Association of Major Adverse Financial Events and Later-Stage Cancer Diagnosis in the United States.

PURPOSE: This study assessed the prevalence of specific major adverse financial events (AFEs)-bankruptcies, liens, and evictions-before a cancer diagnosis and their association with later-stage cancer at diagnosis. METHODS: Patients age 20-69 years diagnosed with cancer during 2014-2015 were identified from the Seattle, Louisiana, and Georgia SEER population-based cancer registries. Registry data were linked with LexisNexis consumer data to identify patients with a history of court-documented AFEs before cancer diagnosis. The association of AFEs and later-stage cancer diagnoses (stages III/IV) was assessed using separate sex-specific multivariable logistic regression. RESULTS: Among 101,649 patients with cancer linked to LexisNexis data, 36,791 (36.2%) had a major AFE reported before diagnosis. The mean and median timing of the AFE closest to diagnosis were 93 and 77 months, respectively. AFEs were most common among non-Hispanic Black, unmarried, and low-income patients. Individuals with previous AFEs were more likely to be diagnosed with later-stage cancer than individuals with no AFE (males-odds ratio [OR], 1.09 [95% CI, 1.03 to 1.14]; P < .001; females-OR, 1.18 [95% CI, 1.13 to 1.24]; P < .0001) after adjusting for age, race, marital status, income, registry, and cancer type. Associations between AFEs prediagnosis and later-stage disease did not vary by AFE timing. CONCLUSION: One third of newly diagnosed patients with cancer had a major AFE before their diagnosis. Patients with AFEs were more likely to have later-stage diagnosis, even accounting for traditional measures of socioeconomic status that influence the stage at diagnosis. The prevalence of prediagnosis AFEs underscores financial vulnerability of patients with cancer before their diagnosis, before any subsequent financial burden associated with cancer treatment.

Evaluation of the Completeness of Managed Care Data to Identify Cancer Diagnoses and Treatments for Patients in the SEER-Medicare Data.

BACKGROUND: The utility of codes on Medicare Advantage (MA) data to capture cancer diagnoses and treatment for cancer patients is unknown. OBJECTIVE: This study compared cancer diagnoses and treatments on MA encounter data (MA data) with the Surveillance, Epidemiology, and End-Results (SEER) data. SUBJECTS: Subjects were patients enrolled in either MA or Medicare fee-for-service (MFFS) when diagnosed with incident breast, colorectal, prostate, or lung cancer, 2015-2017, in a SEER cancer registry. MEASURES: MA data, from 2 months before to 12 months following SEER diagnosis, were reviewed to identify cancer diagnoses, surgery, chemotherapy, and radiotherapy (RT). MA data were compared with SEER to determine their sensitivity to capture cancer diagnoses and sensitivity/specificity to identify surgeries. The agreement between SEER and Medicare data regarding receipt of chemotherapy and RT was measured by Kappa statistics. A similar comparison to SEER diagnoses/treatments was made using MFFS claims to provide context for the SEER-MA comparison. RESULTS: The study included 186,449 patients, 38% in MA. MA data had 92%+ sensitivity to identify SEER cancer diagnosis and 90%+ sensitivity for cancer surgery. Specificity for surgery was >84%, except for breast cancer (52%). Kappa statistics for agreement between SEER and MA data regarding chemotherapy varied by cancer, 0.61-0.82, and for receipt of RT exceeded 0.75 for all cancers. Results observed for MFFS claims were similar to those in MA data. CONCLUSION: For 4 common cancers, MA data included most cancer diagnoses and general types of cancer treatment reported in the SEER data. More research is needed to assess additional cancers and detailed treatments.

A History of Health Economics and Healthcare Delivery Research at the National Cancer Institute.

