CoRe Enrollment File

The SEER-Medicare Condensed Resource (CoRe) Enrollment file includes one record for each cancer diagnosis reported to SEER that occurred among persons enrolled in Medicare. The file can be used to identify analytic cohorts based on continuous Medicare enrollment relative in time to the date of cancer diagnosis. Requiring continuous enrollment ensures as complete as possible healthcare utilization and outcomes data. The enrollment file combines information from the annual Medicare Master Beneficiary Summary File (MBSF) (aka the Medicare BASE enrollment file) and the SEER-Medicare Cancer File.

Historically, most SEER-Medicare analyses have been restricted to elderly persons (i.e., age >65 years) who have continuous enrollment in Parts A (in-patient) and B (out-patient) fee-for-service (ABFFS) prior to a malignant cancer diagnosis to assess pre-diagnosis comorbidities and to persons who have continuous ABFFS and/or Part D (prescription drug) coverage after diagnosis to assess receipt of cancer treatment. With the release of Medicare Advantage (MA) encounter data, the assessment of healthcare utilization among persons enrolled in Medicare managed care plans can also be assessed. Therefore, the CoRe enrollment file indicates ABFFS or Part D cohort inclusion for each cancer diagnosis.

Cohort observation time can end (“cohort exit”) in month 2+ after diagnosis for multiple reasons (e.g., Medicare enrollment status changed, the person died, the person was diagnosed with a subsequent malignant cancer, or end of available data). The end observation date and reason for end of observation is also documented in the Enrollment file.

If a person has more than one cancer diagnosis, they will have more than one record in the Enrollment file, to provide enrollment information relative to each cancer diagnosis. Additional records will include enrollment data at and around any subsequent cancer diagnosis; therefore, the last chronological record for each person will list either the date they died or the end of available data, which will change each time the linkage is updated. The below figure illustrates four scenarios of how Medicare enrollment relative to cancer diagnosis relates to cohort inclusion and available measures.

Scenarios illustrating the relationship between Medicare enrollment relative to cancer diagnosis, cohort inclusion, and available measures

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Scenarios illustrating the relationship between Medicare enrollment relative to cancer diagnosis, cohort inclusion, and available measures.

A. Measures for a person in ABFFS cohort (Irrespective of enrollment in Part D).

This illustrates the observed timeline and available measures for a person who has only one known cancer diagnosis and is included in the ABFFS cohort, but not in the Part D cohort. ABFFS cohort inclusion requires enrollment in Medicare fee-for-service Parts A and B during a continuous 12-month baseline pre-diagnosis period, the month of diagnosis, and at least one month post diagnosis. In this specific example, the person is included in the cohort for more than 12 months post diagnosis. Therefore, this person will have available claims to determine pre- and post-diagnosis comorbidities, and in-patient and out-patient cancer treatments starting from 4 months prior to their diagnosis through the end of ABFFS cohort observation. Cohorts are designed to allow for treatment assessments prior to diagnosis to acknowledge possible diagnosis date imprecision. Here, cohort observation may have ended due to changes in enrollment, such as dropping Part A and/or B coverage or switching to Medicare Advantage (HMO); death; or end of available data.

B. Measures for a person in Part D cohort (Irrespective of enrollment in Part ABFFS).

This illustrates the observed timeline and available measures for a person who has only one known cancer diagnosis and is included in the Part D cohort, but not in the ABFFS cohort. Part D cohort inclusion requires enrollment in Medicare Part D during a continuous 4-month baseline pre-diagnosis period, the month of diagnosis, and at least one month post diagnosis. In this specific example, the person is included in the cohort for more than 12 months post diagnosis. Therefore, this person will have available prescription data to determine their pharmacy-based cancer treatments starting from 4 months prior to their diagnosis date through the end of Part D cohort observation. Cohorts were designed to allow for treatment assessments prior to diagnosis to acknowledge possible diagnosis date imprecision. Here, cohort observation may have ended due to end of Part D coverage; death; or end of available data.

