Originally published as JCO Early Release 10.1200/JCO.2004.00.1297 on November 21 2005

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Insurance Status and the Use of Guideline Therapy in the Treatment of Selected Cancers

From the Division of Cancer Control and Population Sciences; Cancer Therapy Evaluation Program, National Cancer Institute, National Institutes of Health, Bethesda; and Information Management Services, Silver Spring, MD.

Address reprint requests to Linda C. Harlan, PhD, National Cancer Institute/Applied Research Program, Executive Plaza North Rm 4005, 6130 Executive Blvd MSC 7344, Bethesda, MD 20892-7344; e-mail: lh50w{at}nih.gov

	ABSTRACT

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Authors' Disclosures of... REFERENCES

 
PURPOSE: This study estimates the impact of type of insurance coverage on the receipt of guideline therapy in a population-based sample of cancer patients treated in the community.

PATIENTS AND METHODS: Patients (n = 7,134) from the National Cancer Institute's Patterns of Care studies who were newly diagnosed with 11 different types of cancer were analyzed. The definition of guideline therapy was based on the National Comprehensive Cancer Network treatment recommendations. Insurance status was categorized as a mutually exclusive hierarchical variable (no insurance, any private insurance, any Medicaid, Medicare only, and all other). Multivariate analyses were used to examine the association between insurance and receipt of guideline therapy.

RESULTS: Adjusting for clinical and nonclinical variables, insurance status was a modest, although statistically significant, determinant of receipt of guideline therapy, with 65% of the privately insured patients receiving recommended therapy compared with 60% of patients with Medicaid. Seventy percent of the uninsured patients received guideline therapy, which was nonsignificantly different compared with private insurance. When stratified by race, insurance was a statistically significant predictor of the receipt of guideline therapy only for non-Hispanic blacks.

CONCLUSION: Overall, levels of guideline treatment were lower than expected and particularly low for patients with Medicaid or Medicare only. The use of guideline therapy for ovarian and cervical cancer patients and for patients with rectal cancers was unrelated to type of insurance. Of particular concern is the significantly lower use of guideline therapy for non-Hispanic black patients with Medicaid. After adjusting for other factors, only half of these patients received guideline therapy.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Authors' Disclosures of... REFERENCES

 
Significant improvements in treatment and survival after the diagnosis of cancer have been made over the last decade.^[1] However, disparities in cancer outcomes and the receipt of guideline cancer-related health care persist. Disparities have been described in terms of racial and ethnic status as well as economic, geographic (rural v urban), educational, cultural, and age-related factors.^[2-4] Health insurance coverage often is identified as a proximal factor that strongly influences access to appropriate medical care.^[5] Insurance coverage has been consistently shown to be strongly associated with the receipt of appropriate cancer screening services. In addition, the President's Cancer Panel, legislatively mandated in 1971, described the lack of health insurance as a Catch 22 for those low-income individuals who are able to obtain cancer screening tests from community health centers but are unable to afford follow-up diagnostic or treatment services.^[6] The lack of health insurance coverage also has been shown to be associated with lower average levels of expenditures on medical treatment among cancer patients, a finding that suggests that cancer patients lacking health insurance may be less likely to receive all types of appropriate care.^[7]

However, evidence on the association of health insurance with receipt of appropriate cancer treatment has been inconsistent. In some studies, insurance has been reported as an independent factor related to the receipt of guideline therapy even after adjusting for age and racial or ethnic group.^[8-10] Studies that have examined treatment patterns across different types of private insurance, such as fee for service (FFS) compared with health maintenance organizations (HMO), have not found significant differences in use of guideline therapy.^[11,12] However, one study found that, at the individual plan level, rates of guideline breast cancer therapy were significantly higher in some HMOs than in the local FFS settings, whereas the converse was found in other plans.^[13]

The main focus of this study was to investigate whether being uninsured or the type of insurance had an impact on the receipt of guideline therapy. We selected guideline therapy as a surrogate measure of access and quality of care and a standard that should be provided to the majority of the cancer patients. We hypothesized that patients who had private insurance would receive guideline therapy more often than patients with no insurance or Medicaid or Medicare only. This is the first study that examines insurance status and use of guideline therapy in a population-based sample of cancer patients treated in community settings.