With increased attention to the financing and structure of healthcare, dramatic increases in the cost of diagnosing and treating cancer, and corresponding disparities in access, the study of healthcare economics and delivery has become increasingly important. The Healthcare Delivery Research Program (HDRP) in the Division of Cancer Control and Population Sciences at the National Cancer Institute (NCI) was formed in 2015 to provide a hub for cancer-related healthcare delivery and economics research. However, the roots of this program trace back much farther, at least to the formation of the NCI Division of Cancer Prevention and Control in 1983. The creation of a division focused on understanding and explaining trends in cancer morbidity and mortality was instrumental in setting the direction of cancer-related healthcare delivery and health economics research over the subsequent decades. In this commentary, we provide a brief history of health economics and healthcare delivery research at NCI, describing the organizational structure and highlighting key initiatives developed by the division, and also briefly discuss future directions. HDRP and its predecessors have supported the growth and evolution of these fields through the funding of grants and contracts; the development of data, tools, and other research resources; and thought leadership including stimulation of research on previously understudied topics. As the availability of new data, methods, and computing capacity to evaluate cancer-related healthcare delivery and economics expand, HDRP aims to continue to support this growth and evolution.

Role of Medicaid in Early Detection of Screening-Amenable Cancers.

BACKGROUND: This study examines the association between Medicaid enrollment, including through the National Breast and Cervical Cancer Early Detection Program (NBCCEDP), and distant stage for three screening-amenable cancers: breast, cervical, and colorectal. METHODS: We use the Surveillance, Epidemiology, and End Results Cancer Registry linked with Medicaid enrollment data to compare patients who were Medicaid insured with patients who were not Medicaid insured. We estimate the likelihood of distant stage at diagnosis using logistic regression. RESULTS: Medicaid enrollment following diagnosis was associated with the highest likelihood of distant stage. Medicaid enrollment through NBCCEDP did not mitigate the likelihood of distant stage disease relative to Medicaid enrollment prior to diagnosis. Non-Hispanic Black patients had a greater likelihood of distant stage breast and colorectal cancer. Residing in higher socioeconomic areas was associated with a lower likelihood of distant stage breast cancer. CONCLUSIONS: Medicaid enrollment prior to diagnosis is associated with a lower likelihood of distant stage in screen amenable cancers but does not fully ameliorate disparities. IMPACT: Our study highlights the importance of health insurance coverage prior to diagnosis and demonstrates that while targeted programs such as the NBCCEDP provide critical access to screening, they are not a substitute for comprehensive insurance coverage.

The Utility of Pathology Reports to Identify Persons With Cancer Recurrence.

BACKGROUND: Cancer recurrence is an important measure of the impact of cancer treatment. However, no population-based data on recurrence are available. Pathology reports could potentially identify cancer recurrences. Their utility to capture recurrences is unknown. OBJECTIVE: This analysis assesses the sensitivity of pathology reports to identify patients with cancer recurrence and the stage at recurrence. SUBJECTS: The study includes patients with recurrent breast (n=214) or colorectal (n=203) cancers. RESEARCH DESIGN: This retrospective analysis included patients from a population-based cancer registry who were part of the Patient-Centered Outcomes Research (PCOR) Study, a project that followed cancer patients in-depth for 5 years after diagnosis to identify recurrences. MEASURES: Information abstracted from pathology reports for patients with recurrence was compared with their PCOR data (gold standard) to determine what percent had a pathology report at the time of recurrence, the sensitivity of text in the report to identify recurrence, and if the stage at recurrence could be determined from the pathology report. RESULTS: One half of cancer patients had a pathology report near the time of recurrence. For patients with a pathology report, the report's sensitivity to identify recurrence was 98.1% for breast cancer cases and 95.7% for colorectal cancer cases. The specific stage at recurrence from the pathology report had a moderate agreement with gold-standard data. CONCLUSIONS: Pathology reports alone cannot measure population-based recurrence of solid cancers but can identify specific cohorts of recurrent cancer patients. As electronic submission of pathology reports increases, these reports may identify specific recurrent patients in near real-time.

Stage and mortality of low-income patients with cancer: Evidence from SEER-Medicaid.

