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Adding Comorbidity Data to the Hawai‘i SEER Registry for Kaiser Permanente Hawai‘i Members
HMO Research Network Annual Meeting
April 30, 2012
Mark C. Hornbrook, PhD and Joan Holup, MAThe Center for Health Research, Kaiser Permanente
Marsha E. Reichman, PhD, MPHThe Food and Drug Administration
Marc T. Goodman, PhD, MPHCancer Research Center of Hawai‘i, University of Hawai‘i
Robin Yabroff, PhDDCCPS, National Cancer Institute
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Research Site
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Project Team
CHR Hawai‘i Aileen Uchida, MPH Mark M. Schmidt
SEER Hawai‘i (Hawai‘i Tumor Registry, Cancer Research Center of Hawai‘i) Michael Green, CTR Alan Y. Mogi, CDP
IMS Inc. Jennifer Stevens
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Funding and IRB
National Cancer Institute IRB approvals
KP Hawai‘i KP Northwest delegated to KPH University of Hawai‘i
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Why?
A cancer registry focuses exclusively on malignancies, which can generate an incomplete picture of the patient’s health state
New developments in health informatics make it feasible and affordable to extract and transfer comorbidity data to a disease registry Cancer can be examined within the context of
other significant health problems
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Comorbidities
Comorbidities may influence medical decisionmaking “Numerous biologic ties between cancer and
comorbidity exist, one example being an association of diabetes with an increased risk of disease recurrence and mortality in the setting of colon cancer.”
Need to understand the role of comorbidities on cancer treatment and outcomes to personalize care and derive optimal benefit
Pal SK, Hurria A. Impact of age, sex, and comorbidity on cancer therapy and disease progression. J Clin Oncol. 2010 Sep 10;28(26):4086-93. Epub 2010 Jul 19.
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Aims—SEER
Develop and test pathway for up-loading comorbidity data on KPH cancer patients to the Hawai‘i SEER Registry
To illustrate the utility of comorbidity data to a cancer or other disease registry
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Challenges
IRB issues Data linkage issues
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Human Subjects Protection Issues
Univ. of Hawai‘i Committee on Human Studies, IRB for Hawai‘i SEER (Hawaii Tumor Registry) Approved receipt of PHI and comorbidity data from KPH Did not approve sending PHI for KPH cancer cases not
recorded by KPH for their members
KPH IRB Since KPH is already sending PHI to HTR, approval provided
to resubmit PHI (for linking purposes) with additional diagnosis and medication comorbidity variables
Did not approve releasing PHI for patients NOT reported to the Hawai‘i Tumor Registry
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Phase I: PHI File—KPH to HTR
Match and reconcile KPH records to HTR records for cancer diagnosed between January 1, 2000 and December 31, 2008
Tabulate KPH comorbidities by tumor to match with HTR tumor records
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980
1,134 1,132 1,0901,201
1,2761,173 1,224 1,179
0
200
400
600
800
1000
1200
1400
2000 2001 2002 2003 2004 2005 2006 2007 2008
KPH Tumor Records Sent to HTR, 2000-2008
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Perfect Fuzzy0
1000
2000
3000
4000
5000
6000
7000
8000
6935
2611
73%
17%
Number of Matches: KPH to HTR
Matching Keys: Site, Histology, Behavior, Laterality, Date of Diagnosis
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94% 94% 94% 92% 89% 91% 92% 89% 92% 92%
0%10%20%30%40%50%60%70%80%90%
100%
2000 2001 2002 2003 2004 2005 2006 2007 2008 All Years
KPH Tumor Records Matched to HTR Using Dx Date, Name, Birth Date, and Other PHI, 2000-2008
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© 2012, KAISER PERMANENTE CENTER FOR HEALTH RESEARCH
1 2 3 4 5 6 7 8 90%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
776 866 846739 786
783 692 678769
142 205 219265 287
381 388411
313
62 63 67 86 128 112 93 135 97
50 41 59 72 84 150 134 155 172
Perfect Match (KPH to HTR) Fuzzy Match (KPH to HTR)Unmatched, on KPH file, not HTR Unmatched, on HTR file, not KPH
Matching Tumor Records
2000 2001 2002 2003 2004 2005 2006 2007 2008
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Comorbidity Measurement
12 months 1 month
Cancer Diagnosed
Comorbidity Assessment Period
One-month gap between comorbidity assessment period and date of cancer diagnosis reduces influence of cancer-related “rule-out” diagnoses on comorbidity measure.
Treatment
1
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Charlson-Deyo Comorbidity Classes
Myocardial infarction Congestive heart disease Peripheral vascular
disease Cerebrovascular disease Dementia Chronic obstructive
pulmonary disease Rheumatoid arthritis
Rheumatoid arthritis Peptic ulcer disease Mild liver disease Diabetes Diabetes complications Paralysis Renal disease Severe liver disease
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Presence of Comorbid Diagnoses by Cancer Site
Cancer SiteTotal # of Tumors
% of Tumors with Comorbidity
All Sites 9,546 37%
Respiratory & Intra-thoracic 1,133 54%
Colon & Rectum 1,110 40%
Prostate 1,080 37%
Breast 1,832 25%
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Frequency of Comorbid DiagnosesTotal Number of Tumors 9,546 100%
Number of Tumors with C-D Comorbidities 3,503 37%
Total C-D Comorbidities 6,018 100%
Serious Chronic Conditions Number Percent
Diabetes Mellitus 1,578 26%
Chronic Obstructive Pulmonary Disease 1,487 25%
Complications of Diabetes Mellitus 585 10%
Renal Disease 486 8%
Cerebrovascular Disease 458 8%
Congestive Heart Disease 413 7%
Myocardial Infarction 269 4%
Peripheral Vascular Disease 280 5%
36%
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Cancers of Digestive Organs
Digestive Organs# of
Tumors
# of Tumors with
Comorbidities# of
ComorbiditiesComorbidities
per Tumor
All Digestive System sites 1,110 448 804 1.8
Pelvic/Sigmoid/Sigmoid Flexure (C187) 260 90 152 1.7
Rectum (C209) 259 85 154 1.8
Ascending/Right (C182) 140 77 153 2.0
Cecum (C180) 121 47 81 1.7
Rectosigmoid/Colon and Rectum (C199) 109 38 55 1.4
Descending/Left (C186) 63 40 81 2.0
Transverse (C184) 62 28 55 2.0
Hepatic Flexure (C183) 39 21 34 1.6
Splenic Flexure (C185) 37 16 32 2.0
Appendix (C181) 10 2 2 1.0
Colon, NOS (C189) 7 3 4 1.3
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Comorbidities of Digestive System CancersTotal Number of Digestive Organ Tumors 1,843
Number of Digestive Organ Tumors with C-D Comorbidities 807
C-D Comorbidities Number
Diabetes Mellitus 417
Chronic Obstructive Pulmonary Disease 274
Complications of Diabetes Mellitus 152
Renal Disease 105
Cerebrovascular Disease 104
Congestive Heart Disease 101
Myocardial Infarction 72
Peripheral Vascular Disease 67
Peptic Ulcer Disease 52
Mild Liver Disease 50
Dementia 25
Severe Liver Disease 17
Rheumatoid Arthritis 14
Paralysis 7
Total C-D Comorbidities 1,450
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Implications
SEER registries should have comorbidity data Reporting laws may need amending Matching algorithms should include two-way
sharing of linkage files to identify and resolve linkage errors
Matching by patient attributes only is not sufficient Matching must include tumor attributes
Site, histology, behavior, laterality, date of diagnosis (year/month)
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