	PATIENTS AND METHODS

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Authors' Disclosures of... REFERENCES

 
The National Cancer Institute's (NCI) Surveillance, Epidemiology, and End Results (SEER) Program collects data on the occurrence of cancer in defined populations. Detailed information on demographics, tumor characteristics, and therapy are abstracted, and the registries maintain active follow-up of patients. Data from the SEER program are generally representative of the US cancer incidence and mortality, although the SEER populations tend to be slightly more urban and have a greater number of foreign-born individuals than the US population overall.^[14]

The primary source of the SEER data is hospital medical records, pathology reports, and/or outpatient surgical center reports. However, this information does not provide a complete picture of cancer treatment. Information on adjuvant therapy is often unavailable or incomplete in hospital medical records because it is provided in an outpatient setting. The NCI has an ongoing program of Patterns of Care (POC) studies to supplement the SEER data. Each year, the POC studies select certain cancer sites and sample patients from within the SEER population to examine the provision of adjuvant therapies.^[15]

Selection of Patients
This POC analysis examined individuals aged 20 years or older who were newly diagnosed with cancer between 1995 and 1999. Patients with a previous diagnosis of cancer, other than nonmelanoma skin cancer, and patients diagnosed simultaneously with two primary cancers were ineligible because either might alter the selection of initial therapy. Patients diagnosed on autopsy or on the death certificate only also were excluded. A random sample of patients within each SEER registry was selected from all eligible patients by strata, which was defined by cancer site and race or ethnicity and, when appropriate, by age, sex, and stage. This analysis includes cancer patients from 5 years of POC studies. These patients were diagnosed with the following: early-stage breast cancer, stage II or III colorectal cancer, stage I, II, or III melanoma, or all stages of invasive bladder cancers diagnosed in 1995; all stages of lung or ovarian cancer or stage I, II, or III melanoma diagnosed in 1996; cervical cancer diagnosed in 1997; cancers of the pancreas and corpus uteri diagnosed in 1998; or testicular cancer diagnosed in 1999. A total of 7,889 patients were included in this analysis. Patients who were participants in clinical trials (n = 237), whose insurance status was unknown (n = 333), or whose cancer was not staged (n = 185) were excluded from the current analyses. The final sample included 7,134 patients.

Abstracting the Data
Each year before the study began, the abstractor from each SEER registry who was primarily responsible for the study attended a central training session. This training was intended to ensure consistency and comparability of abstracting and coding across all participating registries.

The abstractors reviewed hospital medical records, records from surgical centers, and unified records from HMOs to verify tumor characteristics, treatment provided, demographic information, and insurance status. All comorbidities listed in the record at the time of treatment were recorded on the abstract. One medical records technician coded the comorbidities centrally into International Classification of Diseases (9th revision, clinical modification) for all years of the study. The comorbidities were then analyzed using the Charlson Comorbidity Index Score.^[16-18]

The clinical factors included in these analyses were cancer site, stage at diagnosis, whether lymph nodes were sampled and the number of positive nodes, and comorbidities. Demographic factors included age, race/ethnicity, sex, marital status, and geographic location. Individual education level was not available in these data. Therefore, we estimated a level of educational attainment for each patient by determining the patient's area of residence at the time of diagnosis and assigning the percentage of individuals aged 25 years and older who had at least a high school diploma and resided within that census tract.

Hospital bed size and the presence of a residency training program were used to reflect health system factors. Using data from the American Hospital Guidebook,^[19] the SEER registries coded bed size and residency program for the hospital where the patient was treated. If the patient was not hospitalized, codes were used to identify that the patient was treated at a physician's office or outpatient facility.

