership status, should be considered. Studies of patients with head and neck cancer have found that county hospitals disproportionally treat patients with high rates of advanced-stage cancers. Hospitals that treat relatively large numbers of black patients have disproportionally high mortality rates after acute myocardial infarctions.13-17 This study was designed to determine the association of hospital-level characteristics on the acquisition of surgery for early-stage non–small-cell lung cancer (NSCLC) in a system where all patients have the same health insurance. Racial composition of the hospital has not been examined separately in lung cancer, but has been examined in other situations,13-16 and earlier studies have noted a separate and unequal medical system.18
Data Sources Patients from 11 tumor registries participating in the National Cancer Institute's Surveillance, Epidemiology and End Results (SEER) program were studied. The registries capture 97% of the incident cases,19 covering a nearly representative sample of 14% of the American population.20 The registries collect data on patient age, sex, race, ethnicity, cancer site, stage, histology, and date of death and diagnosis. Medicare claims, both inpatient and outpatient, have been linked to SEER for patients aged 65 and older.21 Hospital-level data associated with SEER-Medicare were obtained for the years 1996, 1998, 2000, and 2001 to obtain hospital-level variables.
Cohort Selection Patients were excluded if they had any prior cancers or if they were not admitted to a hospital any time after their diagnosis. We excluded patients who were enrolled in Medicare for end-stage renal disease or disability instead of age, patients whose diagnoses were made from autopsy or death certificates, patients with an unknown date of diagnosis, and those whose date of death differed by more than 3 months between SEER and Medicare. We also excluded patients if they did not have continuous Medicare enrollment (Part A and Part B) or if they were enrolled in a health maintenance organization at any time from 13 months prediagnosis (to use for comorbidity assessment) to death or last Medicare claim date (December 31, 2001).
Identification of Hospital Racial Composition
Definition of Surgery
Definition of Explanatory Variables
Statistical Methods
Patient Selection Our patient cohort included 9,688 patients diagnosed with NSCLC between 1991 and 1999. There were 7,688 white patients (79%) and 1,391 black patients (14%), along with 609 patients (6%) classified as "other." Table 1 shows the characteristics of this patient cohort. The most common histology was adenocarcinoma for white and "other" patients. For black patients, the most common histology was squamous cell carcinoma. Forty-seven percent (n = 4,563) of all patients had surgery, with a higher percentage of white patients undergoing surgery (49%) compared with patients defined as black (34%; P < .001). Crude differences by race were also apparent in socioeconomic status, with more patients of black or other race being in the lower socioeconomic status quintile and having state buy-in coverage. A higher percentage of black patients seemed to have slightly worse comorbid disease status when compared with white patients. Median age was 74 years for white patients and patients classified as other and 73 years for black patients. The results for individual registries are also listed in Table 1. Whereas white patients were well distributed throughout the 11 registries, black patients seemed to be concentrated in the Michigan, Georgia, and Los Angeles registries, and for this reason, we chose for our analysis those registries that had at least 5% black patients. The San Francisco registry was retained, but Connecticut, New Mexico, Seattle, Utah, Iowa, San Jose, and Hawaii were not part of the main analysis. All patients in the remaining registries were classified as urban by the SEER regional designation. Only three individual registries had more than 20% of their patients classified as rural: Iowa (45%), New Mexico (23%), and Utah (27%). Of the 610 hospitals in the study, 56% were classified as teaching hospitals, and 76% were classified as nonprofit.
Racial Distribution Across Hospitals Figure 1 illustrates the relationship between patient race and the racial composition of the hospital where the patients were treated for their lung cancer. Fifty-nine percent of white patients were treated at a hospital that had  8% black patients, whereas 60% of black patients were treated a hospital that had 30% black patients. Only 8% of white patients were treated in hospitals that had 30% black patients. Those patients classified as other had similar experiences to the white patients in this study.
Multivariable Analysis Using the percentage of black patients cared for in a hospital as a categoric independent variable, we performed a logistic regression analysis to predict likelihood of surgery. Race, age, sex, stage of disease, and state buy-in coverage (low income), as well as socioeconomic quintiles, patient volume quartiles, and registry sites, were all incorporated into the model (Table 2). The negative effect of the increasing percentage of black patients in a hospital remained significant in multivariable analysis, as did the negative effect of being seen in the lowest-volume quartile hospital. Being seen in a teaching hospital positively affected surgery. The other hospital level effect, such as nonprofit status, was not significant. Patient level effects, such as black race, increasing comorbid disease status, increasing age, low income, and having stage III disease, all had a significant negative effect on obtaining surgery. Patients were more likely to have had surgery if they had been seen in a teaching hospital, had higher socioeconomic status, or had stage II disease. Individual registries were also evaluated in the model and compared with the Los Angeles registry. Both Michigan and San Francisco had significant odds ratios that indicated that patients in those registries were less likely to obtain surgery. The Georgia registry was not significant. The most powerful effect in our model outside of stage of the cancer was registry.
For sensitivity purposes, further analyses were performed. Individual hospitals had different rates of surgery that varied crudely with the racial composition of the hospital. Figure 2 shows the rate of surgery for each hospital by racial composition. Each data point indicates a hospital, and the size of the point was determined by the hospital volume from the top to the lowest quartile. The R2 value was 0.027 for the fitted trend line.