BACKGROUND: A national data source for identifying patients with cancer enrolled in Medicaid is needed to evaluate cancer care for low-income, publicly insured patients. In this study, a population-based data set of patients diagnosed with cancer and enrolled in Medicaid was created and evaluated. The objective was to compare the characteristics of patients with cancer identified in Surveillance, Epidemiology, and End Results (SEER) data and linked to the Medicaid Analytic eXtract (MAX) Personal Summary files with the characteristics of patients who were not linked to the MAX file. METHODS: All persons in 14 SEER registries diagnosed with cancer from 2006 to 2013 who were or were not linked to the 2006-2013 nationwide MAX files were selected, and patient demographic characteristics were compared for 3 age groups. Common cancer sites and the timing of Medicaid enrollment with respect to patients' cancer diagnoses were reported, and the stage at diagnosis and 4-year mortality were compared by 3 categories of Medicaid enrollment. RESULTS: Approximately 18% of the sample was enrolled in Medicaid within 25 months of diagnosis. Enrollees had a greater proportion of racial/ethnic minorities in comparison with patients who were not enrolled. A late-stage diagnosis was more common among Medicaid patients and particularly among those who enrolled after their diagnosis. For every common cancer site, mortality was highest in the sample of Medicaid patients who enrolled after their diagnosis. CONCLUSIONS: The Medicaid enrollment data newly added to SEER records enhance researchers' ability to investigate research questions related to Medicaid policies and care delivery. For patients enrolled before their diagnosis, Medicaid appears to offer protection against late-stage disease and mortality.

Cancer-Attributable Medical Costs for Colorectal Cancer Patients by Phases of Care: What Is the Effect of a Prior Cancer History?

Medical care costing studies have excluded patients with a prior cancer history. This study aims to update methods for estimating medical care costs attributable to cancer and to evaluate the effect of a prior history of cancer on costs for colorectal cancer (CRC) patients. We used Surveillance, Epidemiology, and End Results (SEER)-Medicare data and matched cancer patients to controls without cancer to estimate cancer-attributable costs by phases of care using Medicare 2007-2013 claims. CRC annualized average cancer-attributable costs were $56.0 K, $5.3 K, $92.5 K, and $24.3 K in the initial, continuing, and end-of-life cancer and noncancer death phases, respectively, in 2014 dollars. Costs were higher for patients diagnosed with more advanced stage, younger ages, and nonwhite races. Costs for patients with prior cancers were consistently higher than patients without prior cancers, especially in the continuing (4.9 K vs 7.2 K) and end-of-life noncancer death (22.7 K vs 30.0 K). Our CRC costs improve previous estimates by using more recent data and updated methods.

Estimating Chemotherapy Use Among Patients With a Prior Primary Cancer Diagnosis Using SEER-Medicare Data.

Cancer treatment studies commonly exclude patients with prior primary cancers due to difficulties in ascertaining for which site treatment is intended. Surveillance, Epidemiology, and End Results-Medicare patients 65 years and older diagnosed with an index colon or rectal cancer (CRC) or female breast cancer (BC) between 2004 and 2013 were included. Chemotherapy, defined as "any chemotherapy" and more restrictively as "chemotherapy with confirmatory diagnoses," was ascertained based on claims data within 6 months of index cancer diagnosis by prior cancer history. Any chemotherapy use was slightly lower among patients with a prior cancer (CRC: no prior = 17.4%, prior = 16.1%; BC: no prior = 12.9%, prior = 12.0%). With confirmatory diagnoses required, estimates were lower, especially among patients with a prior cancer (CRC: no prior = 16.8%, prior = 13.6%; BC: no prior = 12.6%, prior = 11.0%). These findings suggest that patients with prior cancers can be included in studies of chemotherapy use; requiring confirmatory diagnoses can increase treatment assignment confidence.

Home Health Use Following a Cancer Diagnosis Among Patients Enrolled in Medicare Advantage and Traditional Medicare: Findings From the Newly Linked SEER-Medicare and Home Health OASIS Data.

BACKGROUND: This article describes characteristics of patients receiving home health following an initial cancer diagnosis, comparing those enrolled in Medicare Advantage (MA) and Traditional Medicare (TM), using the newly linked 2010-2014 National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER)-Medicare and home health Outcome and Assessment Information Set (OASIS) data. METHODS: We identified SEER-Medicare beneficiaries with at least one OASIS assessment within 3 months of cancer diagnosis in 2010-2014, and summarized their demographic and clinical characteristics. Demographic and diagnostic data were obtained from the SEER-Medicare data, while further details about cognitive status, mood, function, and medical history were obtained from OASIS. We assessed differences between MA and TM beneficiaries using chi-square tests for independence, t-tests, and Kruskal-Wallis tests. RESUTLS: We identified 104 023 patients who received home health within 3 months of cancer diagnosis: 81 587 enrolled in TM and 22 436 enrolled in MA. TM cancer patients had higher unadjusted rates of home health use than MA patients (16.3% vs 10.3%, P < .001). TM cancer patients receiving home health had more limitations in their cognitive function than their MA counterparts and longer lengths of service (mean = 42.2 days vs 39.4 days, P < .001; median = 27 vs 26 days, interquartile range = 42). CONCLUSION: This study demonstrates the large number of cancer patients in the SEER-Medicare-OASIS data and describes characteristics for TM and MA patients. These newly linked data can be used to assess home health care among older patients with cancer.