Insurance status at the time of diagnosis was collected from the hospital, surgical center, or radiation facility. Patients were defined as having private insurance if they had FFS, HMO, independent physician association, or managed care insurance and included patients with Medicare plus any private coverage. Patients were classified as having Medicaid if they had Medicaid plus Medicare or Medicaid without supplemental private insurance. If patients had Medicare only with no supplemental insurance, they were categorized as having Medicare. Patients with traditional Medicare coverage only are responsible for copayments of 20% for nonhospital-based (part B) services in addition to expenses for prescription medications and may, therefore, have less access to specialty cancer care.^[20] All other insurance types, including Civilian Health and Medical Program of the Uniformed Services Veterans Affairs, were categorized as other. If patients had no insurance, they were categorized as uninsured.

Verifying Adjuvant Therapy
Because much adjuvant therapy is provided in an outpatient setting, the treating physicians were contacted. Each patient's treating physician was asked to verify whether the patient participated in a treatment clinical trial; whether he or she had received radiation therapy, chemotherapy, hormonal therapy, or other adjuvant therapy; and which specific agents were administered. Only initial therapy provided to the patient was collected. This is generally any treatment planned or administered in the first 4 months after diagnosis and does not include treatment for recurrence or progression of the disease. We asked the physician to provide the name of the agent administered and whether radiation was administered. The physician was also asked whether the patient refused any of these therapies. We believe that, for medical and legal reasons, the physician would have noted in the patient's medical record the recommendation for and refusal of therapy. We did not collect information about dosage or duration of treatments. The physician also was asked to provide the names and addresses of other physicians who might have provided treatment to the patient. These physicians were contacted to determine whether they provided adjuvant therapy to the patient.

Assessing Receipt of Guideline Therapy
We examined the association between receipt of guideline therapy, based on the National Comprehensive Cancer Network (NCCN) treatment recommendations, and insurance type.^[21] Patients were restricted to the common histologies covered by NCCN guidelines. We selected these guidelines because they could be considered a standard of care. Although we used 2002 guidelines, at the level of measurement available for this study, the 2002 NCCN guidelines differ only modestly from NCI or other clinical guidelines already in effect by the mid-1990s (see Discussion). These guidelines should be applied equally to all groups. Using these guidelines, three independent reviewers with credentials in oncology, nursing, and epidemiology classified patients as having either received or not received guideline cancer treatment. Patients who refused therapies (n = 48) were categorized as having received guideline therapy in recognition of the fact that patients may have a legitimate preference to balance the toxicity of treatment against sometimes modest expected survival gains. We analyzed guideline therapy using guidelines as the minimum treatment; additional therapy was allowed. We performed a second analysis in which the guidelines were the only treatment allowed and additional therapy was considered overtreatment. The second definition decreased the percentage of patients receiving guideline therapy by approximately 4% but did not change the relationship between insurance and guideline therapy. Therefore, we are presenting only the data using the definition that allows for additional treatment beyond the guidelines. We did not know the dose or duration of radiation or chemotherapy and only examine whether or not therapy was administered.

Performing the Analyses
Bivariate assessment of the association between therapy and clinical and nonclinical variables was performed to determine which factors were associated with the receipt of guideline therapy. Multivariate analyses were then performed to examine the use of guideline therapy after adjusting for clinical and nonclinical factors. Variables were sequentially added to the models in the following manner: (1) insurance alone; (2) cancer site; (3) clinical factors, such as stage at diagnosis (stage 0/I, II, III, or IV), number of positive nodes (0, 1 to 3, 4 or more, or unknown), and Charlson Score (0 or > 0); (4) health system factors, such as residential training program (yes or no) and bed size (< 200, 200 to 299, 300 to 399, 400 to 499, or 500 beds); and (5) demographic factors, such as sex (male or female), age at diagnosis (< 50, 50 to 64, or 65 years), geographic region (SEER registries), race and ethnicity (non-Hispanic white, non-Hispanic black, or Hispanic), marital status at diagnosis (married or not married), and receipt of high school diploma (< 75%, 75% to < 90%, or 90%). We also performed regression analysis stratified by racial and ethnic group. All tests were two sided. We present the percentages of patients receiving guideline therapy adjusting for the independent variables. These adjusted percentages were the estimated average marginal predictions (marginalizing over the distribution of the covariates in the population used in each model).^[22]

