© 2005 Oxford University Press
ARTICLE |
Physician Predictors of Mammographic Accuracy
Affiliations of authors: Departments of Radiology (RS-B, PC, CQ, EAS) and Epidemiology and Biostatistics (RS-B, PB, KK), University of California, San Francisco, CA; Center for Health Studies, Group Health Cooperative and Department of Biostatistics, University of Washington, Seattle, WA (DLM); Department of Radiology, University of New Mexico, Albuquerque, NM (RDR); Center for Research Design and Statistical Methods, University of Nevada School of Medicine, Applied Research Facility, Reno, NV (GC); Health Promotion Research, University of Vermont, College of Medicine, Burlington, VT (BG); General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, CA (KK)
Correspondence to: Rebecca Smith-Bindman, MD, Department of Radiology, University of California, San Francisco, 1600 Divisadero St., San Francisco, CA 94115 (e-mail: Rebecca.Smith-Bindman{at}Radiology.UCSF.Edu).
Background: The association between physician experience and the accuracy of screening mammography in community practice is not well studied. We identified characteristics of U.S. physicians associated with the accuracy of screening mammography. Methods: Data were obtained from the Breast Cancer Surveillance Consortium and the American Medical Association Master File. Unadjusted mammography sensitivity and specificity were calculated according to physician characteristics. We modeled mammography sensitivity and specificity by multivariable logistic regression as a function of patient and physician characteristics. All statistical tests were two-sided. Results: We studied 209 physicians who interpreted 1 220 046 screening mammograms from January 1, 1995, through December 31, 2000, of which 7143 (5.9 per 1000 mammograms) were associated with breast cancer within 12 months of screening. Each physician interpreted a mean of 6011 screening mammograms (95% confidence interval [CI] = 4998 to 6677), including a mean of 34 (95% CI = 28 to 40) from women diagnosed with breast cancer. The mean sensitivity was 77% (range = 29%–97%), and the mean false-positive rate was 10% (range = 1%–29%). After adjustment for the patient characteristics of those whose mammograms they interpreted, physician characteristics were strongly associated with specificity. Higher specificity was associated with at least 25 years (versus less than 10 years) since receipt of a medical degree (for physicians practicing for 25–29 years, odds ratio [OR] = 1.54, 95% CI = 1.14 to 2.08; P = .006), interpretation of 2500–4000 (versus 481–750) screening mammograms annually (OR = 1.30, 95% CI = 1.06 to 1.59; P = .011) and a high focus on screening mammography compared with diagnostic mammography (OR = 1.59, 95% CI = 1.37 to 1.82; P<.001). Higher overall accuracy was associated with more experience and with a higher focus on screening mammography. Compared with physicians who interpret 481–750 mammograms annually and had a low screening focus, physicians who interpret 2500–4000 mammograms annually and had a high screening focus had approximately 50% fewer false-positive examinations and detected a few less cancers. Conclusion: Raising the annual volume requirements in the Mammography Quality Standards Act might improve the overall quality of screening mammography in the United States.
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