Challenges With Identifying Indication for Examination in Breast Imaging as a Key Clinical Attribute in Practice, Research, and Policy

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• 作者：Julie E. Weiss ; MS^a ; ^b ; ^{julie.weiss@dartmouth.edu} ; Martha Goodrich ; MS^a ; ^b ; Kimberly A. Harris ; MM^c ; Rachael E. Chicoine ; BS^d ; Marie B. Synnestvedt ; PhD^e ; Steve J. Pyle ; MSE^a ; Jane S. Chen ; ScB^c ; Sally D. Herschorn ; MD^d ; ^f ; Elisabeth F. Beaber ; PhD^g ; Jennifer S. Haas ; MD ; MS^c ; ⁱ ; ^j ; Anna N.A. Tosteson ; ScD^b ; ^h ; Tracy Onega ; PhD ; MA ; MS^a ; ^b ; ^h ; on behalf of the PROSPR (Population-based Research Optimizing Screening through Personalized Regimens) consortium
• 关键词：Indication for examination ; data source ; digital mammography ; digital breast tomosynthesis ; ultrasound ; magnetic resonance imaging
• 刊名：Journal of the American College of Radiology
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：14
• 期：2
• 页码：198-207.e2
• 全文大小：1346 K
• 卷排序：14

文摘

To assess indication for examination for four breast imaging modalities and describe the complexity and heterogeneity of data sources and ascertainment methods.MethodsIndication was evaluated among the Population-based Research Optimizing Screening through Personalized Regimens (PROSPR) breast cancer research centers (PRCs). Indication data were reported overall and separately for four breast imaging modalities: digital mammography (DM), digital breast tomosynthesis (DBT), ultrasound (US), and magnetic resonance imaging (MRI).ResultsThe breast PRCs contributed 236,262 women with 607,735 breast imaging records from 31 radiology facilities. We found a high degree of heterogeneity for indication within and across six data sources. Structured codes within a data source were used most often to identify indication for mammography (59% DM, 85% DBT) and text analytics for US (45%) and MRI (44%). Indication could not be identified for 17% of US and 26% of MRI compared with 2% of mammography examinations (1% DM, 3% DBT).ConclusionsMultiple and diverse data sources, heterogeneity of ascertainment methods, and nonstandardization of codes within and across data systems for determining indication were found. Consideration of data sources and standardized methodology for determining indication is needed to assure accurate measurement of cancer screening rates and performance in clinical practice and research.