All estimates were weighted to reflect the population from which the sample was drawn. The sample weights, calculated as the inverse of the sampling proportion for each sampling stratum, were used to obtain estimates that are representative of all eligible patients with cancer of the same site in the study areas. We used the statistical software SUDAAN (Research Triangle Institute, Research Triangle, NC) for all analyses.^[23] This software allows for the use of sample weights and adjusts for the complex sample design.

	RESULTS

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The number and weighted percentage of patients by clinical characteristics, sociodemographic factors, and treatment facility are listed in [Table 1]. Although breast cancer patients represented the largest number of patients by cancer site, when weighted to the SEER population, lung cancer patients represented the largest percentage. Most of the patients (41%) were diagnosed with stage 0 or I disease.

We found that patients who were less than 50 years old, Hispanic, or not married were more often uninsured. Uninsured patients tended to be from census tracts with lower educational attainment than patients with private insurance.

Surprisingly, a statistically nonsignificant larger percentage of patients who had no insurance (72%) received guideline therapy compared with patients with private insurance (67%). All other categories of insured patients received guideline therapy at a lower percentage ([Table 3]). Patients with Medicaid were least likely to receive guideline therapy, even compared with patients with Medicare alone. Patients with stage II or III disease and on Medicaid received guideline therapy less than half of the time. Except for non-Hispanic blacks with Medicare alone, non-Hispanic white patients received guideline therapy more often than non-Hispanic blacks and Hispanics within the same insurance type.

We also found that the influence of age persisted after adjusting for all other variables in the model. There was an inverse relationship between age at diagnosis and receipt of guideline therapy; patients who were younger than 65 years old were significantly more likely to receive guideline therapy, even after adjusting for variables including comorbidities.

	DISCUSSION

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Authors' Disclosures of... REFERENCES

 
To our knowledge, this is the first population-based study that examines the effect of insurance on receipt of guideline therapy for multiple cancer sites. After adjusting for clinical and nonclinical variables, insurance type emerged as a significant determinant of receipt of guideline therapy. Sixty-five percent of patients who were privately insured and 70% of patients who were uninsured received guideline cancer therapy, which is a statistically nonsignificant difference. Patients with Medicaid, Medicare only, or the other types of insurance were less likely than privately insured patients to receive guideline therapy. The 5% difference between private insurance and Medicaid and Medicare is modest but involves a substantial number of individuals when one considers the size of the treated population. Similar levels of adherence to guideline care have been reported for other conditions. For example, a recent study of quality of care for common conditions reported that adherence to screening recommendations was 52% and adherence to follow-up care recommendations was 58%.^[24]

The reasons why uninsured individuals have a higher receipt of guideline therapy are uncertain. Misclassification is a possibility. However, medical care facilities have a financial incentive to obtain the insurance information, and patients with unknown insurance status were excluded from this analysis. The picture that emerges of these uninsured individuals is that of a younger, healthier population diagnosed at earlier stages of disease. This may help to explain what we found. Overall, patients with the earliest stages of disease also have more treatment options within the guidelines. Younger patients with fewer comorbid conditions are more likely to be treated than older patients with more health-related problems. Although the higher use of guideline therapy remained after adjusting for these variables, it is likely that an unmeasured variable, such as income, had an impact on these findings. However, if the uninsured are indeed younger, more fit, and diagnosed at an earlier stage compared with other groups of patients, there would be an impetus within the health care profession to be certain they received guideline care, especially if they were perceived to be curative. Physicians, nurses, and other health professionals often do not charge for their services in cases like this and likely feel an obligation to find care for this uninsured individual.

