An algorithm for the use of medicare claims data to identify women with incident breast cancer

Health Services Research, Dec, 2004 by Ann B. Nattinger, Purushottam W. Laud, Ruta Bajorunaite, Rodney A. Sparapani, Jean L. Freeman

The quality of cancer care in the United States is known to be variable, and factors determining quality of cancer care have been insufficiently studied (Hewitt and Simone 1999). The development of methods for using existing databases to study the quality of cancer care would be a major advance (Hewitt and Simone 2000). Methods to permit the use of Medicare administrative databases to study cancer quality of care would be particularly helpful because about 60 percent of persons diagnosed with cancer are aged 65 and older (Hewitt and Simone 2000), and the Medicare claims data represent a nearly population-based source of data.

With respect to breast cancer specifically, several challenges have been identified in the use of Medicare claims in studying the care provided. The use of inpatient Medicare claims to identify incident breast cancer cases offers excellent specificity but poor sensitivity because 30-40 percent of initial breast cancer operations are done on an outpatient basis (Warren et al. 1999; Warren et al. 1996). Inpatient records are also more likely to identify patients undergoing mastectomy for initial therapy than those undergoing breast-conserving surgery (Warren et al. 1996; Cooper et al. 2000). Compared to inpatient data alone, the use of combined inpatient, outpatient, and physician claims increases sensitivity to 80-90 percent (Freeman et al. 2000; Cooper et al. 1999), but decreases specificity (Warren et al. 1999; Freeman et al. 2000). Because only a small percentage of the female Medicare population develops breast cancer in a given year, even small decreases in specificity lead to large decreases in the positive predictive value (PPV) (Freeman et al. 2000).

Our major goal in the development of this algorithm was to identify a cohort of incident breast cancer patients, whose surgical, medical, and follow-up care could be studied over time. Inherent in this goal was a requirement for a high positive predictive value (PPV), ensuring that a high percentage of the cohort was made up of true breast cancer patients. The requirement for a high PPV was considered more important than the algorithm's sensitivity, particularly for the small percentage (6-7 percent) of women not undergoing initial surgical therapy. However, we also considered important the consistency of the algorithm's sensitivity across subgroups defined by geographic location, age, and type of initial surgery undergone (breast-conserving surgery [BCS] or mastectomy.)

The prior work of the other investigators cited had adequately demonstrated that a relatively simple algorithm (generally consisting of the identification of a claim with a coincident breast cancer diagnosis and operative procedure) would not permit us to achieve our goal. Our strategy was to use an interaction of clinical rationale and statistical analysis in developing the four-step algorithm presented herein.

METHODS

Sources of Data

The key data source for this study was the linked SEER-Medicare database (SEER-Medicare Linked Database 2003). This database links information from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) tumor registries and the Centers for Medicare and Medicaid Services (CMS) Medicare claims data. The population-based SEER registries cumulatively represent about 14 percent of the U.S. population, and include information on incident cancer patients, such as demographics, month and year of diagnosis, extent of disease, and initial treatment undergone. The Medicare files required for this study include the Medicare Provider Analysis and Review (MEDPAR) file, which contains inpatient hospital claims; Outpatient file, which contains claims from institutional outpatient providers including hospital ambulatory surgery centers; the Carrier Claims (previously known as Part B Physician/Supplier File), which contains inpatient and outpatient claims from noninstitutional providers such as physicians, as well as stand-alone ambulatory surgical centers; and the Denominator file, which contains beneficiary demographic information and Medicare entitlement and enrollment information. About 94 percent of the SEER registry patients aged 65 and older were successfully linked with their Medicare claims (Potosky et al. 1993). An additional data source was a 5 percent random sample of Medicare beneficiaries residing in the SEER geographic areas, including an indicator for whether the individual linked to the SEER database. When SEER subjects are removed from this sample, it represents nearly a population-based random sample of cancer-free control subjects residing in SEER areas. This study was approved by the Medical College of Wisconsin Human Subjects Research Review Committee.

Training and Validation Datasets

Training Set: Incident Breast Cancer Cases. A cohort of women aged 65 or older at the time of diagnosis of breast cancer in 1995 (according to SEER) was developed. Cases were excluded if the diagnosis was made only at autopsy or by death certificate. Subjects were required to meet the following criteria for the period from January 1995 to March 1996: eligibility for Medicare Parts A and B, not in a Medicare HMO, and to be alive. Eligibility through the first quarter of 1996 was required to capture Medicare treatment information for patients who were diagnosed near the end of 1995, but treated early in 1996. These criteria resulted in a cohort of 7,700 women, whose 1995 Medicare claims comprised the training set for incident breast cancer cases.