C. Measures for a person in ABFFS and part D cohort.

This illustrates the observed timeline and available measures for a person who has only one known cancer diagnosis and is included in both the ABFFS and Part D cohorts. ABFFS cohort inclusion requires enrollment in Medicare fee-for-service Parts A and B during a continuous 12-month baseline pre-diagnosis period, the month of diagnosis, and at least one month post diagnosis. Part D cohort inclusion requires enrollment in Medicare Part D a continuous 4-month baseline pre-diagnosis period, the month of diagnosis, and at least one month post diagnosis. In this specific example, the person stays in the ABFFS cohort for more than 12 months post diagnosis but drops their Part D coverage before their ABFFS cohort observation ends. This person will have available claims to determine pre- and post-diagnosis comorbidities and sufficient information to determine their in-patient, out-patient, and pharmacy-based cancer treatments starting from 4 months prior to their diagnosis date through end of cohort observation. Cohorts were designed to allow for treatment assessments prior to diagnosis to acknowledge possible diagnosis date imprecision. In this example, pharmacy-based cancer treatments will be observable until the person dropped their Part D coverage and in-patient and out-patient cancer treatments will be observable through the end of ABFFS cohort observation, which here may have ended due to changes in enrollment, such as dropping Part A and/or B coverage or switching to Medicare Advantage (HMO); death; or end of available data.

D. Measures for a person in ABFFS cohort only, not in Part D cohort, two cancers.

This illustrates the observed timeline and available measures for a person who has two known cancer diagnoses. Cohort inclusion is determined at the tumor-level. Therefore, in this example, the person’s two tumors were both included in the ABFFS cohort, but not the Part D cohort. ABFFS cohort inclusion requires enrollment in Medicare fee-for-service Parts A and B during a continuous 12-month baseline pre-diagnosis period, the month of diagnosis, and at least one month post diagnosis. As a result, this person will have available claims to determine comorbidities during the pre- and post-diagnosis periods for both tumors and sufficient information to determine their in-patient and out-patient cancer treatments starting from 4 months prior to each diagnosis date through end of cohort observation for each tumor. Cohorts were designed to allow for treatment assessments prior to diagnosis to acknowledge possible diagnosis date imprecision. In this example, ABFFS cohort observation for tumor 1 ends at tumor 2 diagnosis and ABFFS cohort observation for tumor 2 may have ended due to changes in enrollment, such as dropping Part A and/or B coverage or switching to Medicare Advantage (HMO); death; or end of available data. Note that the post-diagnosis observation period for tumor 1 overlaps with the pre-diagnosis observation period for tumor 2.

SEER-Medicare cancer diagnoses at age 66+ years by cohort inclusion status

Cancer diagnoses that do not meet the ABFFS or Part D cohort inclusion criteria are included in the CoRe Enrollment file, to allow assessments of representativeness. The file includes variables that document reason for ABFFS and/or Part D cohort exclusion (i.e., in hierarchical order: diagnosed prior to 2000 for ABFFS or 2008 for Part D; unknown month of diagnosis; age at diagnosis <66 years or unknown age; non-malignant cancer diagnosis or malignancy status unknown; diagnosis at death/autopsy; and non-continuous enrollment during the baseline period: 12 months prior to through one month after cancer diagnosis). Cancer diagnoses included in the ABFFS cohort without any claims during the 12 months prior to diagnosis are also flagged.

The below tables provide a comparison of person-level demographics and tumor characteristics for the cancers included in the ABFFS cohort, the Part D cohort, both the ABFFS and Part D cohorts, which is not mutually exclusive from the two prior categories, and those in neither cohort, which largely consists of Medicare Advantage beneficiaries. Persons with more than one eligible cancer will be represented more than once and could be included in more than one category because cohort inclusion is assessed with respect to each cancer diagnosis.

Download compiled table (XLSX, 21 KB)

