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Impact of Referral Patterns on the Use of Chemotherapy for Lung Cancer

From the Center for Outcomes and Policy Research, Department of Adult Oncology, and Department of Biostatistical Science, Dana-Farber Cancer Institute, and Program on the Economic Evaluation of Medical Technology, Center for Risk Analysis, Harvard School of Public Health, Boston, MA.

Address reprint requests to Craig C. Earle, MD, Center for Outcomes and Policy Research, Dana-Farber Cancer Center, 44 Binney St, Boston, MA 02115; email: craig_earle{at}dfci.harvard.edu

	ABSTRACT

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PURPOSE: To determine the extent to which unexplained variation in the use of chemotherapy for advanced lung cancer is due to access to oncologists’ services as opposed to treatment decisions made after seeing an oncologist.

METHODS: We performed a retrospective cohort study of 12,015 patients over age 65 diagnosed with metastatic lung cancer between 1991 and 1996 while living in one of 11 regions monitored by a Survival, Epidemiology, and End Results (SEER) tumor registry. Assessment by an oncologist and subsequent treatment with chemotherapy were determined by examining linked Medicare claims.

RESULTS: Of patients who did not receive chemotherapy, 36% were never assessed by a physician who provides chemotherapy. Patients living in certain areas, those diagnosed in more recent years, and those who received care in a teaching hospital were all more likely to see a cancer specialist. These factors were unrelated to subsequent treatment decisions, however. Conversely, age and comorbidity did not have a significant effect on whether a patient was seen by an oncologist, but they were associated with the likelihood of subsequently receiving chemotherapy. Black race, probably acting as a proxy for lower socioeconomic status, was associated with both a diminished likelihood of seeing a cancer specialist and subsequently receiving chemotherapy.

CONCLUSION: Nonmedical factors are important determinants of whether a lung cancer patient is seen by a physician who provides chemotherapy. After seeing such a physician, treatment decisions seem to be mostly explained by appropriate medical factors. Racial and socioeconomic disparities still exist at both steps, however. As therapeutic options expand, referring physicians must ensure that biases and barriers to care do not deprive patients of the opportunity to consider all of their treatment options.

	INTRODUCTION

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MANY STUDIES HAVE documented significant variations in medical practices and outcomes based on patient sex,¹ race,² socioeconomic status,^3,4 hospital type,⁵ and geographic location.^6,7 Moreover, recent data suggest that physicians can have race and sex biases⁸ and barriers to care⁹ that significantly influence their treatment recommendations. However, the contribution of physician referral to this practice variation has not been fully explored.

We and others have previously reported large unexplained variations in the use of palliative chemotherapy for advanced non–small-cell lung cancer (NSCLC) based on race, socioeconomic status, and geographic location,^10-14 despite no evidence of differential treatment effectiveness according to these factors.^15-17 Although this variation would be appropriate if it were due to patient preference or good clinical judgment, it would be unacceptable if it were due to referral bias or lack of access. For cancer patients to receive chemotherapy, they must have access to a physician who administers chemotherapy and they must make the decision that chemotherapy is appropriate for them.

Advanced lung cancer can serve as a good case study for referral and practice patterns. It is the leading cause of cancer death in North America, so the management issues surrounding metastatic disease will affect a large number of Americans this year.¹⁸ Although palliative chemotherapy has been shown to impart modest benefits in survival and quality of life,¹⁹ controversy surrounding the tradeoffs with toxicity still exists.²⁰ Therefore, decisions about chemotherapy may be particularly sensitive to the biases of referring and treating physicians.^21-24 In order to better understand the processes of care that determine whether a cancer patient receives treatment, we examined the factors related to assessment by an oncologist and those associated with subsequent therapy.

	METHODS

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Data Sources
We studied patients from the 11 tumor registries participating in the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) program. These registries capture about 97% of all incident cases,²⁵ covering a representative sample²⁶ of approximately 14% of the American population.²⁷ The Centers for Medicare and Medicaid Services (CMS, formerly the Health Care Financing Administration) Medicare database includes files through 1998 for inpatient and outpatient care, physician and laboratory billings, as well as bills for home health and hospice care. For patients age 65 and over captured by the SEER registries, 94% have been linked to Medicare.²⁸ Census-level sociodemographic data have also been linked to these cases.