The percentage of patients receiving guideline therapy varied by cancer site. This did not seem to be related to use of the current NCCN guidelines applied to patients diagnosed previously. More than 90% of patients with testicular cancer received guideline therapy regardless of their insurance status. This is a disease site where acceptance of the guidelines and the potential for cure seem to be clearly disseminated into clinical practice. Similarly, a large percentage of patients with bladder cancer received guideline therapy. These high rates of receipt remain even after adjusting for clinical and nonclinical factors. However, only approximately 30% of women with cervical cancer received guideline therapy, and this did not vary substantially by insurance type. Although the current NCCN guidelines recommend the use of radiation plus cisplatin for patients with positive nodes, excluding the requirement for cisplatin increased guideline therapy by only 3% for women with Medicare insurance alone and approximately 6% for patients with other insurance types. The primary reason for not meeting guideline therapy was the lack of lymph node sampling. This was also the primary reason ovarian cancer patients had similar rates of guideline therapy. Rectal cancer patients did not fare much better with respect to guideline therapy. However, this was a result of the failure to receive radiation. The 1990 National Institutes of Health (NIH) Consensus Development Conference also recommended radiation for rectal cancer patients (http://consensus.nih.gov/cons/079/079_intro.htm). The use of radiation has been shown to significantly reduces locoregional recurrence from 13% to 8% over 5 years but without an associated increase in survival.^[25] Perhaps physicians are deciding the benefits do not outweigh the risks and adverse effects on quality of life associated with radiation.

Other guideline changes seemed minimal and did not account for the lack of guideline therapy. Breast cancer patients administered guideline therapy as recommended by NCCN should have received chemotherapy if they had node-positive tumors 3 cm or larger despite having receptor-positive tumors. Although the 1985 NIH Consensus Development Conference guidelines recommended only tamoxifen for postmenopausal women with node-positive and estrogen receptor–positive tumors, the 1988 Clinical Announcement recommended chemotherapy for early-stage breast cancer patients with negative nodes if their tumors were greater than 3 cm, irrespective of their estrogen receptor status.^[26] Therefore, it seems likely that by 1995, the year these patients were diagnosed, physicians would be providing chemotherapy for women with positive nodes and tumors 3 cm or larger. Only 24 women (1%) with early-stage breast cancer did not meet this guideline for treatment. The NCCN guidelines also recommend that women with four or more positive lymph nodes or tumors 5 cm or greater receive radiation even though they had a mastectomy. The 2000 NIH Consensus Development Conference made similar recommendations (http://consensus.nih.gov/cons/114/114_statement.htm). Removing these requirements only moves 28 women (1.3% weighted) with four or more positive nodes or tumors 5 cm or greater having mastectomies who did not receive radiation into the category of having received guideline therapy.

This study had several limitations. We do not know the quality of the surgery or the adequacy of the radiation and chemotherapy. We do not know the dose or cycles of radiation or chemotherapy administered. Data on insurance status were collected from hospitals, hospital outpatient departments, and freestanding surgical and radiation centers. Patients who were never treated in one of those facilities (primarily patients who did not have surgery or radiation) often had missing insurance information and were excluded from this study. This is likely to produce a more conservative estimate of the difference between patients receiving and not receiving guideline therapy because, for most of these cancers, surgery or radiation would be part of guideline therapy. Our definition of private insurance is unable to account for the impact of differences in coverage provided by policies. This may significantly influence the choice of treatments. Although we adjusted for comorbidities using the Charlson Score, we were unable to adjust for the severity of the condition. Severity of disease is likely to vary by age and racial or ethnic group. Patients with Medicaid or Medicare only were less likely to receive guideline therapy. Given the small percentage of patients who were uninsured, we believe that a substantial number of patients moved from the uninsured category to Medicaid when they were diagnosed with cancer. We cannot say what the result would have been if they were uninsured.

