Analysis of a claims database for the identification of patients with carcinoma of the breast

Solin, Lawrence J.; Legorreta, Antonio P.; Schultz, Delray; Levin, Howard A.; Zatz, Steven; Goodman, Robert L.

doi:10.1007/bf00999321

Cited by 42 publications

(20 citation statements)

References 14 publications

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“…[10][11][12][13][14][15][16][17][18][19] Freeman et al 17) obtained a high sensitivity (90%) and specificity (99%), but a low PPV (70%). In their discussion, they attributed the high sensitivity to the use of three kinds of claims data (inpatients, outpatients, and physician services), while the low PPV was considered to be due to limitations in distinguishing recurrent and secondary cancers.…”

Section: Discussionmentioning

confidence: 99%

“…We identified the definitions which were capable of identifying breast cancer cases from the claims database with high sensitivity, specificity, and PPV. Because we had no information on the Japanese codes used in the claims of breast cancer patients prior to the construction of definitions, we developed exploratory definitions by reference to previous studies [10][11][12][13][14][15][16][17][18][19] and using advice from experts in the area. We then evaluated each definition and attempted to determine the optimal combination of three validity measures (sensitivity, specificity, and PPV).…”

Section: Discussionmentioning

confidence: 99%

“…[10][11][12][13][14][15][16][17][18][19] For example, Freeman et al 17) determined the optimal combination of predictors (e.g., diagnosis, procedures) using a logistic regression model to identify the incidence of breast cancer from a population-based cancer registry and Medicare claims data, which included data of inpatients, outpatients, and physician services. Setoguchi et al 10) developed case definitions to identify 6 types of cancer cases using multiple combinations of predictors in Pennsylvania, using Medicare claims data linked to pharmacy dispensing data and the population-based cancer registry.…”

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confidence: 99%

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The Accuracy of Japanese Claims Data in Identifying Breast Cancer Cases

2015

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In use of a claims database for a study, an inaccurate diagnosis of breast cancer based on claims data may lead to invalid study results. The aim of this study was to assess the accuracy of definitions for identifying breast cancer cases from the Japanese claims database. The study cohort consisted of women with no prior cancer-related history, from the claims data at a single institution between January 1 and December 31, 2011. We developed 14 definitions for identifying breast cancer based on claims data, using a combination of diagnosis codes and treatment procedure codes. We calculated the sensitivity, specificity, and positive predictive value (PPV) of each definition, compared to cases identified from the standardized hospital-based cancer registry as a standard reference. A total of 50056 women were included in the study cohort from the claims database. We identified 633 breast cancer cases from the cancer registry. Of 14 definitions, 12 exhibited higher sensitivity than 90%, while the others exhibited lower sensitivity than 40%. The specificities of all definitions were high (≥99%), and the PPVs were between 65.8 and 90.7%. We selected the most optimal definition obtained from combinations of diagnosis and cancer treatment codes (surgery, chemotherapy, medication, radiation procedure), which had high values for sensitivity (90.4%), specificity (99.8%), and PPV (87.3%). Definitions obtained via combinations of the diagnosis codes and procedure codes could be used to accurately identify breast cancer cases from the claims database. Further studies in a multi-institutional setting are planned to confirm our results.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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The Accuracy of Japanese Claims Data in Identifying Breast Cancer Cases

2015

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“…We relied solely on administrative data, which, although generally accurate in studies of cancer care, could not be independently verified. [65][66][67][68] The Florida AHCA, for example, does not have a system for validating treatment information contained in discharge abstracts. It was not possible to ascertain all patient comorbidities, nor their individual severities, from administrative data.…”

Section: Discussionmentioning

confidence: 99%

Effects of health insurance and race on colorectal cancer treatments and outcomes

Roetzheim

Pal²,

Gonzalez³

et al. 2000

Am J Public Health

214

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OBJECTIVES: We hypothesized that health insurance payer and race might influence the care and outcomes of patients with colorectal cancer. METHODS: We examined treatments received for all incident cases of colorectal cancer occurring in Florida in 1994 (n = 9551), using state tumor registry data. We also estimated the adjusted risk of death (through 1997), using proportional hazards regression analysis controlling for other predictors of mortality. RESULTS: Treatments received by patients varied considerably according to their insurance payer. Among non-Medicare patients, those in the following groups had higher adjusted risks of death relative to commercial fee-for-service insurance: commercial HMO (risk ratio [RR] = 1.40; 95% confidence interval [CI] = 1.18, 1.67; P = .0001), Medicaid (RR = 1.44; 95% CI = 1.06, 1.97; P = .02), and uninsured (RR = 1.41; 95% CI = 1.12, 1.77; P = .003). Non-Hispanic African Americans had higher mortality rates (RR = 1.18; 95% CI = 1.01, 1.37; P = .04) than non-Hispanic Whites. CONCLUSIONS: Patients with colorectal cancer who were uninsured or insured by Medicaid or commercial HMOs had higher mortality rates than patients with commercial fee-for-service insurance. Mortality was also higher among non-Hispanic African American patients.

