Abstract

BackgroundAccurate indication classification is critical for obtaining unbiased estimates of colonoscopy effectiveness and quality improvement efforts, but there is a dearth of published systematic classification approaches. The objective of this study was to evaluate the effects of data-source and adjudication on indication classification and on estimates of the effectiveness of screening colonoscopy on late-stage colorectal cancer diagnosis risk.MethodsThis was an observational study in members of four U.S. health plans. Eligible persons (n = 1039) were age 55–85 and had been enrolled for 5 years or longer in their health plans during 2006–2008. Patients were selected based on late-stage colorectal cancer diagnosis in a case–control design; each case patient was matched to 1–2 controls by study site, age, sex, and health plan enrollment duration. Reasons for colonoscopies received in the 10-year period before the reference date were collected from three medical records sources (progress notes; referral notes; procedure reports) and categorized using an algorithm, with committee adjudication of some tests. We evaluated indication classification concordance before and after adjudication and used logistic regressions with the Wald Chi-square test to compare estimates of the effects of screening colonoscopy on late-stage colorectal cancer diagnosis risk for each of our data sources to the adjudicated indication.ResultsClassification agreement between each data-source and adjudication was 78.8-94.0% (weighted kappa = 0.53-0.72); the highest agreement (weighted kappa = 0.86-0.88) was when information from all data sources was considered together. The choice of data-source influenced the association between screening colonoscopy and late-stage colorectal cancer diagnosis; estimates based on progress notes were closest to those based on the adjudicated indication (% difference in regression coefficients = 2.4%, p-value = 0.98), as compared to estimates from only referral notes (% difference in coefficients = 34.9%, p-value = 0.12) or procedure reports (% difference in coefficients = 27.4%, p-value = 0.23).ConclusionThere was no single gold-standard source of information in medical records. The estimates of colonoscopy effectiveness from progress notes alone were the closest to estimates using adjudicated indications. Thus, the details in the medical records are necessary for accurate indication classification.

Highlights

  • Accurate indication classification is critical for obtaining unbiased estimates of colonoscopy effectiveness and quality improvement efforts, but there is a dearth of published systematic classification approaches

  • The algorithm-based colonoscopy indication was categorized as ‘unknown’ for 2.8% of tests when based on the procedure report, 10.7% when based on the progress notes, and 11.4% when based on the referral note (Figure 3A)

  • In patient-level analyses based on the algorithm-derived indications, a similar percentage of patients were classified as screening across the three data sources or ‘high-risk’ (Figure 3B)

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Summary

Introduction

Accurate indication classification is critical for obtaining unbiased estimates of colonoscopy effectiveness and quality improvement efforts, but there is a dearth of published systematic classification approaches. There is a critical need for valid comparative effectiveness studies of cancer screening tests, but this is often hampered by uncertainties about the exact reason for testing. The accurate determination and classification of the reasons for testing is crucial to the validity of observational studies of colonoscopy’s effectiveness and for guiding quality improvement efforts [15]. Assigning an indication may be difficult due to the multiplicity of reasons often recorded for a particular test or when common gastrointestinal symptoms, which have a low predictive value for CRC diagnosis, [19,20,21] are recorded at the time a colonoscopy is recommended or performed [15]. Colonoscopy indication derived from clinical or administrative data may be misclassified, leading to biased results in observational studies of screening colonoscopy effectiveness

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