scholarly journals Linking physician attitudes to their breast cancer screening practices: A survey of US primary care providers and gynecologists

2018 ◽  
Vol 107 ◽  
pp. 90-102 ◽  
Author(s):  
Archana Radhakrishnan ◽  
Sarah A. Nowak ◽  
Andrew M. Parker ◽  
Kala Visvanathan ◽  
Craig E. Pollack
2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 1550-1550
Author(s):  
Anne Hudson Blaes ◽  
Rachel Isaksson Vogel ◽  
Nancy Raymond ◽  
Kristine Talley ◽  
Alicia Allen ◽  
...  

1550 Background: Little literature exists on primary care providers’ knowledge and preferences towards breast cancer screening for high-risk women. While guidelines recommend MRI and mammography, it is unclear how frequently these recommendations are used. Methods: This web-based survey of providers licensed to practice in Minnesota was conducted. This analysis focuses on breast cancer screening practices for high-risk women. Data were summarized using descriptive statistics; professional characteristic comparisons were conducted using Chi-squared tests. Results: 805 of 10,392 (8%) invitees completed the survey. 72.2% were female. 43.9% were physicians (20.8% internists, 71.7% family medicine, 6.3% gynecology), 11.4% physician assistants (PAs), 44.8% advanced practice registered nurses (APRNs). 84.8% were in community practice, 38% > 20 years of experience and 27.1% < 10 years. When asked how effective screening was for reducing cancer mortality in high risk women, mammography was thought to be very effective (48.8%) or effective (46.8%) in women ages 40-49 years, for women ages 50+ years, 60.8% and 35.7%, respectively. 62.4% thought breast MRI was very effective in reducing cancer mortality in high risk women. There was no difference in breast MRI recommendation based on professional background, experience or practice setting. Female practitioners, less experience, and those working in gynecology or women’s health were more likely to recommend breast MRI. A case vignette for high risk screening cancer survivors is provided (Table). Conclusions: Most primary care providers believe mammography is helpful in women at high risk for developing breast cancer. Less than half of practitioners, however, are following guideline specific recommendations of both mammography and MRI for breast cancer screening in high-risk patients. [Table: see text]


2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e13037-e13037
Author(s):  
Deanna Gek Koon Teoh ◽  
Rachel Isaksson Vogel ◽  
Alicia Allen ◽  
Anne Hudson Blaes ◽  
Susan Mason ◽  
...  

e13037 Background: Breast cancer screening guidelines disagree on the age to initiate and discontinue screening. We sought to determine the age at which Minnesota providers initiate and discontinue breast cancer screening. Methods: A cross-sectional online survey of Minnesota primary care providers was conducted in 2016. The survey queried providers’ breast screening practices for average-risk women. Data were summarized using descriptive statistics and comparisons by professional characteristics were conducted using Chi-squared tests. Results: There were 805 respondents (8% of 10,392 invitees), of which 456 (56.7%) provided primary care to women and were included in the analysis. 316 (72%) were women, 193 (44%) were physicians, 50 (11%) were physician assistants (PAs), and 197 (45%) were advanced practice nurses (APNs). 85% practiced in a community setting. 38% had practiced > 20 years, and 27% had practiced < 10 years. Among respondents, 67%, 77% and 72% recommended screening mammography for women age 40-44, 45-49 and 70+ years, respectively. Compared to male providers, female providers were more likely to screen women age 40-44 years (73% vs. 49%; p < 0.0001) and 45-49 years (81% vs. 66%; p = 0.002), but there was no difference by gender for patients age 70+ years (72% vs. 74%; p = 0.89). Respondents reporting specialized interest in women’s health were more likely to screen women age 40-44 years (73% vs. 61%; p = 0.006), 45-49 years (83% vs 72%; p = 0.007) and older than age 70 years (77% vs. 69%; p = 0.04). Physicians were less likely to screen women age 40-44 and 45-49 years (57% and 71%, respectively; p = 0.001) than PAs (72%, 78%) and APNs (74%, 83%), but APNs were less likely to screen women age 70+ years (65% vs. physicians 79% vs. PAs 76%; p = 0.006). Number of years in practice was not associated with a difference in age at initiation of screening, however, increasing number of years in practice was associated with screening women age 70+ years (p = 0.02). Conclusions: Although breast cancer screening practices for average risk women vary by healthcare provider characteristics, a majority of Minnesota primary care providers initiate breast cancer screening between ages 40-49 years, and continue screening women age 70 years and older.