Comparison of Physician Data in Two Data Files Available for Cancer Health Services Research.

INTRODUCTION: Physicians are vital to health-care delivery, but assessing their impact on care can be challenging given limited data. Historically, health services researchers have obtained physician characteristics data from the American Medical Association (AMA) Physician Masterfile. The Center for Medicare and Medicaid Services' Medicare Data on Provider Practice and Specialty (MD-PPAS) file was assessed, as an alternative source of physician data, particularly in the context of cancer health services research. METHODS: We used physician National Provider Identifiers in the MD-PPAS data (2008-2014) to identify physicians in the AMA data current as of July 18, 2016. Within each source, we grouped physicians into six broad specialty groups. Percent agreement and Cohen's kappa coefficient (k) were calculated for age, sex, specialty, and practice state. RESULTS: Among the 698 202 included physicians, there was excellent agreement for age (percent agreement = 97.7%, k = 0.97) and sex (99.4%, k = 0.99) and good agreement for specialty (86.1%, k = 0.80). Within specialty, using AMA as the reference, agreement was lowest for oncologists (77%). Approximately 85.9% of physicians reported the same practice state in both data sets. CONCLUSION: Although AMA data have been commonly used to account for physician-level factors in health services research, MD-PPAS data provide researchers with an alternative option depending on study needs. MD-PPAS data may be optimal if nonphysicians, provider utilization, practice characteristics, and/or temporal changes are of interest. In contrast, the AMA data may be optimal if more granular specialty, physician training, and/or a broader inclusion of physicians is of interest.

Assessment of Oncology Practice Billing Claims for Supplementing Chemotherapy: A Pilot Study in the Georgia SEER Cancer Registry.

BACKGROUND: Chemotherapy information in the population-based cancer registries is underascertained and lacks detail. We conducted a pilot study in the Georgia SEER Cancer Registry (GCR) to investigate the feasibility of supplementing chemotherapy information using billing claims from six private oncology practices (OP). METHODS: To assess cancer patients' representativeness from OP, we compared individuals with invasive first primary cancers diagnosed during 2013-2015 in the GCR (cohort 1) with those who had at least one OP claim in the 12 months after diagnosis (cohort 2). To assess completeness of OP claims to capture chemotherapy (yes or no), we further restricted cohort 2 to patients ages 65 years and older enrolled in fee-for-service Medicare Part A and B from the diagnosis date through 12 months follow-up or to the date of death. With Medicare data serving as the gold standard, sensitivity, specificity, and kappa statistics for the receipt of chemotherapy per OP claims were calculated by demographic and clinical characteristics. RESULTS: Cancer patients seeking care in the OP included in our analysis were not representative of the underlying patient population in the GCR. The practices underrepresented minorities and uninsured while overrepresenting females, persons with high socioeconomic status, patients residing outside the metropolitan Atlanta area, and persons with advance staged disease. The ability of practice claims to identify chemotherapy receipt was moderate (76.1% sensitivity) but varied by demographic and clinical characteristics (76.1-83.0%). CONCLUSIONS: Given the limited ability of OP claims to identify chemotherapy receipt, we suggest analyzing these data for hypothesis generation, but inference should be limited to this patient cohort.

Sensitivity of Medicare Data to Identify Oncologists.