Despite the limitations, our overall results are consistent with previous studies that have found that private insurance or Medicare plus private supplemental insurance is associated with an increase in the use of recommended cancer therapy.^[27-30] However, these studies have been limited to one cancer site or evaluation of a specific therapy. Several large studies have found that lack of insurance coverage, Medicare without supplemental insurance, and Medicaid are associated with decreased rates of cancer screening.^[31-36]

In addition to health insurance, we found other factors to be related to the receipt of recommended treatment. Compared with patients who were not married, married individuals were more often privately insured, and a larger percentage received guideline therapy. Stage was also associated with the receipt of recommended treatment, indicating that the complexity of treatment may be a determining factor in whether guideline therapy is received. More patients with stage I or IV disease received recommended therapy compared with patients with stage II or III disease. After adjusting for clinical and nonclinical factors, significantly more patients with stage IV disease and significantly fewer patients with stage II disease received guideline therapy compared with all other stages. Guidelines for the treatment of stage I disease tend to be well standardized and less aggressive than the guidelines for treatment of stage II and III disease. A wide range of interventions are accepted for stage IV disease, and this increases the likelihood that a patient with stage IV disease will receive guideline therapy. Treatments for stage II and III disease are generally more complex, and there may be less consensus in the community about the appropriateness of the guidelines. However, the differences in use of guidelines by stage of disease could not be explained by greater changes in the current guidelines for stage II disease. When we examined the reasons why guidelines were not met, the reasons were not related to guideline changes that influenced stage II treatment only. Perhaps physicians are reluctant to prescribe the intensive guideline treatments for the earlier stage disease.

Consistent with the results of other studies,^[37,38] we found the receipt of recommended treatment to be inversely related to age, even after adjusting for comorbidity and insurance, indicating that treating physicians may believe the adverse complications outweigh the benefits of guideline therapy. Interestingly, after adjusting for health insurance status and other factors, we did not find a statistically significant relationship between the receipt of recommended treatment for all cancer sites combined and the presence of a residency training program or hospital bed size. However, we were unable to measure the volume of treatments by hospitals, and this may be associated with the use of guideline therapy, especially in certain cancer sites.

Health insurance may be a proxy for other socioeconomic factors that influence the receipt of guideline therapy. Non-Hispanic blacks with Medicaid, which indicates lower incomes, have a significantly lower rate of guideline therapy compared with non-Hispanic blacks with Medicare only, private insurance, or no insurance. Several studies have documented poorer survival among patients with lower socioeconomic status.^[8,39-41] Treatment may also be associated with other factors, such as access to specialty care providers and regional practice variation.^[42,43]

Insurance coverage is an important component of access to cancer preventive, diagnostic, and treatment services. Comprehensive programs that provide a continuous and improved coverage for the Medicaid and Medicare populations without supplemental insurance may yield substantial benefits by decreasing late-stage diagnosis and increasing the use of guideline therapy, which would result in improving survival and quality of life. However, the data presented here also indicate that providing private health insurance to all is only one of several factors that must be addressed to ensure that optimal cancer treatment is provided to all cancer patients by the US health care delivery system.

	Authors' Disclosures of Potential Conflicts of Interest

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Authors' Disclosures of... REFERENCES

 
The authors indicated no potential conflicts of interest.

	NOTES

	REFERENCES

TOP ABSTRACT INTRODUCTION PATIENTS AND METHODS RESULTS DISCUSSION Authors' Disclosures of... REFERENCES

 
1. von Eschenbach A: The Nation's Investment in Cancer Research. Bethesda, MD, National Institute of Health, National Cancer Institute, 2003, pp 108

2. Trans-HHS Cancer Health Disparities Progress Review Group: Making Cancer Health Disparities History. Washington, DC, Department of Health and Human Services, 2004, pp 118

3. Shavers VL, Brown ML: Racial and ethnic disparities in the receipt of cancer treatment. J Natl Cancer Inst 94:334-357, 2002[Abstract/Free Full Text]

