Catherine S Giess1, Aijia Wang2, Ivan K Ip2, Ronilda Lacson2, Sarvanez Pourjabbar3, Ramin Khorasani2. 1. Center for Evidence-Based Imaging, Department of Radiology, Harvard Medical School, Brigham and Women's Hospital, 75 Francis Street, Boston, Massachusetts. Electronic address: cgiess@bwh.harvard.edu. 2. Center for Evidence-Based Imaging, Department of Radiology, Harvard Medical School, Brigham and Women's Hospital, 75 Francis Street, Boston, Massachusetts. 3. Center for Evidence-Based Imaging, Department of Radiology, Harvard Medical School, Brigham and Women's Hospital, 75 Francis Street, Boston, Massachusetts; Current address: Department of Radiology & Biomedical Imaging, Yale University Medical Center, New Haven, Connecticut.
Abstract
OBJECTIVE: The aims of this study were to evaluate patient, radiologist, and examination characteristics affecting screening mammography recall rates in an academic breast imaging practice and to identify modifiable factors that could reduce recall variation. METHODS: This institutional review board-approved retrospective study included screening mammographic examinations in female patients interpreted by 13 breast imaging specialists at an academic center and two outpatient centers from October 1, 2012, to May 31, 2015. Patient demographics were extracted via electronic medical record. Natural language processing captured breast density, BI-RADS assignment, and current and prior screening examination findings. Radiologists' annual screening volumes, clinical experience, and concentration in breast imaging were calculated. Risk aversion, stress from uncertainty, and malpractice concerns were derived via survey. Univariate and multivariate analyses assessed patient, radiologist, and examination characteristics associated with likelihood of mammography recall. The Pearson product-moment correlation coefficient was used to assess the relationship between cancer detection rate and recall rate. RESULTS: Overall, 5,678 of 61,198 screening examinations (9.3%) were recalled. In multivariate analysis, patient and radiologist characteristics associated with higher odds of recall included patient's age < 50 years (P < .0001), prior mammographic findings (calcification [P < .0001], mass [P < .0001], higher density category [P < .0001]), baseline examination (P < .0001), annual reading volume < 1,250 examinations (P = .0282), and <10 years of experience (P = .0036). Radiologist's risk aversion, stress from uncertainty, malpractice concerns, and cancer detection rates were not associated with higher recall rates (r = -0.36, P = .23). CONCLUSIONS: In addition to patient and examination factors, screening recall variations were associated with radiologists' annual reading volume and experience. Interventions targeting radiologist factors (screening volumes, second review of potential recalls) may help reduce unwarranted variation in screening recall.
OBJECTIVE: The aims of this study were to evaluate patient, radiologist, and examination characteristics affecting screening mammography recall rates in an academic breast imaging practice and to identify modifiable factors that could reduce recall variation. METHODS: This institutional review board-approved retrospective study included screening mammographic examinations in female patients interpreted by 13 breast imaging specialists at an academic center and two outpatient centers from October 1, 2012, to May 31, 2015. Patient demographics were extracted via electronic medical record. Natural language processing captured breast density, BI-RADS assignment, and current and prior screening examination findings. Radiologists' annual screening volumes, clinical experience, and concentration in breast imaging were calculated. Risk aversion, stress from uncertainty, and malpractice concerns were derived via survey. Univariate and multivariate analyses assessed patient, radiologist, and examination characteristics associated with likelihood of mammography recall. The Pearson product-moment correlation coefficient was used to assess the relationship between cancer detection rate and recall rate. RESULTS: Overall, 5,678 of 61,198 screening examinations (9.3%) were recalled. In multivariate analysis, patient and radiologist characteristics associated with higher odds of recall included patient's age < 50 years (P < .0001), prior mammographic findings (calcification [P < .0001], mass [P < .0001], higher density category [P < .0001]), baseline examination (P < .0001), annual reading volume < 1,250 examinations (P = .0282), and <10 years of experience (P = .0036). Radiologist's risk aversion, stress from uncertainty, malpractice concerns, and cancer detection rates were not associated with higher recall rates (r = -0.36, P = .23). CONCLUSIONS: In addition to patient and examination factors, screening recall variations were associated with radiologists' annual reading volume and experience. Interventions targeting radiologist factors (screening volumes, second review of potential recalls) may help reduce unwarranted variation in screening recall.
Authors: Mattie Salim; Erik Wåhlin; Karin Dembrower; Edward Azavedo; Theodoros Foukakis; Yue Liu; Kevin Smith; Martin Eklund; Fredrik Strand Journal: JAMA Oncol Date: 2020-10-01 Impact factor: 31.777