Are physicians social networks linked to breast cancer screening recommendations for older adults?

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 6550-6550 ◽  
Author(s):  
Craig Evan Pollack ◽  
Archana Radhakrishnan ◽  
Andrew M Parker ◽  
Kala Visvanathan ◽  
Sarah A Nowak
Keyword(s):  
Breast Cancer ◽  
Social Networks ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Poor Prognosis ◽  
Family Members ◽  
Primary Care Providers ◽  
Good Prognosis ◽  
Average Risk ◽  
Care Providers

6550 Background: Physicians’ prior experiences caring for patients with breast cancer along with experiences in their social networks including family members and friends may be a key and understudied driver of recommendations for cancer screening. Methods: The Breast Cancer Social Networks study (CanSNET) is a national, mailed survey of 2,000 primary care providers (PCPs) randomly selected from the American Medical Association Masterfile. PCPs were asked to provide detailed characteristics on up to 2 women they know who have been diagnosed with breast cancer and “whose cancer, broadly speaking, had the greatest impact” on them, including friends, family members and patients. Each woman was categorized as being diagnosed (a) through screening with a good prognosis, (b) not through screening with a good prognosis, (c) through screening with a poor prognosis or (d) not through screening with a poor prognosis. We used a logistic regression model to assess the association between the network member and recommendations for routine screening mammograms to average-risk women ages 75+, adjusting for provider and practice characteristics. Results: Overall 871 physicians responded to the survey yielding an adjusted response rate of 52.3% (out of 1665 eligible). We found that 67% of physicians recommended screening for women 75+. The sample reported on 762 patients, 378 family members and 476 other network members who had been diagnosed with breast cancer. Ten percent of patients and 25.1% of family members reported on died of their disease. In adjusted models, we found that physicians who reported on family members who did not receive a mammogram and had a poor prognosis were significantly more likely to recommend screening compared to those who did not (Odds Ratio 1.22, 95% Confidence Interval 1.03, 1.43). Conclusions: Physicians’ experiences with their social networks was linked to their breast cancer screening recommendations, underscoring the potential for information that is learned from social networks to differ from clinical guidelines and highlighting the need to address a broad array of influences in trying to reduce potential over-screening in cancer.

Minnesota healthcare providers’ breast cancer screening practices at the extremes of age.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e13037-e13037
Author(s):  
Deanna Gek Koon Teoh ◽  
Rachel Isaksson Vogel ◽  
Alicia Allen ◽  
Anne Hudson Blaes ◽  
Susan Mason ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Primary Care ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Online Survey ◽  
Primary Care Providers ◽  
Screening Methods ◽  
Average Risk ◽  
Care Providers ◽  
Screening Practices

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.

scholarly journals Variation in Breast Cancer Screening Recommendations by Primary Care Providers Surveyed in Wisconsin

2020 ◽  
Vol 35 (9) ◽  
pp. 2553-2559
Author(s):  
Emily Nachtigal ◽  
Noelle K. LoConte ◽  
Sarah Kerch ◽  
Xiao Zhang ◽  
Amanda Parkes
Keyword(s):  
Breast Cancer ◽  
Primary Care ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Primary Care Providers ◽  
Care Providers

Breast cancer screening practices with high-risk women: A cross-sectional survey.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 1550-1550
Author(s):  
Anne Hudson Blaes ◽  
Rachel Isaksson Vogel ◽  
Nancy Raymond ◽  
Kristine Talley ◽  
Alicia Allen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Primary Care ◽  
Cancer Screening ◽  
High Risk ◽  
Breast Cancer Screening ◽  
Breast Mri ◽  
Primary Care Providers ◽  
Care Providers ◽  
Screening Practices ◽  
High Risk Women

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]

scholarly journals Using Mixed Methods With Multiple Stakeholders to Inform Development of a Breast Cancer Screening Decision Aid for Women With Limited Health Literacy

2021 ◽  
Vol 6 (2) ◽  
pp. 238146832110332
Author(s):  
Christine M. Gunn ◽  
Ariel Maschke ◽  
Michael K. Paasche-Orlow ◽  
Ashley J. Housten ◽  
Nancy R. Kressin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Health Literacy ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Primary Care Providers ◽  
Safety Net ◽  
Informational Needs ◽  
Care Providers ◽  
Limited Health Literacy ◽  
Limited Health

