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Medicine and Public Policy |

Discordance of Databases Designed for Claims Payment versus Clinical Information Systems: Implications for Outcomes Research

James G. Jollis, MD; Marek Ancukiewicz, PhD; Elizabeth R. DeLong, PhD; David B. Pryor, MD; Lawrence H. Muhlbaier, PhD; and Daniel B. Mark, MD, MPH
[+] Article and Author Information

From Duke University Medical Center, Durham, North Carolina. Requests for Reprints: James G. Jollis, MD, Box 3254, Duke University Medical Center, Durham, NC 27710. Grant Support: By grants HS-06503 and HS-05635 from the Agency for Health Care Policy and Research; grant HL-17670 from the National Heart, Lung, and Blood Institute; and a grant from the Robert Wood Johnson Foundation. Dr. Jollis was an American College of Cardiology Merck Research Fellow during the course of this research. Acknowledgments: The authors thank Patrick S. Romano, MD, MPH, and Leslie L. Roos, PhD, who designed the ICD-9-CM mapping system used in the Patient Outcomes Research Team for ischemic heart disease; the other members of the Patient Outcomes Research Team for ischemic heart disease for their comments on earlier versions of this work; and Lloyd Hedgpeth and his staff in the Duke Medical Center Information System for providing the insurance claims data for this study.


Copyright 2004 by the American College of Physicians


Ann Intern Med. 1993;119(8):844-850. doi:10.7326/0003-4819-119-8-199310150-00011
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Objective: To determine the suitability of insurance claims information for use in clinical outcomes research in ischemic heart disease.

Design: Concordance study of two databases.

Setting: Tertiary care referral center.

Patients: A total of 12 937 consecutive patients hospitalized for cardiac catheterization for suspected ischemic heart disease between July 1985 and May 1990.

Interventions: Two-by-two tables were used to compute overall and measures of agreement comparing clinical versus claims data for 12 important predictors of prognosis in patients with ischemic heart disease.

Measurements: Kappa statistics (agreement adjusted for chance agreement) were used to quantify agreement rates.

Results: Agreement rates between the clinical and claims databases ranged from 0.83 for the diagnosis of diabetes to 0.09 for the diagnosis of unstable angina ( values). Claims data failed to identify more than one half of the patients with prognostically important conditions, including mitral insufficiency, congestive heart failure, peripheral vascular disease, old myocardial infarction, hyperlipidemia, cerebrovascular disease, tobacco use, angina, and unstable angina, when compared with the clinical information system.

Conclusions: Our results suggest that insurance claims data lack important diagnostic and prognostic information when compared with concurrently collected clinical data in the study of ischemic heart disease. Thus, insurance claims data are not as useful as clinical data for identifying clinically relevant patient groups and for adjusting for risk in outcome studies, such as analyses of hospital mortality.

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