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Showing content from https://pubmed.ncbi.nlm.nih.gov/22922433/ below:

Distinguishing screening from diagnostic mammograms using Medicare claims data

doi: 10.1097/MLR.0b013e318269e0f5. Distinguishing screening from diagnostic mammograms using Medicare claims data

Affiliations

Affiliation

¹ *Departments of Family and Community Medicine, Radiology, and the Center for Healthcare Research and Policy, University of California-Davis, Sacramento, CA †Group Health Research Institute, Seattle, WA ‡Departments of Radiology, Epidemiology and Biostatistics, University of California-San Francisco, San Francisco, CA §Department of Biostatistics, University of Washington, Seattle, WA.

PMID: 22922433
PMCID: PMC3534834
DOI: 10.1097/MLR.0b013e318269e0f5

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Distinguishing screening from diagnostic mammograms using Medicare claims data

Joshua J Fenton et al. Med Care. 2014 Jul.

doi: 10.1097/MLR.0b013e318269e0f5. Affiliation

¹ *Departments of Family and Community Medicine, Radiology, and the Center for Healthcare Research and Policy, University of California-Davis, Sacramento, CA †Group Health Research Institute, Seattle, WA ‡Departments of Radiology, Epidemiology and Biostatistics, University of California-San Francisco, San Francisco, CA §Department of Biostatistics, University of Washington, Seattle, WA.

PMID: 22922433
PMCID: PMC3534834
DOI: 10.1097/MLR.0b013e318269e0f5

Item in Clipboard

Abstract

Background: Medicare claims data may be a fruitful data source for research or quality measurement in mammography. However, it is uncertain whether claims data can accurately distinguish screening from diagnostic mammograms, particularly when claims are not linked with cancer registry data.

Objectives: To validate claims-based algorithms that can identify screening mammograms with high positive predictive value (PPV) in claims data with and without cancer registry linkage.

Research design: Development of claims-derived algorithms using classification and regression tree analyses within a random half-sample of bilateral mammogram claims with validation in the remaining half-sample.

Subjects: Female fee-for-service Medicare enrollees aged 66 years and older, who underwent bilateral mammography from 1999 to 2005 within Breast Cancer Surveillance Consortium (BCSC) registries in 4 states (CA, NC, NH, and VT), enabling linkage of claims and BCSC mammography data (N=383,730 mammograms obtained from 146,346 women).

Measures: Sensitivity, specificity, and PPV of algorithmic designation of a "screening" purpose of the mammogram using a BCSC-derived reference standard.

Results: In claims data without cancer registry linkage, a 3-step claims-derived algorithm identified screening mammograms with 97.1% sensitivity, 69.4% specificity, and a PPV of 94.9%. In claims that are linked to cancer registry data, a similar 3-step algorithm had higher sensitivity (99.7%), similar specificity (62.7%), and higher PPV (97.4%).

Conclusions: Simple algorithms can identify Medicare claims for screening mammography with high predictive values in Medicare claims alone and in claims linked with cancer registry data.

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Conflict of interest statement

Conflicts of Interest : None declared.

Figures
Figure 1

Allocation of mammograms by screening…

Figure 1

Allocation of mammograms by screening vs. diagnostic purpose using the three-step algorithm for…

Figure 1

Allocation of mammograms by screening vs. diagnostic purpose using the three-step algorithm for claims without linkage to cancer registry data

Figure 2

Allocation of mammograms by screening…

Figure 2

Allocation of mammograms by screening vs. diagnostic purpose using the three-step algorithm for…

Figure 2

Allocation of mammograms by screening vs. diagnostic purpose using the three-step algorithm for mammography claims with linkage to cancer registry data