OBJECTIVE: To assess the utility of survey-based physician policy in predicting actual mammography ordering behavior, as measured by medical record abstraction. DESIGN: Cross-sectional survey of practicing community physicians. Responses were correlated with data abstracted from the medical records of patients in the practices of the participating physicians. PARTICIPANTS: Family and general practitioners in Washington State. Medical records of female patients aged 40 to 80 years provided data on actual mammography performance. MAIN OUTCOME MEASURES: The proportions of female patients aged 40 to 49 and 50 to 80 years who had received a screening mammogram within the previous 2 years. RESULTS: Of the more than 100 potential predictors available, only 4 were significantly associated with screening rates for women younger than 50 years and only 3 were associated with screening rates for older women. Regression models explained only 21% to 25% of the variance in screening rates. Physician estimates of screening rates were poorly correlated with actual screening rates. CONCLUSIONS: Practicing physicians do not know how well they screen their patients using mammography. Extensive survey data, including direct estimates of behavior, demographics, policy measures, and case scenario responses, were of limited use in predicting actual screening rates. Our results underscore the importance of using data rather than proxy measures to study physician performance.
OBJECTIVE: To assess the utility of survey-based physician policy in predicting actual mammography ordering behavior, as measured by medical record abstraction. DESIGN: Cross-sectional survey of practicing community physicians. Responses were correlated with data abstracted from the medical records of patients in the practices of the participating physicians. PARTICIPANTS: Family and general practitioners in Washington State. Medical records of female patients aged 40 to 80 years provided data on actual mammography performance. MAIN OUTCOME MEASURES: The proportions of female patients aged 40 to 49 and 50 to 80 years who had received a screening mammogram within the previous 2 years. RESULTS: Of the more than 100 potential predictors available, only 4 were significantly associated with screening rates for women younger than 50 years and only 3 were associated with screening rates for older women. Regression models explained only 21% to 25% of the variance in screening rates. Physician estimates of screening rates were poorly correlated with actual screening rates. CONCLUSIONS: Practicing physicians do not know how well they screen their patients using mammography. Extensive survey data, including direct estimates of behavior, demographics, policy measures, and case scenario responses, were of limited use in predicting actual screening rates. Our results underscore the importance of using data rather than proxy measures to study physician performance.
Authors: Joshua J Fenton; Joseph Egger; Patricia A Carney; Gary Cutter; Carl D'Orsi; Edward A Sickles; Jessica Fosse; Linn Abraham; Stephen H Taplin; William Barlow; R Edward Hendrick; Joann G Elmore Journal: AJR Am J Roentgenol Date: 2006-07 Impact factor: 3.959
Authors: Henry Brodaty; Louisa Hr Gibson; Melissa L Waine; Allan M Shell; Ruth Lilian; Constance Dimity Pond Journal: Ment Health Fam Med Date: 2013-09
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