Patient, Radiologist, and Examination Characteristics Affecting Screening Mammography Recall Rates in a Large Academic Practice

Giess, Catherine S.; Wang, Aijia; Ip, Ivan K.; Lacson, Ronilda; Pourjabbar, Sarvanez; Khorasani, Ramin

doi:10.1016/j.jacr.2018.06.016

Cited by 26 publications

(14 citation statements)

References 32 publications

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“…However, Giess et al found that concerns about malpractice and individual risk tolerance did not increase screening mammography recall rates. ( 13 ) Similarly, Elmore et al showed that medical malpractice experience or concerns were not associated with mammography recall or false-positive rates( 16 ) Understanding the actual reasons that lead some radiologists to make follow-up recommendations more frequently requires further investigation preferably with large numbers of radiologists from multiple institutions. Our study also contrasts with previous work showing that radiologists with greater years of experience made fewer follow-up recommendations( 5 ).…”

Section: Discussionmentioning

confidence: 99%

“…For example, malpractice fears or risk intolerance could lead some radiologists to make more follow-up recommendations. However, Giess et al (13) found that concerns about malpractice and individual risk tolerance did not increase screening mammography recall rates. Similarly, Elmore et al (16) showed that medical malpractice experience or concerns were not associated with mammography recall or rates of false-positive findings.…”

Section: Multivariable Analysis By Divisionmentioning

confidence: 97%

“…Prior literature performed at single institutions and in single subspecialty divisions has suggested that radiologist experience may be associated with fewer follow-up recommendations. ( 5 , 13 ). However, it remains poorly understood how much radiologists vary when making recommendations for additional imaging and what additional radiologist and other factors influence the likelihood of additional imaging.…”

Section: Introductionmentioning

confidence: 99%

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Variation in Follow-up Imaging Recommendations in Radiology Reports: Patient, Modality, and Radiologist Predictors

et al. 2019

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A critical part of interpreting radiologic images is determining the need for potential follow-up imaging. Reported rates of follow-up recommendations in radiology reports range 8%-37% (1-6) with high rates of interobserver variability (7). Even radiology reports with noncritical findings may contain recommendations for further imaging by using different modalities or recommendations for interval followup by using the same modality (5). Furthermore, there are known differences in radiologists' familiarity and adherence with evidence-based guidelines (8-10). This may lead to unnecessary additional tests in the follow-up of incidental or ambiguous imaging findings (11,12). A better understanding of follow-up recommendations in radiology reports is needed, as are clear identification of factors that might account for variation in rates of follow-up recommendations. Previous studies (5,13) performed at single institutions and in single subspecialty divisions have suggested that radiologist experience may be associated with fewer follow-up recommendations. However, it remains poorly understood how much radiologists vary when recommending additional imaging and what additional radiologists and other factors influence the likelihood of additional imaging. We hypothesized there is a large amount of likely unwarranted variation among radiologists in terms of the probability of making a follow-up recommendation. Therefore, we sought to identify factors associated with follow-up recommendations in radiology reports from multiple modalities, patient care settings, and imaging divisions to better evaluate features associated with a higher number of follow-up recommendations.

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Section: Discussionmentioning

confidence: 99%

Section: Multivariable Analysis By Divisionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

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Variation in Follow-up Imaging Recommendations in Radiology Reports: Patient, Modality, and Radiologist Predictors

et al. 2019

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“…While mammography remains the mainstay for post-BCT surveillance [1], falsepositive findings that necessitate recall and additional procedures occur [10,11]. Digital breast tomosynthesis (DBT), an adjunct to digital mammography (DM), images the breasts in multiple thin planes, thereby reducing the effect of superimposed tissues that produce falsepositive recalls on DM [10,12].…”

Section: Introductionmentioning

confidence: 99%

Mammographic Surveillance After Breast-Conserving Therapy: Impact of Digital Breast Tomosynthesis and Artificial Intelligence–Based Computer-Aided Detection

Yoon

Kim

et al. 2022

American Journal of Roentgenology

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The publication of this Accepted Manuscript is provided to give early visibility to the contents of the article, which will undergo additional copyediting, typesetting, and review before it is published in its final form. During the production process, errors may be discovered that could affect the content of the Accepted Manuscript. All legal disclaimers that apply to the journal pertain. The reader is cautioned to consult the definitive version of record before relying on the contents of this document.

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“…In this direction, a recent meta-analysis suggests that breast tomosynthesis can improve cancer detection rates and decrease recall rates compared to traditional 2D mammography (6). Finally, double versus single reading, geographic location of the readers and particularly, radiologists' reading volume and experience have also been linked to differences in results and recall rates of screening programs (4,7,8). Clearly, there is room for improvement in several aspects of this screening approach.…”

mentioning

confidence: 99%

External validation of AI algorithms in breast radiology: the last healthcare security checkpoint?

Martín-Noguerol

Luna

2021

Quant Imaging Med Surg

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Patient, Radiologist, and Examination Characteristics Affecting Screening Mammography Recall Rates in a Large Academic Practice

Cited by 26 publications

References 32 publications

Variation in Follow-up Imaging Recommendations in Radiology Reports: Patient, Modality, and Radiologist Predictors

Variation in Follow-up Imaging Recommendations in Radiology Reports: Patient, Modality, and Radiologist Predictors

Mammographic Surveillance After Breast-Conserving Therapy: Impact of Digital Breast Tomosynthesis and Artificial Intelligence–Based Computer-Aided Detection

External validation of AI algorithms in breast radiology: the last healthcare security checkpoint?

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