Multivariable analysis was performed, and we restricted it to patients with stage I and II disease only. There was no change in the results (data not shown). We also performed the multivariable analysis with various interaction variables for each race combined with the hospital racial composition variable. None were significant, and thus data are not shown. In further sensitivity analysis, the complete cohort with 19,081 patients and all 11 registries was retained, and the multivariable analysis was repeated. There were no significant changes to the regression model.
Our study provides information about the association of hospital-level characteristics with the use of surgical procedures for Medicare beneficiaries with NSCLC. We found that receiving care at a teaching hospital or at hospitals with relatively larger percentages of white patients were associated with higher odds of patients undergoing surgical procedures. First, black and white patients seem to receive their lung cancer care at different hospitals. Most white patients were treated in hospitals that were predominantly white, whereas the majority of black patients were treated in hospitals that had a high number of black patients. Second, we found that the higher the percentage of black patients treated at a hospital, the less likely patients of either race were to undergo surgery for lung cancer. Lastly, in all hospitals, regardless of the racial mix, white patients were more likely to obtain surgery versus black patients, even when controlling for common confounders. Our model attempted to account for the major confounders, including patient volume, income, stage of disease, and SEER registry. The role of patient factors such as insurance was difficult to ascertain, as all patients were Medicare recipients, although those patients who were listed as low income had state buy-in for insurance and were also less likely to obtain surgery. This effect is independent of the patient race and hospital effect. Access to care has always been an important issue in discerning the cause of racial disparities in cancer treatment.26Our work looks at the effects of race in an equal access system, and recent published work has indicated that where patients obtain care can be an important factor contributing to racial disparities.14,16,27-29 The distribution of care demonstrated in Figure 1 is consistent with recent studies in the literature.30 Our analysis, using a multivariable regression model, demonstrated that the likelihood of obtaining surgery for early-stage lung cancer decreased with increasing percentage of black patients in a hospital. The model contained the traditional patient level covariates for stage, patient race, comorbid disease, socioeconomic status, SEER registry, and sex. It is of interest to note that black race remained a significant negative predictor of surgery for lung cancer, even with the hospital-level factors, racial composition, and patient volume in the model. This indicates that hospital racial composition affects care in addition to (not because of) individual patient race. The effect of volume of the hospital did seem to indicate that patients seen at smaller-volume hospitals also obtained surgery less than in patients seen in larger-volume hospitals. In all analyses, black race seemed to be a negative predictive factor in undergoing surgery for early-stage lung cancer, and this effect was similar in strength but was independent of the racial composition of the hospital. The effect of SEER registry is likely multifactorial, combining some elements of regional treatment patterns and proximity to major treatment centers. There are some limitations to our study. Our analytic database combines data from the SEER registries and Medicare claims. Medicare claims were not created for research and can suffer from coding error. In addition, comorbidity adjustment using administrative data might miss some relevant factors that physicians use in choosing which patients are likely to tolerate surgery24,31 and is not a proxy for performance status. Because our analysis was limited to Medicare-enrolled patients, we were unable to examine patients younger than 65 years of age. Patients in health maintenance organizations were excluded and may have different patterns of care. It is possible that the hospitals with higher numbers of black patients are safety net or county hospitals, but we were unable to discern hospital type in the SEER-Medicare database. Identifying patients based on hospital admission is imperfect but necessary, given the constraints of administrative databases like SEER-Medicare. Likewise, income estimates can also be imprecise, given the intimation of income via census tract data. We have shown that, regardless of race, patients are less likely to have surgery for nonmetastatic NSCLC if they are treated at hospitals with larger black populations. Furthermore, black patients seem to be treated for lung cancer more often at predominantly black hospitals. It is well known that black patients have surgery less often for NSCLC compared with white patients. Hospital-level characteristics, such as racial composition of the hospital, are often determined by regional resources. The reasons for the hospital-level effect of racial composition we observed are unknown but could be the result of historical treatment and referral patterns. Indeed, many safety net or county hospitals are large-volume teaching hospitals that traditionally provide care to the underserved. If the hospitals that treat the majority of black patients are overburdened and/or underfunded, then an exacerbation of the already present treatment disparities is bound to occur. Future research should focus on the specific characteristics of the hospitals that correspond to improved access to lung cancer care for all patients, regardless of race or ethnicity.
The author(s) indicated no potential conflicts of interest.
Conception and design: Christopher S. Lathan, Craig C. Earle Financial support: Craig C. Earle Collection and assembly of data: Bridget A. Neville Data analysis and interpretation: Christopher S. Lathan, Bridget A. Neville, Craig C. Earle Manuscript writing: Christopher S. Lathan, Bridget A. Neville, Craig C. Earle Final approval of manuscript: Christopher S. Lathan, Bridget A. Neville, Craig C. Earle
We thank Mary Beth Landrum, PhD, for her assistance with statistical analysis.
Supported by National Cancer Institute Grant No. KO1 CA124581-01A (C.S.L.) and the National Cancer Institute funded Program in Cancer Outcomes Research Training (Grant No. 5R25 CA092203-04). Presented in part at the 41st Annual Meeting of the American Society of Clinical Oncology, May 13-17, 2005, Orlando, FL. Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.
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Copyright © 2008 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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ABSTRACT
INTRODUCTION
8%, more than 8% to 29%, and 