ABFFS Cohort MA Cohort Part D Cohort Both ABFFS & Part D Cohorts Both MA & Part D Cohorts Neither ABBFS/MA/Part D Cohorts
N Col % N Col % N Col % N Col % N Col % N Col %
Total 4,939,498 100.0% 843,730 100.0% 3,626,778 100.0% 1,899,926 100.0% 820,626 100.0% 1,768,855 100.0%
Year of Diagnosis ABFFS Cohort MA Cohort Part D Cohort Both ABFFS & Part D Cohorts Both MA & Part D Cohorts Neither ABBFS/MA/Part D Cohorts
N Col % N Col % N Col % N Col % N Col % N Col %
2000 210,934 4.27% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 112,257 6.35%
2001 220,018 4.45% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 113,411 6.41%
2002 228,233 4.62% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 107,262 6.06%
2003 234,979 4.76% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 96,593 5.46%
2004 240,047 4.86% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 100,985 5.71%
2005 241,788 4.89% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 103,352 5.84%
2006 240,959 4.88% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 112,459 6.36%
2007 238,333 4.83% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 123,375 6.97%
2008 231,676 4.69% 0 0.0% 183,753 5.07% 107,973 5.68% 0 0.0% 57,608 3.26%
2009 228,458 4.63% 0 0.0% 191,793 5.29% 108,778 5.73% 0 0.0% 59,986 3.39%
2010 223,121 4.52% 0 0.0% 194,308 5.36% 108,308 5.70% 0 0.0% 60,800 3.44%
2011 223,732 4.53% 0 0.0% 201,943 5.57% 111,397 5.86% 0 0.0% 61,079 3.45%
2012 219,608 4.45% 0 0.0% 211,258 5.82% 116,958 6.16% 0 0.0% 60,762 3.44%
2013 219,228 4.44% 0 0.0% 238,403 6.57% 132,624 6.98% 0 0.0% 62,661 3.54%
2014 218,429 4.42% 0 0.0% 256,632 7.08% 142,062 7.48% 0 0.0% 65,108 3.68%
2015 220,339 4.46% 0 0.0% 273,657 7.55% 147,508 7.76% 0 0.0% 67,118 3.79%
2016 224,315 4.54% 116,967 13.86% 287,139 7.92% 154,343 8.12% 113,068 13.78% 63,717 3.60%
2017 225,323 4.56% 127,690 15.13% 303,744 8.38% 157,915 8.31% 123,937 15.10% 64,800 3.66%
2018 222,339 4.50% 135,909 16.11% 312,065 8.60% 157,619 8.30% 132,236 16.11% 67,714 3.83%
2019 223,810 4.53% 149,569 17.73% 329,161 9.08% 160,305 8.44% 145,900 17.78% 70,860 4.01%
2020 197,247 3.99% 143,868 17.05% 302,768 8.35% 142,187 7.48% 139,924 17.05% 66,921 3.78%
2021 206,582 4.18% 169,727 20.12% 340,154 9.38% 151,949 8.00% 165,561 20.17% 70,027 3.96%
Age at Diagnosis ABFFS Cohort MA Cohort Part D Cohort Both ABFFS & Part D Cohorts Both MA & Part D Cohorts Neither ABBFS/MA/Part D Cohorts
N Col % N Col % N Col % N Col % N Col % N Col %
66-69 950,340 19.24% 173,785 20.60% 770,238 21.24% 379,266 19.96% 170,621 20.79% 469,972 26.57%
70-74 1,249,134 25.29% 243,247 28.83% 973,741 26.85% 496,570 26.14% 237,170 28.90% 417,335 23.59%
75-79 1,135,463 22.99% 191,775 22.73% 800,914 22.08% 421,073 22.16% 186,339 22.71% 332,689 18.81%
80-84 863,070 17.47% 127,555 15.12% 577,658 15.93% 313,826 16.52% 123,300 15.03% 258,241 14.60%
85+ 741,491 15.01% 107,368 12.73% 504,227 13.90% 289,191 15.22% 103,196 12.58% 290,618 16.43%
Race/Ethnicity ABFFS Cohort MA Cohort Part D Cohort Both ABFFS & Part D Cohorts Both MA & Part D Cohorts Neither ABBFS/MA/Part D Cohorts
