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Determination of Colonoscopy Indication From Administrative Claims Data

Ko, Cynthia W. MD, MS*; Dominitz, Jason A. MD, MHS*,†; Neradilek, Moni MS; Polissar, Nayak PhD; Green, Pam PhD§; Kreuter, William MPA; Baldwin, Laura-Mae MD, MPH§

Medical Care:
doi: 10.1097/MLR.0b013e31824ebdf5
Applied Methods
Abstract

Background: Colonoscopy outcomes, such as polyp detection or complication rates, may differ by procedure indication.

Objectives: To develop methods to classify colonoscopy indications from administrative data, facilitating study of colonoscopy quality and outcomes.

Research Design: We linked 14,844 colonoscopy reports from the Clinical Outcomes Research Initiative, a national repository of endoscopic reports, to the corresponding Medicare Carrier and Outpatient File claims. Colonoscopy indication was determined from the procedure reports. We developed algorithms using classification and regression trees and linear discriminant analysis (LDA) to classify colonoscopy indication. Predictor variables included ICD-9CM and CPT/HCPCS codes present on the colonoscopy claim or in the 12 months prior, patient demographics, and site of colonoscopy service. Algorithms were developed on a training set of 7515 procedures, then validated using a test set of 7329 procedures.

Results: Sensitivity was lowest for identifying average-risk screening colonoscopies, varying between 55% and 86% for the different algorithms, but specificity for this indication was consistently over 95%. Sensitivity for diagnostic colonoscopy varied between 77% and 89%, with specificity between 55% and 87%. Algorithms with classification and regression trees with 7 variables or LDA with 10 variables had similar overall accuracy, and generally lower accuracy than the algorithm using LDA with 30 variables.

Conclusions: Algorithms using Medicare claims data have moderate sensitivity and specificity for colonoscopy indication, and will be useful for studying colonoscopy quality in this population. Further validation may be needed before use in alternative populations.

Author Information

*Department of Medicine, University of Washington

The VA Puget Sound Health Care System

Mountain-Whisper-Light Statistics

§Department of Family Medicine

Department of Rehabilitation Medicine, University of Washington, Seattle, Washington

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Supported by NIH grant CA127659. J.A.D. was supported by the American Society for Gastrointestinal Endoscopy Endoscopic Research Career Development Award. This material is based upon work supported in part by the VA Puget Sound Health Care System, Department of Veterans Affairs. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs.

The authors declare no conflict of interest.

Reprints: Cynthia W. Ko, MD, MS, Division of Gastroenterology, Box 356424, University of Washington, Seattle, WA 98195. E-mail: cwko@u.washington.edu.

© 2014 by Lippincott Williams & Wilkins.