BACKGROUND: Health services researchers have studied how care from oncologists impacts treatment and outcomes for cancer patients. These studies frequently identify physician specialty using files from the Center for Medicare and Medicaid Services (CMS) or the American Medical Association (AMA). The completeness of the CMS data resources, individually or combined, to identify oncologists is unknown. This study assessed the sensitivity of CMS data to capture oncologists included in the AMA Physician Masterfile. METHODS: Oncologists were identified from three CMS data resources: physician claims, the National Plan and Provider Enumeration System Registry, and the Medicare Data on Provider Practice and Specialty file. CMS files and AMA data were linked using a unique physician identifier. Sensitivity to identify any oncologists, radiation oncologists (ROs), surgical oncologists (SOs), and medical oncologists (MOs) was calculated for individual and combined CMS files. For oncologists in the AMA data not identified as oncologists in the CMS data, their CMS specialty was assessed. RESULTS: Individual CMS files each captured approximately 83% of the 17 934 oncologists in the AMA Masterfile; combined CMS files captured 90.4%. By specialty, combined CMS data captured 98.2% of ROs, 89.3% of MOs, and 70.1% of SOs. For ROs and SOs in the AMA data not identified as oncologists in the CMS data, their CMS specialty was usually similar to the AMA subspecialty; ROs were radiologists and SOs were surgeons. CONCLUSION: Using combined files from CMS identified most ROs and MOs found in the AMA, but not most SOs. Determining whether to use the AMA data or CMS files for a particular research project will depend on the specific research question and the type of oncologist included in the study.

Development and Utility of the Observational Research in Oncology Toolbox: Cancer Medications Enquiry Database-Healthcare Common Procedure Coding System (HCPCS).

PURPOSE: Health-care claims are of increasing utility as a rich, real-world data resource for conducting treatment-related cancer research. However, multiple dynamic coding nomenclatures exist, leading to study variability. To promote increased standardization and reproducibility, the National Cancer Institute (NCI) developed the Cancer Medications Enquiry Database (CanMED)-Healthcare Common Procedure Coding System (HCPCS) within the Observational Research in Oncology Toolbox. METHODS: The CanMED-HCPCS includes codes for oncology medications that a) have a US Food and Drug Administration-approved indication for cancer treatment or treatment-related symptom management; b) are present in National Comprehensive Cancer Network guidelines; or c) carry an orphan drug designation for treatment or management of cancer. Included medications and their HCPCS codes were primarily identified based on Center for Medicare and Medicaid Services annual HCPCS Indices (2012-2018). To demonstrate the utility of the CanMED-HCPCS, use of systemic treatment for stage II-IV colorectal cancer patients included in the Surveillance, Epidemiology, and End Results-Medicare data (2007-2013) was assessed. RESULTS: The CanMED-HCPCS (v2018) includes 332 HCPCS codes for cancer-related medications: chemotherapy (156), immunotherapy (74), hormonal therapy (54), and ancillary therapy (48). Observed treatment trends within the NCI Surveillance, Epidemiology, and End Results-Medicare data were as expected; utilization of each treatment type increased with stage, and immunotherapy was largely confined to use among stage IV patients. CONCLUSION: The CanMED-HCPCS provides a comprehensive resource that can be used by the research community to facilitate systematic identification of medications within claims or electronic health data using the HCPCS nomenclature and greater reproducibility of cancer surveillance and health services research.

An Evaluation of the Utility of Big Data to Supplement Cancer Treatment Information: Linkage Between IQVIA Pharmacy Database and the Surveillance, Epidemiology, and End Results Program.

Oral anticancer medications (OAMs) are increasingly utilized. We evaluated the representativeness and completeness of IQVIA, a large aggregator of pharmacy data, for breast cancer, colon cancer, chronic myeloid leukemia, and myeloma cases diagnosed in six Surveillance, Epidemiology, and End Results Program (SEER) registries between 2007 and 2011. Patient's SEER and SEER-Medicare data were linked and compared with IQVIA pharmacy data from 2006 to 2012 for specific OAMs. Overall, 67.6% of SEER cases had a pharmacy claim in IQVIA during the treatment assessment window. This varied by location, race and ethnicity, and insurance status. IQVIA consistently identified fewer cases who received an OAM of interest than SEER-Medicare. The difference was least pronounced for breast cancer agents and most pronounced for myeloma agents. The IQVIA pharmacy database included a large portion of persons in the SEER areas. Future studies should assess receipt of OAMs for other cancer sites and in different SEER registries.