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“…The validity of these approaches is supported by further evidence that 1) cancer is a diagnosis reliably coded on hospital billing records [40] and 2) algorithms to estimate cancer incidence rates from hospital claims have produced estimated rates similar to those of cancer registries [20][21]. However, attempts to identify specific cases of breast cancer (as distinguished from overall incidence rates) using administrative data have raised concerns about the claims' ability to identify individual subjects with incident disease, particularly with hospital data alone [23,41].…”

Section: Introductionmentioning

confidence: 95%

The Elevated Breast Cancer Mortality in the Northeastern U.S. is Secondary to Poorer Survival Rather Than Increased Incidence

Goodwin¹

1999

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Public reporting burden for ft» corlectx»i of infcrmaeon i» estimated to average 1 hour per response, including the time for nwiew^ instructions. Matching existing data sources, gatrmng and maintaining the data needed and ujinp>e«ng and reviewing this ooHecaon of Monnation. Send oannw* regarding »« burden «el»IIa» or any other aspect ot this cc«oclion of intormaly^.itKliidii^ suggestions for reducing this burden to Washington Headquarters Service*. Directorate for Information Operations and Reports, 1215 Jefferson Davis highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188), Washington. DC 20503 AGENCY USE ONLY (Leave blank)2. REPORT DATE December 1999 REPORT TYPE AND DATES COVEREDFinal (1 Aug 97 -15 Nov 99) TITLE AND SUBTITLEThe Elevated Breast Cancer Mortality in the Northeastern U.S. is Secondary to Poorer Survival Rather Than Increased Incidence.6. AUTHOR(S) James S. Goodwin, M.D. FUNDING NUMBERS DAMD17-97-1-7095 PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)University of Texas Medical Branch at Galveston Galveston, Texas 77555-0136 E-MAIL:jsgo(xlwi@utmb.edu Mortality rates for breast cancer are approximately 25% higher in the northeast U.S. than the south or west. Virtually all previous investigations into this phenomenon have assumed that the elevated mortality rates reflect elevated incidence, and this putative elevation in incidence has been attributed to a number of factors. We hypothesized that the geographic variation in breast cancer mortality was secondary to differences in survival with breast cancer as well as differences in incidence. We proposed to test this by identifying women aged > 70 years newly diagnosed with breast cancer in 1991 in different regions of the country using Medicare charge data and assessing their survival. Initially we developed algorithms to determine incident breast cancer and date of diagnosis from the Medicare data and validating them using the SEER-Medicare linked data base. We found that an algorithm incorporating data from hospital inpatient, hospital outpatient, and physician services claims produced levels of sensitivity and specificity > 90%. However, the positive prediction value was low (67 to 70 percent), precluding use of Medicare data alone to examine survival from breast cancer. Our current work is using SEER-Medicare linked data to examine geographic variation in incidence, survival and mortality of women with breast cancer. PERFORMING ORGANIZATION REPORT NUMBER SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES)U SUBJECT TERMSBreast cancer survival; geographic variation; incidence; older women; Medicare data Where copyrighted material is quoted, permission has been obtained to use such material.Where material from documents designated for limited distribution is quoted, permission has been obtained to use the material.Citations of commercial organizations and trade names in this report do not constitute an official Department of Army endorsement or approval of the products or s...

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Analysis of a claims database for the identification of patients with carcinoma of the breast

Cited by 42 publications

References 14 publications

The Accuracy of Japanese Claims Data in Identifying Breast Cancer Cases

The Accuracy of Japanese Claims Data in Identifying Breast Cancer Cases

Effects of health insurance and race on colorectal cancer treatments and outcomes

The Elevated Breast Cancer Mortality in the Northeastern U.S. is Secondary to Poorer Survival Rather Than Increased Incidence

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