Journal of the American College of Radiology : JACR · 2016
Challenges With Identifying Indication for Examination in Breast Imaging as a Key Clinical Attribute in Practice, Research, and Policy.
Сравнительное исследованиеОценочное исследованиеСтатьяМногоцентровое исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Weiss Julie E, Goodrich Martha, Harris Kimberly A, Chicoine Rachael E, Synnestvedt Marie B, Pyle Steve J, Chen Jane S, Herschorn Sally D, Beaber Elisabeth F, Haas Jennifer S, Tosteson Anna N A, Onega Tracy, PROSPR (Population-based Research Optimizing Screening through Personalized Regimens) consortium
Аннотация
PURPOSE: To assess indication for examination for four breast imaging modalities and describe the complexity and heterogeneity of data sources and ascertainment methods.
METHODS: Indication 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).
RESULTS: The 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).
CONCLUSIONS: Multiple 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.
METHODS: Indication 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).
RESULTS: The 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).
CONCLUSIONS: Multiple 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.