Using the SEER-Medicare Data to Assess Incident Chronic Myeloid Leukemia and Bladder Cancer Cases Missed by Cancer Registries.

The growing use of oral systemic therapies and transition of some cancer treatments to the outpatient setting makes capturing all cancer case patients more difficult. We aim to develop algorithms to identify potentially missed incident case patients and estimate impact on incidence rates. We reviewed claims from SEER-Medicare 5% noncancer control patient sample to identify potentially missed chronic myeloid leukemia (CML) and bladder case patients based on diagnosis codes, cancer-related treatments, and oncology consultations. Observed rates of definite missed CML and definite and probable missed bladder case patients were calculated and the impact of missed case patients of these two cancers on SEER 65+ incidence rates were estimated. From 2008 to 2015, the algorithm estimated 781 definite CML case patients missed, increasing the number by 10.7%. From 2007 to 2015, the algorithm estimated 4629 definite and 5772 probable bladder case patients missed, increasing the number by 3.8% to 8.1%. Our algorithms offer potential methods for identifying missed case patients and validating the completeness of cancer registries.

Development and Evaluation of a Process to Link Cancer Patients in the SEER Registries to National Medicaid Enrollment Data.

Cancer patients receiving Medicaid have worse prognosis. Patients in 14 Surveillance, Epidemiology, and End Results (SEER) cancer registries were linked to national Medicaid enrollment files, 2006-2013, to determine enrollment status during the year before and after diagnosis. A deterministic algorithm based on Social Security number, Medicare Health Insurance Claim number, sex, and date of birth was utilized. Results were compared with an independent linkage of Kentucky-based SEER and Medicaid data. A total 559 484 cancer cases were linked to national Medicaid enrollment files, representing 15-17% of persons with cancer yearly. About 60% of these cases were a complete match on all variables. There was 99% agreement on enrollment status compared with the Kentucky linked data. SEER data were successfully linked to national Medicaid enrollment data. NCI will make the linked data available to researchers, allowing for more detailed assessments of the impact Medicaid enrollment has on cancer diagnosis and outcomes.

Updated Overview of the SEER-Medicare Data: Enhanced Content and Applications.

BACKGROUND: The National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER)-Medicare-linked database was first created almost 30 years ago. Over time, additional data have been added to the SEER-Medicare database, allowing for expanded insights into the delivery of health care across the cancer continuum from screening to end of life. METHODS: This article includes an overview of the current SEER-Medicare database, presenting potential users with an introduction to how the data can facilitate innovative epidemiologic and health services research studies. With a focus on the population 65 years and older, this article presents descriptive data on beneficiary demographics, cancer characteristics, service settings, Medicare coverage (eg, Parts A, B, C, and D), and use (number of services or bills) from 2011 to 2015. RESULTS: From 2011 to 2015, 857 056 cancer patients and 601 470 population-based noncancer controls were added to the database. The database includes detailed tumor characteristics and clinical assessments for cancer cases, and demographics and health-care use (eg, hospitals, outpatient facilities, individual providers, hospice, home health-care providers, and pharmacies) for both cases and controls. Although characteristics varied overall between cases and controls, sufficient cancer-specific matched controls are available. Roughly 60% of cases were enrolled in fee for service at cancer diagnosis. The annual average number of claims per case was 60.7 and 92.3 during the year before and after cancer diagnosis, respectively, and 127.5 during the year before death. CONCLUSIONS: The large sample size and diverse array of data on cancer patients and noncancer controls in the SEER-Medicare database make it a unique resource for conducting cancer health services research.

Patterns of Care and Costs for Older Patients With Colorectal Cancer at the End of Life: Descriptive Study of the United States and Canada.

