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American Journal of Epidemiology Advance Access published online on April 3, 2007
American Journal of Epidemiology, doi:10.1093/aje/kwm034
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American Journal of Epidemiology Copyright © 2007 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.

Practice of Epidemiology

Using Probabilistic Corrections to Account for Abstractor Agreement in Medical Record Reviews

Timothy L. Lash1,2, Matthew P. Fox1, Soe Soe Thwin1,3, Ann M. Geiger4,5, Diana S. M. Buist6, Feifei Wei7, Terry S. Field8,9, Marianne Ulcickas Yood10,11, Floyd J. Frost12, Virginia P. Quinn5, Marianne N. Prout3 and Rebecca A. Silliman1,2,3

1 Boston University School of Public Health, Boston, MA
2 Boston University School of Medicine, Boston, MA
3 Boston Medical Center, Boston, MA
4 Wake Forest University School of Medicine, Winston-Salem, NC
5 Kaiser Permanente Southern California, Los Angeles, CA
6 Group Health Center for Health Studies, Seattle, WA
7 HealthPartners Research Foundation, Minneapolis, MN
8 University of Massachusetts Medical School, Worcester, MA
9 Fallon Community Health Plan, Worcester, MA
10 Henry Ford Health System, Detroit, MI
11 Yale University School of Medicine, New Haven, CT
12 Lovelace Health Systems, Albuquerque, NM

Correspondence to Dr. Timothy L. Lash, Department of Epidemiology, Boston University School of Public Health, 715 Albany Street, TE3, Boston, MA 02118 (e-mail: tlash{at}bu.edu).

Received for publication June 14, 2006. Accepted for publication December 6, 2006.

The quality of medical record abstracts is often characterized in a reliability substudy. These results usually indicate agreement, but not the extent to which lack of agreement affects associations observed in the complete data. In this study, medical records were reviewed and abstracted for patients diagnosed with stage I or stage II breast cancer between 1990 and 1994 at one of six US Cancer Research Network sites. For a subsample, interrater reliability data were available. The authors calculated conventional hazard ratios and 95% confidence intervals for the association of demographic, tumor, and treatment characteristics with recurrence rate. These conventional estimates of effect were compared with three sets of estimates and 95% simulation intervals that took account of the uncertainty assessed by lack of agreement in the reliability substudy. The rate of recurrence was associated with increasing cancer stage and with treatment modality but not with demographic characteristics. The hazard ratios and simulation intervals that took account of the reliability data showed that the simulation interval grew wider as the sources of uncertainty taken into account grew more complete, but the associations expected a priori remained readily apparent. While many investigators use reliability data only as a metric for data quality, a more thorough approach can also quantitatively depict the uncertainty in the observed associations.

breast neoplasms; data collection; epidemiologic methods; medical records

Abbreviations: CCI, Charlson comorbidity index; IRR, interrater reliability


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