4. Smedley BD, Stith AY, Nelson AR: Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC, The National Academies Press, 2003

5. Committee on the Consequences of Uninsurance, Institute of Medicine of The National Academies: Hidden Cost, Value Lost: Uninsurance in America. Washington, DC, The National Academies Press, 2003

6. President's Cancer Panel: Meeting summary: President's Cancer Panel—Improving cancer care for all: Real people, real problems—Why don't all Americans get the best available cancer care? Washington, DC, March 8-9, 2001

7. Thorpe KE, Howard D: Health insurance and spending among cancer patients. Health Aff (Millwood) W3-189–W3-98, 2003 (suppl)

8. Bradley CJ, Given CW, Roberts C: Race, socioeconomic status, and breast cancer treatment and survival. J Natl Cancer Inst 94:490-496, 2002[Abstract/Free Full Text]

9. Janes RH Jr, Niederhuber JE, Chmiel JS, et al: National patterns of care for pancreatic cancer: Results of a survey by the Commission on Cancer. Ann Surg 223:261-272, 1996[CrossRef][Medline]

10. Kotwall C, Covington D, Churchill P, et al: Breast conservation surgery for breast cancer at a regional medical center. Am J Surg 176:510-514, 1998[CrossRef][Medline]

11. Lee-Feldstein A, Feldstein PJ, Buchmueller T, et al: The relationship of HMOs, health insurance, and delivery systems to breast cancer outcomes. Med Care 38:705-718, 2000[CrossRef][Medline]

12. Vernon SW, Heckel V, Jackson GL: Medical outcomes of care for breast cancer among health maintenance organization and fee-for-service patients. Clin Cancer Res 1:179-184, 1995[Abstract]

13. Riley GF, Potosky AL, Klabunde CN, et al: Stage at diagnosis and treatment patterns among older women with breast cancer: An HMO and fee-for-service comparison. JAMA 281:720-726, 1999[Abstract/Free Full Text]

14. Surveillance, Epidemiology, and End Results: Characteristics of the SEER Population Compared With the Total United States Population. Rockville, MD, National Cancer Institute, National Institutes of Health, 2003

15. National Cancer Institute: Patterns of Care/Quality of Care Studies. Bethesda, MD, Division of Cancer Control and Population Sciences and Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, 2004. http://healthservices.cancer.gov/surveys/poc/

16. Charlson ME, Pompei P, Ales KL, et al: A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 40:373-383, 1987[CrossRef][Medline]

17. Deyo RA, Cherkin DC, Ciol MA: Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 45:613-619, 1992[CrossRef][Medline]

18. Romano PS, Roos LL, Jollis JG: Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: Differing perspectives. J Clin Epidemiol 46:1075-1079; discussion 1081-1090, 1993

19. American Hospital Association.American Hospital Association Guide to the Health Care Field. Chicago, IL, American Hospital Association, 2000

20. Centers for Medicare and Medicaid Services: Medicare and You (Physician Edition). Baltimore, MD, United States Department of Health and Human Services, 2004

21. National Comprehensive Cancer Network: Guidelines for Treatment of Cancer by Site. Jenkintown, PA, National Comprehensive Cancer Network, 2003

22. Korn EL, Graubard BI: Analysis of Health Surveys. Hoboken, NJ, John Wiley and Sons, Inc, 1999

23. Research Triangle Institute: SUDAAN. Research Triangle, NC, Research Triangle Institute, 2004

24. McGlynn EA, Asch SM, Adams J, et al: The quality of health care delivered to adults in the United States. N Engl J Med 348:2635-2645, 2003[Abstract/Free Full Text]

25. Wolmark N, Wieand HS, Hyams DM, et al: Randomized trial of postoperative adjuvant chemotherapy with or without radiotherapy for carcinoma of the rectum: National Surgical Adjuvant Breast and Bowel Project Protocol R-02. J Natl Cancer Inst 92:388-396, 2000[Abstract/Free Full Text]