Background. When stakeholders offer divergent input, it can be unclear how to prioritize information for decision aids (DAs) on mammography screening. Objectives. This analysis triangulates perspectives (breast cancer screening experts, primary care providers [PCPs], and patients with limited health literacy [LHL]) to understand areas of divergent and convergent input across stakeholder groups in developing a breast cancer screening DA for younger women with LHL. Design. A modified online Delphi panel of 8 experts rated 57 statements for inclusion in a breast cancer screening DA over three rounds. Individual interviews with 25 patients with LHL and 20 PCPs from a large safety net hospital explored informational needs about mammography decision making. Codes from the qualitative interviews and open-ended responses from the Delphi process were mapped across stakeholders to ascertain areas where stakeholder preferences converged or diverged. Results. Four themes regarding informational needs were identified regarding 1) the benefits and harms of screening, 2) different screening modalities, 3) the experience of mammography, and 4) communication about breast cancer risk. Patients viewed pain as the primary harm, while PCPs and experts emphasized the harm of false positives. Patients, but not PCPs or experts, felt that information about the process of getting a mammogram was important. PCPs believed that mammography was the only evidence-based screening modality, while patients believed breast self-exam was also important for screening. All stakeholders described incorporating personal risk information as important. Limitations. As participants came from one hospital, perceptions may reflect local practices. The Delphi sample size was small. Conclusions. Patients, experts, and PCPs had divergent views on the most important information needed for screening decisions. More evidence is needed to guide integration of multiple stakeholder perspectives into the content of DAs. [Box: see text]

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
Keyword(s):  
Breast Cancer ◽  
Primary Care ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Primary Care Providers ◽  
Physician Attitudes ◽  
Care Providers ◽  
Screening Practices

scholarly journals Artificial intelligence in breast cancer screening: primary care provider preferences

2020 ◽  
Author(s):  
Nathaniel Hendrix ◽  
Brett Hauber ◽  
Christoph I Lee ◽  
Aasthaa Bansal ◽  
David L Veenstra
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Primary Care ◽  
Decision Making ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Primary Care Providers ◽  
Latent Class Models ◽  
Supporting Evidence ◽  
Care Providers

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.

Provider preferences for attributes of artificial intelligence in breast cancer screening: A discrete choice experiment.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e14118-e14118
Author(s):  
Nathaniel Hendrix ◽  
A. Brett Hauber ◽  
Christoph I. Lee ◽  
Aasthaa Bansal ◽  
David Leroy Veenstra
Keyword(s):  
Breast Cancer ◽  
Artificial Intelligence ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Qualitative Interviews ◽  
Primary Care Providers ◽  
Care Providers

e14118 Background: One of the emerging medical applications of artificial intelligence (AI) is the interpretation of mammograms for breast cancer screening. It is uncertain what attributes would result in acceptance of AI for breast cancer screening (AI BCS) among ordering clinicians. Methods: We performed qualitative interviews to identify the most important attributes of AI BCS for ordering clinicians. We then invited US-based primary care providers (PCPs) to participate in a discrete choice experiment (DCE). The experiment featured 15 choices between radiologist alone and two AI BCS alternatives where respondents traded better metrics on some attributes for worse metrics on others. Responses were analyzed using a mixed logit model adjusting for preference heterogeneity to determine the probability of recommending AI BCS. Results: In qualitative interviews, the six most important attributes to PCPs were AI sensitivity, specificity, radiologist involvement, understandability of AI decision-making, supporting evidence, and diversity of training data. Forty PCPs completed the DCE. Sensitivity was the most important attribute: a 4 percentage point improvement in sensitivity over the average radiologist increased the probability of recommending AI by 0.41 (95% confidence interval (CI), 0.38-0.42). Specificity was approximately half as important. Respondents were indifferent to whether radiologists confirmed all or only screens likely to be abnormal. However, no radiologist involvement reduced the probability of recommendation by 0.31 (95% CI, 0.29-0.31). An AI developed using data from diverse populations increased the probability of recommendation by 0.38 (95% CI, 0.36-0.39). Lastly, an AI that is transparent in the rationale for its decisions increased the probability of recommendation by 0.41 (95% CI, 0.39-0.41). Conclusions: PCPs prefer AI BCS that improves sensitivity versus specificity, and involves radiologists in the confirmation of abnormal screens. Improving sensitivity alone, however, will likely not be sufficient to support widespread PCP acceptance – algorithms will need to be developed with diverse data and more transparent explanations of their decisions.

scholarly journals Delayed or failure to follow-up abnormal breast cancer screening mammograms in primary care: a systematic review

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jeanette C. Reece ◽  
Eleanor F. G. Neal ◽  
Peter Nguyen ◽  
Jennifer G. McIntosh ◽  
Jon D. Emery
Keyword(s):  
Breast Cancer ◽  
Primary Care ◽  
Cancer Screening ◽  
Breast Cancer Screening ◽  
Primary Care Providers ◽  
The United States ◽  
Cochrane Library ◽  
Care Providers ◽  
Screening Mammograms

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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