Cohort Assembly
Our study sample consisted of all Medicare-eligible patients over age 65 who were diagnosed with stage IV NSCLC between January 1, 1991, and December 31, 1996. Patients were considered to have stage IV disease at presentation if metastases were documented by SEER abstractors within 2 months of diagnosis. Because only the month of diagnosis is recorded by SEER, we assumed all patients were diagnosed on the 15th day of each month. Patients were excluded if they had had any prior cancers. Sixteen percent of patients were excluded because they were enrolled in a health maintenance organization (HMO) at some time during the study period and, therefore, did not have complete treatment information. Cases were also excluded if the dates of diagnosis and death differed by more than 2 months in the SEER and Medicare databases or if the lung cancer was first identified at the time of death or autopsy.

Identification of Chemotherapy Utilization
We identified chemotherapy use from Medicare claims using the International Classification of Disease, 9th Revision (ICD-9), diagnostic code V58.1 and procedure code 9925, and the Diagnostic Related Group code 410 for chemotherapy administration in the inpatient setting. For the outpatient files and physician billing claims, CMS Common Procedure Coding System codes for chemotherapy administration (Q0083-Q0085, J7150, or J8999-J9999), Current Procedural Terminology codes (96,400, 96,408, 96,410, 96,412, 96,414, and 96,545), as well as the relevant revenue center codes (0331, 0332, and 0335) were also used where applicable. Patients were considered to have received chemotherapy if any of these codes were used at any time after the diagnosis of metastatic lung cancer.

Identification of Oncologists
We defined an oncologist as (1) any physician billing for the procedure of delivering chemotherapy to any stage IV NSCLC patient during the study period and (2) any physician identified as a subspecialist in medical oncology or hematology-oncology (CMS specialty codes 83 or 90). In this way, both noncertified physicians who practice oncology and board-certified oncologists would be captured. By definition, all patients receiving chemotherapy saw an oncologist, and we searched the billing records of patients who did not receive chemotherapy to determine whether they had ever seen such a physician. Each oncologist’s case volume was also calculated as the number of stage IV NSCLC patients seen during the study period. About 5% of patients who received chemotherapy were treated exclusively in the hospital, so their treatment could not be associated with a specific provider.

Definitions of Explanatory Variables
We categorized race and ethnicity into "white," consisting of non-Hispanic white patients, "black" non-Hispanic African-Americans, and "other." We calculated the Charlson comorbidity index^29,30 by examining the inpatient and outpatient diagnostic and procedure codes recorded in the year before the diagnosis of lung cancer.^31,32 Region-specific socioeconomic quintiles were developed based on the availability of information, according to the following hierarchy: (1) race- and age-specific median household wealth by census tract (86.5% of patients); (2) unadjusted median household income by census tract (9.7%); and (3) median household wealth by census tract or zip code (2.8%).³³ Patients were classified as having been treated at a teaching hospital if their record contained a charge for indirect medical education. To assess geographic variation, we divided the 77 Health Care Service Areas (HCSAs)³⁴ into quintiles based on rates of assessment by medical oncologists. HCSAs are groupings of metropolitan statistical areas defined by observed patient flow patterns in Medicare.³⁴ As such, they describe structures analogous to self-contained health care provider groups within Medicare. Patients were considered to live in an urban area if they lived in or adjacent to a metropolitan county with a population of at least 20,000. To explore other indications of whether the availability of oncologists determined either referral or treatment patterns, we calculated the density of oncologists as the number of oncologists in each HCSA divided by the number of lung cancer cases in that HCSA. We also used the area resource file (National Center for Health Workforce Information & Analysis, Department of Health and Human Services, Washington, DC) to determine the density of internal medicine subspecialists (which includes medical oncologists) and hospitals with oncology services. The results of analyses using these alternative methods of density estimation were not meaningfully different and, therefore, they are not reported.