PURPOSE: End-of-life (EOL) cancer care is costly, with challenges regarding intensity and place of care. We described EOL care and costs for patients with colorectal cancer (CRC) in the United States and the province of Ontario, Canada, to inform better care delivery. METHODS: Patients diagnosed with CRC from 2007 to 2013, who died of any cancer from 2007 to 2013 at age ≥ 66 years, were selected from the US SEER cancer registries linked to Medicare claims (n = 16,565) and the Ontario Cancer Registry linked to administrative health data (n = 6,587). We estimated total and resource-specific costs (2015 US dollars) from public payer perspectives over the last 360 days of life by 30-day periods, by stage at diagnosis (0-II, III, IV). RESULTS: In all months, especially 30 days before death, higher percentages of SEER-Medicare than Ontario patients received chemotherapy (15.7% v 8.0%), and imaging tests (39.4% v 31.1%). A higher percentage of Ontario patients were hospitalized (62.5% v 51.0%), but 43.2% of hospitalized SEER-Medicare patients had intensive care unit (ICU) admissions versus 17.9% of hospitalized Ontario patients. Cost differences between cohorts were greater for patients with stage IV disease. In the last 30 days, mean total costs for patients with stage IV disease were $15,881 (SEER-Medicare) and $12,034 (Ontario) versus $19,354 and $17,312 for stage 0-II. Hospitalization costs were higher for SEER-Medicare patients ($11,180 v $9,434), with lower daily hospital costs in Ontario ($1,067 v $2,004). CONCLUSION: These findings suggest opportunities for reducing chemotherapy and ICU use in the United States and hospitalizations in Ontario.

Racial Disparities in the Receipt of Guideline Care and Cancer Deaths for Women with Ovarian Cancer.

BACKGROUND: Black women with ovarian cancer experience worse survival than white women. Receipt of guideline care improves survival, yet care may vary by race. We assessed rates of guideline care and role of guideline treatment on survival disparities. METHODS: This retrospective cohort analysis used the NCI's Patterns of Care data for women diagnosed with ovarian cancer, 2002 and 2011 (weighted n = 3,999), with follow-up through December 12, 2014. Logistic regression included patient characteristics, insurance, and gynecologic oncologist (GO) consultation to produce adjusted standardized percentages of women receiving guideline treatment by race. Cox proportional hazards analysis assessed risk of ovarian cancer death. RESULTS: Guideline care was significantly lower for black women compared with white women (adjusted 27.5% vs. 34.1%). Increased receipt of guideline care was associated with GO consultation, younger ages, stage, and insurance. Rates of GO consultation were comparable for black and white women, approximately 60%. Black women were more likely to receive no surgery or no chemotherapy if they did not consult a GO. The unadjusted death risk was significantly higher in black women (HR = 1.33). After adjusting for receipt of guideline care and other factors, black and white women had similar risk of death (HR = 1.05). CONCLUSIONS: Race was not associated with risk of death when guideline care was included in multivariate survival models. However, black patients received less guideline care. GO consultation significantly increased receipt of guideline care. IMPACT: Research is needed to understand treatment perspectives for black patients and their providers to increase the receipt of guideline care and reduce survival disparities.

New Opportunities for Cancer Health Services Research: Linking the SEER-Medicare Data to the Nursing Home Minimum Data Set.

BACKGROUND: The Surveillance, Epidemiology and End Results (SEER)-Medicare data combine clinical information from population-based cancer registries with Medicare claims. These data have been used in many studies to understand cancer screening, treatment, outcomes, and costs. However, until recently, these data included limited information related to the characteristics and outcomes of cancer patients residing in or admitted to nursing homes. OBJECTIVES: To provide an overview of the new linkage between SEER-Medicare data and the Minimum Data Set (MDS), a nursing home resident assessment instrument detailing residents' physical, psychological, and psychosocial functioning as well as any therapies or treatments received. RESEARCH DESIGN: This is a descriptive, retrospective cohort study. SUBJECTS: Persons in SEER-Medicare diagnosed with cancer from 2004 to 2013 were linked to the 2011-2014 MDS, with 17% of SEER-Medicare patients linked to the MDS data. During 2011-2014, we identified 318,617 cancer patients receiving care in a nursing home and 256,947 cancer patients newly admitted to a total of 10,953 nursing homes. Of these patients, approximately two thirds were Medicare fee-for-service beneficiaries. RESULTS: The timing from cancer diagnoses to nursing home admission varied by cancer. In total, 93% of all patients were admitted directly to a nursing home from an acute care hospital. The majority of patients were cognitively intact, 21% reported some level of depression, and 9% had severe functional limitations. CONCLUSIONS: The new SEER-Medicare-MDS dataset provides a valuable resource for understanding the postacute and long-term care experiences of cancer patients receiving care in United States' nursing homes.