N Col % N Col % N Col % N Col % N Col % N Col %
Non-Hispanic White 4,150,472 84.03% 588,263 69.72% 2,755,967 75.99% 1,560,375 82.13% 569,154 69.36% 1,337,748 75.63%
Non-Hispanic Black 334,175 6.77% 96,027 11.38% 320,848 8.85% 123,799 6.52% 94,286 11.49% 169,376 9.58%
Non-Hispanic American Indian/Alaska Native 14,908 0.30% 2,261 0.27% 10,710 0.30% 6,139 0.32% 2,178 0.27% 5,934 0.34%
Non-Hispanid Asian/Pacific Islander 138,302 2.80% 46,247 5.48% 174,040 4.80% 70,140 3.69% 45,551 5.55% 93,456 5.28%
Hispanic 275,027 5.57% 102,250 12.12% 336,214 9.27% 124,083 6.53% 100,973 12.30% 154,597 8.74%
Unkown 26,614 0.54% 8,682 1.03% 28,999 0.80% 15,390 0.81% 8,484 1.03% 7,744 0.44%
Sex ABFFS Cohort MA Cohort Part D Cohort Both ABFFS & Part D Cohorts Both MA & Part D Cohorts Neither ABBFS/MA/Part D Cohorts
N Col % N Col % N Col % N Col % N Col % N Col %
Male 2,552,344 51.67% 427,470 50.66% 1,780,757 49.10% 909,959 47.89% 413,387 50.37% 942,631 53.29%
Female 2,387,154 48.33% 416,260 49.34% 1,846,021 50.90% 989,967 52.11% 407,239 49.63% 826,224 46.71%
Prior Cancer ABFFS Cohort MA Cohort Part D Cohort Both ABFFS & Part D Cohorts Both MA & Part D Cohorts Neither ABBFS/MA/Part D Cohorts
N Col % N Col % N Col % N Col % N Col % N Col %
First cancer (00/01) 3,640,465 73.70% 612,076 72.54% 2,621,874 72.29% 1,342,507 70.66% 596,009 72.63% 1,275,880 72.13%
Has prior cancer (02-59) 1,299,033 26.30% 231,654 27.46% 1,004,904 27.71% 557,419 29.34% 224,617 27.37% 308,300 17.43%
Not malignant cancer/Unknown (60-99) 0 0.0% 0 0.0% 0 0.0% 0 0.0% 0 0.0% 184,675 10.44%
SEER Registry ABFFS Cohort MA Cohort Part D Cohort Both ABFFS & Part D Cohorts Both MA & Part D Cohorts Neither ABBFS/MA/Part D Cohorts
N Col % N Col % N Col % N Col % N Col % N Col %
Alaska 2,724 0.06% 4 0.0% 1,034 0.03% 966 0.05% 4 0.00% 895 0.05%
California (combined) 814,485 16.49% 212,601 25.20% 839,984 23.16% 347,510 18.29% 209,768 25.56% 478,399 27.05%
Connecticut 162,196 3.28% 23,929 2.84% 106,326 2.93% 59,250 3.12% 23,614 2.88% 44,552 2.52%
Detroit 172,004 3.48% 29,710 3.52% 110,401 3.04% 57,236 3.01% 28,285 3.45% 47,128 2.66%
Georgia (combined) 311,790 6.31% 59,768 7.08% 226,179 6.24% 116,089 6.11% 58,808 7.17% 76,520 4.33%
Hawaii 33,314 0.67% 11,896 1.41% 36,095 1.00% 11,634 0.61% 11,610 1.41% 23,396 1.32%
Idaho 56,472 1.14% 10,683 1.27% 39,590 1.09% 20,144 1.06% 9,784 1.19% 14,193 0.80%
Illinois 549,077 11.12% 53,059 6.29% 312,007 8.60% 213,126 11.22% 51,294 6.25% 131,984 7.46%
Iowa 171,694 3.48% 13,558 1.61% 102,907 2.84% 76,355 4.02% 13,213 1.61% 31,948 1.81%
Kentucky 199,383 4.04% 28,247 3.35% 131,315 3.62% 79,054 4.16% 27,217 3.32% 43,859 2.48%
Louisiana 160,167 3.24% 28,590 3.39% 115,684 3.19% 58,313 3.07% 28,024 3.41% 48,324 2.73%
Massachusetts 268,519 5.44% 26,938 3.19% 166,881 4.60% 104,728 5.51% 26,344 3.21% 101,827 5.76%
New Jersey 419,358 8.49% 38,060 4.51% 249,830 6.89% 171,389 9.02% 37,150 4.53% 112,127 6.34%
New Mexico 56,573 1.15% 11,062 1.31% 42,822 1.18% 20,114 1.06% 10,712 1.31% 22,142 1.25%