2020 ◽  
Vol 35 (9) ◽  
pp. 2553-2559
Author(s):  
Emily Nachtigal ◽  
Noelle K. LoConte ◽  
Sarah Kerch ◽  
Xiao Zhang ◽  
Amanda Parkes

2020 ◽  
Vol 29 (5) ◽  
pp. 686-692
Author(s):  
Anne Blaes ◽  
Rachel I. Vogel ◽  
Rebekah H. Nagler ◽  
Alicia Allen ◽  
Susan Mason ◽  
...  

Author(s):  
Nathaniel Hendrix ◽  
Brett Hauber ◽  
Christoph I Lee ◽  
Aasthaa Bansal ◽  
David L Veenstra

Abstract Background Artificial intelligence (AI) is increasingly being proposed for use in medicine, including breast cancer screening (BCS). Little is known, however, about referring primary care providers’ (PCPs’) preferences for this technology. Methods We identified the most important attributes of AI BCS for ordering PCPs using qualitative interviews: sensitivity, specificity, radiologist involvement, understandability of AI decision-making, supporting evidence, and diversity of training data. We invited US-based PCPs to participate in an internet-based experiment designed to force participants to trade off among the attributes of hypothetical AI BCS products. Responses were analyzed with random parameters logit and latent class models to assess how different attributes affect the choice to recommend AI-enhanced screening. Results Ninety-one PCPs participated. Sensitivity was most important, and most PCPs viewed radiologist participation in mammography interpretation as important. Other important attributes were specificity, understandability of AI decision-making, and diversity of data. We identified 3 classes of respondents: “Sensitivity First” (41%) found sensitivity to be more than twice as important as other attributes; “Against AI Autonomy” (24%) wanted radiologists to confirm every image; “Uncertain Trade-Offs” (35%) viewed most attributes as having similar importance. A majority (76%) accepted the use of AI in a “triage” role that would allow it to filter out likely negatives without radiologist confirmation. Conclusions and Relevance Sensitivity was the most important attribute overall, but other key attributes should be addressed to produce clinically acceptable products. We also found that most PCPs accept the use of AI to make determinations about likely negative mammograms without radiologist confirmation.


BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jeanette C. Reece ◽  
Eleanor F. G. Neal ◽  
Peter Nguyen ◽  
Jennifer G. McIntosh ◽  
Jon D. Emery

Abstract Background Successful breast cancer screening relies on timely follow-up of abnormal mammograms. Delayed or failure to follow-up abnormal mammograms undermines the potential benefits of screening and is associated with poorer outcomes. However, a comprehensive review of inadequate follow-up of abnormal mammograms in primary care has not previously been reported in the literature. This review could identify modifiable factors that influence follow-up, which if addressed, may lead to improved follow-up and patient outcomes. Methods A systematic literature review to determine the extent of inadequate follow-up of abnormal screening mammograms in primary care and identify factors impacting on follow-up was conducted. Relevant studies published between 1 January, 1990 and 29 October, 2020 were identified by searching MEDLINE®, Embase, CINAHL® and Cochrane Library, including reference and citation checking. Joanna Briggs Institute Critical Appraisal Checklists were used to assess the risk of bias of included studies according to study design. Results Eighteen publications reporting on 17 studies met inclusion criteria; 16 quantitative and two qualitative studies. All studies were conducted in the United States, except one study from the Netherlands. Failure to follow-up abnormal screening mammograms within 3 and at 6 months ranged from 7.2–33% and 27.3–71.6%, respectively. Women of ethnic minority and lower education attainment were more likely to have inadequate follow-up. Factors influencing follow-up included physician-patient miscommunication, information overload created by automated alerts, the absence of adequate retrieval systems to access patient’s results and a lack of coordination of patient records. Logistical barriers to follow-up included inconvenient clinic hours and inconsistent primary care providers. Patient navigation and case management with increased patient education and counselling by physicians was demonstrated to improve follow-up. Conclusions Follow-up of abnormal mammograms in primary care is suboptimal. However, interventions addressing amendable factors that negatively impact on follow-up have the potential to improve follow-up, especially for populations of women at risk of inadequate follow-up.


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