Statistical Methods
Univariate comparisons were carried out using t tests for continuous variables and ² analyses for categorical variables. On the basis of the significant explanatory variables, we constructed multivariate logistic regression models to predict the likelihood of assessment by an oncologist and of subsequently receiving chemotherapy. We then created a two-stage model that first predicted the probability that a patient would be seen by an oncologist and then their subsequent odds of receiving chemotherapy, adjusted for the probability of oncologist assessment that was calculated in the first stage. Significant factors were identified through stepwise elimination, and interaction terms between these variables were further investigated if they had a ² P < .05. Models were constructed both with survival time as an independent variable and as a "landmark analysis" restricted to those patients who survived at least 3 months from diagnosis. All statistical analyses were performed with Statistical Analysis Software version 6.12 for UNIX (SAS Institute, Inc, Cary, NC).

	RESULTS

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Twelve thousand fifteen patients met eligibility criteria for the study (Table 1). The average age of the cohort was 73.5 years, and 60% were men. Most patients were white (84%), with black patients making up 8.6% of the group and other patients making up 7.7%. Twenty-eight percent of patients had at least one comorbid condition reported on a Medicare bill in the year before diagnosis, most commonly chronic obstructive pulmonary disease, followed by cardiovascular conditions.

Three thousand ninety-eight patients (26%) received chemotherapy at some time during their illness. Of the 8,917 patients (74%) who did not receive chemotherapy, 36% were never assessed by a physician who provides chemotherapy. For those assessed by an oncologist, the median time to an initial encounter was 19 days after diagnosis. The median time to starting chemotherapy was 30 days from diagnosis for treated patients. These physicians saw on average 14 eligible elderly patients presenting with stage IV NSCLC, ranging from one to 509, over the 6-year study period. Overall chemotherapy use in this population increased from 24.9% in 1991 to 30.3% in 1996. During this same time period, HMO enrollment steadily increased from 11% in 1991 to 24% in 1996.

Determinants of Oncologic Assessment
In Fig 1, the top (solid) line of each graph indicates the likelihood of seeing an oncologist and the bottom (broken) line shows the probability of subsequently receiving chemotherapy given that an oncologist was seen. Several factors were correlated with whether a patient saw an oncologist, but not subsequent treatment choice. There was a significant increase over time in the proportion of patients seen by an oncologist, ranging from 61% in 1991 to 79% in 1996 (P < .001). However, there was no commensurate rise over time in the proportion of assessed patients who subsequently received treatment (P = .48 for trend). Similarly, patients living in geographic areas in which the likelihood of seeing an oncologist was high did not have higher rates of chemotherapy utilization after such an encounter (P = .12). Patients receiving at least some of their care in a teaching hospital also had a much higher chance of seeing an oncologist than those who did not (81% v 65%, P < .001), yet their rates of chemotherapy use after such a visit were identical at 35% (P = .71). Women were more likely than men to see an oncologist (76% v 72%, P < .001). The density of oncologists in the geographic areas was not significantly associated with oncologic assessment or subsequent chemotherapy use.

View larger version (16K): [in this window] [in a new window]   Fig 1. Univariate relationships between patients with stage IV NSCLC being seen by an oncologist (diamonds, solid line) and subsequently being treated with chemotherapy given that they had seen an oncologist (squares, broken line). Geographic quintiles were defined based on increasing likelihood of seeing an oncologist. *P < .05 for trend.

Race and socioeconomic status were related both to the likelihood of seeing an oncologist and of subsequently receiving chemotherapy (Tables 2 and 3). Overall, white patients were significantly more likely to be assessed by an oncologist than nonwhite patients (74% v 70%, P < .001), and white patients of increasing socioeconomic status were more likely both to be seen by an oncologist and to receive chemotherapy. Black patients were significantly less likely to receive chemotherapy than patients of other racial groups. However, these racial patterns were not apparent in the lower socioeconomic strata, where nonwhite patients were more likely to be. There were no consistent socioeconomic trends among nonwhite patients.

	DISCUSSION

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The significant differences in rates of oncologist assessment by race, geographic location, and treatment in a teaching hospital are consistent with prior research.^35-38 However, once these patients were seen by an oncologist, we found that these nonmedical factors were mostly unrelated to treatment with chemotherapy, suggesting that the patterns of care are driven by patient access to an oncologist’s opinion. It is unclear whether these observations reflect referral decisions on the part of physicians making the diagnosis^8,39-42 or decisions made by patients not to seek an oncologic opinion.⁴³ Physician bias could manifest as either a lack of referral or the presentation of chemotherapy as a choice that is not worthwhile. On the other hand, fully informed patients may decline referral, and it is possible that patients with certain sociodemographic characteristics may be more likely to make such a decision. A recent study in breast cancer,⁴⁴ however, found that only 3.7% of patients did not wish to be referred to an oncologist, suggesting that patient preference is unlikely to entirely explain the observed referral patterns.