New York 674,790 13.66% 133,419 15.81% 540,959 14.92% 254,894 13.42% 129,935 15.83% 283,134 16.01%
Seattle 165,382 3.35% 31,313 3.71% 111,424 3.07% 57,722 3.04% 27,092 3.30% 66,673 3.77%
Texas 658,701 13.34% 118,591 14.06% 448,318 12.36% 231,224 12.17% 115,778 14.11% 220,255 12.45%
Utah 62,869 1.27% 12,302 1.46% 45,022 1.24% 20,178 1.06% 11,994 1.46% 21,499 1.22%
Cancer Site ABFFS Cohort MA Cohort Part D Cohort Both ABFFS & Part D Cohorts Both MA & Part D Cohorts Neither ABBFS/MA/Part D Cohorts
N Col % N Col % N Col % N Col % N Col % N Col %
Breast 669,408 13.55% 126,170 14.95% 532,201 14.67% 277,822 14.62% 123,483 15.05% 163,027 9.22%
Lung and Bronchus 734,885 14.88% 114,917 13.62% 522,319 14.40% 278,738 14.67% 111,864 13.63% 270,805 15.31%
Colon 387,497 7.84% 49,607 5.88% 238,173 6.57% 124,588 6.56% 48,226 5.88% 125,243 7.08%
NHL 203,356 4.12% 34,174 4.05% 150,420 4.15% 80,433 4.23% 33,184 4.04% 59,094 3.34%
Uterus 113,656 2.30% 23,817 2.82% 94,911 2.62% 48,314 2.54% 23,297 2.84% 30,241 1.71%
Rectum 120,239 2.43% 15,560 1.84% 73,389 2.02% 37,512 1.97% 15,132 1.84% 37,436 2.12%
Oral Cavity and Pharynx 96,394 1.95% 18,382 2.18% 75,310 2.08% 39,422 2.07% 17,826 2.17% 25,763 1.46%
Pancreas 145,065 2.94% 28,077 3.33% 115,749 3.19% 60,580 3.19% 27,316 3.33% 67,814 3.83%
Myeloma 74,695 1.51% 15,131 1.79% 60,589 1.67% 30,632 1.61% 14,718 1.79% 24,514 1.39%
Other 2,394,303 48.47% 417,895 49.53% 1,763,717 48.63% 921,885 48.52% 405,580 49.42% 964,918 54.55%
Stage 1 ABFFS Cohort MA Cohort Part D Cohort Both ABFFS & Part D Cohorts Both MA & Part D Cohorts Neither ABBFS/MA/Part D Cohorts
N Col % N Col % N Col % N Col % N Col % N Col %
In situ 431,744 9.53% 83,777 9.93% 357,751 9.86% 193,955 10.21% 81,294 9.91% 89,009 5.58%
Localized 1,849,009 40.83% 346,991 41.13% 1,477,980 40.75% 772,983 40.68% 337,792 41.16% 453,863 28.44%
Regional 797,257 17.60% 148,654 17.62% 641,541 17.69% 332,771 17.51% 144,649 17.63% 208,166 13.04%
Distant 1,083,683 23.93% 209,628 24.85% 901,409 24.85% 469,712 24.72% 203,770 24.83% 368,856 23.11%
Benign/Borderline/Unknown 367,141 8.11% 54,680 6.48% 248,097 6.84% 130,505 6.87% 53,121 6.47% 475,965 29.83%
Residential Cenus Tract Median Income ABFFS Cohort MA Cohort Part D Cohort Both ABFFS & Part D Cohorts Both MA & Part D Cohorts Neither ABBFS/MA/Part D Cohorts
N Col % N Col % N Col % N Col % N Col % N Col %
Q1: <$43,426 1,166,711 23.62% 198,067 23.48% 840,100 23.16% 428,723 22.57% 193,251 23.55% 382,732 21.64%
Q2: $43,426-<$56,757 1,181,186 23.91% 206,456 24.47% 856,160 23.61% 435,345 22.91% 200,622 24.45% 407,924 23.06%
Q3: $56,757-<$75,715 1,169,325 23.67% 220,951 26.19% 891,001 24.57% 447,979 23.58% 214,412 26.13% 433,540 24.51%
Q4: $75,715+ 1,254,304 25.39% 196,459 23.28% 933,950 25.75% 527,734 27.78% 191,170 23.30% 436,011 24.65%
Unknown 167,972 3.40% 21,797 2.58% 105,567 2.91% 60,145 3.17% 21,171 2.58% 108,648 6.14%

1 Stage not available for 2000-2003 ID, NY, MA, IL, TX cases, excluded

Last Updated: 28 Jan, 2026