26. National Cancer Institute: Clinical alert from the National Cancer Institute. Breast Cancer Res Treat 12:3-5, 1988

27. Janes GR, Blackman DK, Bolen JC, et al: Surveillance for use of preventive health-care services by older adults, 1995-1997. MMWR CDC Surveill Summ 48:51-88, 1999[Medline]

28. Muss HB, Hunter CP, Wesley M, et al: Treatment plans for black and white women with stage II node-positive breast cancer: The National Cancer Institute Black/White Cancer Survival Study experience. Cancer 70:2460-2467, 1992[CrossRef][Medline]

29. Van Eenwyk J, Campo JS, Ossiander EM: Socioeconomic and demographic disparities in treatment for carcinomas of the colon and rectum. Cancer 95:39-46, 2002[CrossRef][Medline]

30. Young WW, Marks SM, Kohler SA, et al: Dissemination of clinical results: Mastectomy versus lumpectomy and radiation therapy. Med Care 34:1003-1017, 1996[CrossRef][Medline]

31. Hsia J, Kemper E, Kiefe C, et al: The importance of health insurance as a determinant of cancer screening: Evidence from the Women's Health Initiative. Prev Med 31:261-270, 2000[CrossRef][Medline]

32. DeVoe JE, Fryer GE, Phillips R, et al: Receipt of preventive care among adults: Insurance status and usual source of care. Am J Public Health 93:786-791, 2003[Abstract/Free Full Text]

33. Bednarek HL, Schone BS: Variation in preventive service use among the insured and uninsured: Does length of time without coverage matter? J Health Care Poor Underserved 14:403-419, 2003[Medline]

34. Friedman C, Ahmed F, Franks A, et al: Association between health insurance coverage of office visit and cancer screening among women. Med Care 40:1060-1067, 2002[CrossRef][Medline]

35. Potosky AL, Breen N, Graubard BI, et al: The association between health care coverage and the use of cancer screening tests: Results from the 1992 National Health Interview Survey. Med Care 36:257-270, 1998[CrossRef][Medline]

36. Zapka JG, Puleo E, Vickers-Lahti M, et al: Healthcare system factors and colorectal cancer screening. Am J Prev Med 23:28-35, 2002[CrossRef][Medline]

37. Schrag D, Cramer LD, Bach PB, et al: Age and adjuvant chemotherapy use after surgery for stage III colon cancer. J Natl Cancer Inst 93:850-857, 2001[Abstract/Free Full Text]

38. Ballard-Barbash R, Potosky AL, Harlan LC, et al: Factors associated with surgical and radiation therapy for early stage breast cancer in older women. J Natl Cancer Inst 88:716-726, 1996[Abstract/Free Full Text]

39. Ayanian JZ, Kohler BA, Abe T, et al: The relation between health insurance coverage and clinical outcomes among women with breast cancer. N Engl J Med 329:326-331, 1993[Abstract/Free Full Text]

40. Ward E, Jemal A, Cokkinides V, et al: Cancer disparities by race/ethnicity and socioeconomic status. CA Cancer J Clin 54:78-93, 2004[Abstract/Free Full Text]

41. Boyd C, Zhang-Salomons JY, Groome PA, et al: Associations between community income and cancer survival in Ontario, Canada, and the United States. J Clin Oncol 17:2244-2255, 1999[Abstract/Free Full Text]

42. Mandelblatt JS, Yabroff KR, Kerner JF: Equitable access to cancer services: A review of barriers to quality care. Cancer 86:2378-2390, 1999[CrossRef][Medline]

43. Fisher ES, Wennberg DE, Stukel TA, et al: The implications of regional variations in Medicare spending: Part 1. The content, quality, and accessibility of care. Ann Intern Med 138:273-287, 2003[Abstract/Free Full Text]

Submitted September 20, 2004; accepted July 26, 2005.

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