Although we found evidence of differential oncologist assessment related to nonmedical factors, rates of oncologist assessment were unassociated with several relevant clinical characteristics of patients. There was no evidence of differential assessment patterns on the basis of age or comorbidity. In contrast, these factors appropriately affected rates of chemotherapy use. Elderly patients less frequently meet standard physiologic criteria for treatment⁴⁵ and may be less likely to desire aggressive therapies.^13,14,46-53 Patients with metastatic NSCLC tend to have high levels of comorbidity due to concomitant smoking-related illness. It has been observed that patients with even moderately impaired ambulation, for example, have reduced survival and greatly increased toxicity from chemotherapy when compared with more mobile patients.^49,54-56 Although the number of comorbid conditions is not equivalent to functional status,⁵⁷ it has been associated with the likelihood of receiving treatment in other cancers.^49,58

The association between the main outcomes and patient sex is intriguing. Despite higher rates of oncologist assessment, women were less likely to receive chemotherapy after controlling for other factors. It is unknown whether this represents a preference for supportive care among this group or physician bias. At least by self-report, lung cancer physicians do not place much importance on sex when making treatment recommendations.²³

Higher socioeconomic status was associated with both increased oncologist assessment and increased chemotherapy use among referred patients. As we have observed previously,¹⁵ at least part of this is attributable to the longer survival of wealthier patients, which allows more time for these things to occur. However, it does not explain all of the association, and either better-educated and informed patients were more often desiring intervention, there was physician bias, or both. Examination of the relationship between race and socioeconomic status indicates that socioeconomic status is likely the most important feature. Because most nonwhite patients were in lower socioeconomic groups, their numbers decreased in the higher socioeconomic strata, making the estimation of rates less certain. However, because race was known at the patient level, whereas socioeconomic status was known only at the level of the census tract, race was more strongly associated with outcome in multivariate models. In this case, race was probably serving somewhat as a proxy for socioeconomic status.

There must be caution in generalizing from our results: linked SEER-Medicare files only capture patients over 65 years of age; administrative data do not contain detailed clinical information, and methods for comorbidity adjustment are still undergoing validation. Our identification of patients treated in teaching hospitals did not ensure that the decision to refer to an oncologist or to use chemotherapy was made in an academic setting, and chemotherapy identification relied on Medicare procedure codes and, therefore, could be affected by secular trends in billing completeness.^28,59-61 Additionally, our method for defining oncologists may have missed some practitioners who are solely hospital-based, and some of the physicians identified may not have been board-certified oncologists. However, we believe the functional definition of an oncologist as a physician who billed for chemotherapy administration has a great deal of face validity. Lastly, 16% of patients were excluded because they were enrolled in an HMO during part of the study. They tended to be more urban and to have a higher socioeconomic status than those included, and there are data suggesting that the practice patterns in HMOs can differ from those in a fee-for service setting.^58,60,62 Consequently, the increase in chemotherapy use over time may have been underestimated because of the coincident increase in HMO enrollment.

The number of therapeutic options for many cancers is expanding rapidly, making treatment decisions more complex. The increasing use of palliative chemotherapy for lung cancer observed in this study seems to be most strongly related to increasing proportions of these patients being seen by oncologists. Chemotherapy or supportive care can be appropriate choices in different clinical situations, and our data suggest that oncologists do a good job of supporting these choices appropriately. Further research, such as that sponsored by the National Cancer Institute in their Cancer Care Outcomes Research and Surveillance Consortium, is needed to try to discern the reasons for disparities that still exist, however. In the meantime, referring physicians must be vigilant not to allow biases or restricted access to deprive patients of the opportunity to consider all of their treatment options.

	ACKNOWLEDGMENTS

 
Supported in part by grant no. CA 72663 from the National Institutes of Health, Bethesda, MD.

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Submitted May 30, 2001; accepted December 11, 2001.

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