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False positive mammograms and detection controlled estimation
1Center for Health Care Policy and Research, The Pennsylvania State University, University Park, PA 16803, USA.
Objective:
To investigate the causes of false positive in mammograms.
Data Sources:
Secondary data collected from extracts from computerized medical records from 1999 from five thousand patients at a single hospital in a medium-sized Southern city.
Study Design:
Retrospective analysis of electronic medical data on screening and diagnostic mammograms. Detection-controlled estimation (DCE) was used to compare the efficacy of alternative readers of mammogram films. Analysis was also conducted on follow-up exams of women who tested positive in the first stage of investigation. Key variables included whether the patient had had a prior mammogram, age of the patient, and identifiers for the individual physicians.
Data Collection/Extraction Methods:
Hospital maintains electronic medical records (EMR) on all patients. Extracts were performed on this EMR system under the guidance of clinical expertise. Data were collected for all women who had mammograms in 1999. Random samples were employed for screening mammograms, and all data was used for diagnostic mammograms.
Principal Findings:
Study results imply that access to a previous mammogram greatly reduces the incidence of false positives readings. This has important consequences for benefit-cost, and cost-effectiveness analysis of mammography. Were previous mammograms always available, the results imply the number of false positives would decrease by at least half. The results here also indicate that there is no reason to believe this decrease in false positive would be accompanied by an increase in the number of false negatives. Other attributes also affected the number of false positives. Mondays and Wednesdays appear to be more prone to false positives than the other days in the week. There is also some disparity in false positive outcomes among the five physicians studied. With respect to detection-controlled estimation, the results are mixed. With follow-up data, the DCE estimator appears to generate reasonable, robust results. Without follow-up data, however, the DCE estimator is far less precise.
Conclusions:
Study results imply that access to a previous mammogram reduces by at least half the incidence of false positives readings. This has important consequences for benefit-cost, and cost-effectiveness analysis of mammography.