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Colorectal Cancer Identification Methods Among Kansas Medicare Beneficiaries, 2008–2010

Colorectal Cancer Identification Methods Among Kansas Medicare Beneficiaries, 2008–2010

ORIGINAL RESEARCH — Volume 12 — July 9, 2015

Sue-Min Lai, PhD, MS, MBA; Jessica Jungk, MS, MPH; Sarma Garimella, MBBS, MPH

Suggested citation for this article: Lai S, Jungk J, Garimella S. Colorectal Cancer Identification Methods Among Kansas Medicare Beneficiaries, 2008–2010. Prev Chronic Dis 2015;12:140543. DOI:http://dx.doi.org/10.5888/pcd12.140543.

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On this Page

• Abstract
• Introduction
• Methods
• Results
• Discussion
• Acknowledgments
• Author Information
• References
• Tables

Abstract

Introduction

Population-based data are limited on how often colorectal cancer (CRC) is identified through screening or surveillance in asymptomatic patients versus diagnostic workup for symptoms. We developed a process for assessing CRC identification methods among Medicare-linked CRC cases from a population-based cancer registry to assess identification methods (screening/surveillance or diagnostic) among Kansas Medicare beneficiaries.

Methods

New CRC cases diagnosed from 2008 through 2010 were identified from the Kansas Cancer Registry and matched to Medicare enrollment and claims files. CRC cases were classified as diagnostic-identified versus screening/surveillance-identified using a claims-based algorithm for determining CRC test indication. Factors associated with screening/surveillance-identified CRC were analyzed using logistic regression.

Results

Nineteen percent of CRC cases among Kansas Medicare beneficiaries were screening/surveillance-identified while 81% were diagnostic-identified. Younger age at diagnosis (65 to 74 years) was the only factor associated with having screening/surveillance-identified CRC in multivariable analysis. No association between rural/urban residence and identification method was noted.

Conclusion

Combining administrative claims data with population-based registry records can offer novel insights into patterns of CRC test use and identification methods among people diagnosed with CRC. These techniques could also be extended to other screen-detectable cancers.

Figure. Identification method classification process and results for invasive colorectal cancer (CRC), Kansas Medicare beneficiaries, 2008–2010. “Ko algorithm” refers to classification and regression tree algorithm for colonoscopy indication (diagnostic vs average-risk screening/high-risk screening/surveillance) developed by Ko et al (10). [A text description of this figure is also available.]

Acknowledgments

This project was supported by the Kansas Department of Health and Environment and the National Program of Cancer Registries from CDC agreement no. U58/DP003889.

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Author Information

Corresponding Author: Sue-Min Lai, PhD, MS, MBA, Kansas Cancer Registry, Department of Preventive Medicine and Public Health, University of Kansas Medical Center, Mail Stop 1008, 3901 Rainbow Blvd, Kansas City, KS 66160-7313. Telephone: 913-588-2744. Email: slai@kumc.edu.

Author Affiliations: Jessica Jungk, Sarma Garimella, Kansas Cancer Registry, Department of Preventive Medicine and Public Health, University of Kansas Medical Center, Kansas City, Kansas.

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