scholarly journals Women’s attitudes to the use of AI image readers: a case study from a national breast screening programme

2021 ◽  
Vol 28 (1) ◽  
pp. e100293
Author(s):  
Niamh Lennox-Chhugani ◽  
Yan Chen ◽  
Veronica Pearson ◽  
Bernadette Trzcinski ◽  
Jonathan James
Keyword(s):  
Likelihood Ratio ◽  
Breast Screening ◽  
Clinical Settings ◽  
Cross Sectional ◽  
Breast Screening Programme ◽  
National Breast ◽  
Survey Responses ◽  
Positive Effect ◽  
Health Applications

BackgroundResearchers and developers are evaluating the use of mammogram readers that use artificial intelligence (AI) in clinical settings.ObjectivesThis study examines the attitudes of women, both current and future users of breast screening, towards the use of AI in mammogram reading.MethodsWe used a cross-sectional, mixed methods study design with data from the survey responses and focus groups. We researched in four National Health Service hospitals in England. There we approached female workers over the age of 18 years and their immediate friends and family. We collected 4096 responses.ResultsThrough descriptive statistical analysis, we learnt that women of screening age (≥50 years) were less likely than women under screening age to use technology apps for healthcare advice (likelihood ratio=0.85, 95% CI 0.82 to 0.89, p<0.001). They were also less likely than women under screening age to agree that AI can have a positive effect on society (likelihood ratio=0.89, 95% CI 0.84 to 0.95, p<0.001). However, they were more likely to feel positive about AI used to read mammograms (likelihood ratio=1.09, 95% CI 1.02 to 1.17, p=0.009).Discussion and ConclusionsWomen of screening age are ready to accept the use of AI in breast screening but are less likely to use other AI-based health applications. A large number of women are undecided, or had mixed views, about the use of AI generally and they remain to be convinced that it can be trusted.

Organisational readiness for the adoption of AI diagnostic tools in clinical workflows – a case study from the National Breast Screening Programme in the East Midlands of England. (Preprint)

2020 ◽  
Author(s):  
Niamh Lennox-Chhugani ◽  
Simon Harris ◽  
Jacqueline Moxon ◽  
Vipul Patel
Keyword(s):  
Real World ◽  
Breast Screening ◽  
Screening Programme ◽  
Decision Makers ◽  
Diagnostic Tools ◽  
Healthcare Organisation ◽  
Breast Screening Programme ◽  
The Real ◽  
National Breast

BACKGROUND Application of artificial intelligence (AI) in healthcare is accelerating but relatively little is yet known about the real-world implementation of AI in clinical workflows. OBJECTIVE In this paper, we have focused on one application of AI as a second reader of breast mammograms in the context of a national breast screening programme. We look at the development and testing of an AI image reading tool for mammograms and the effect of organisational readiness for AI tool adoption. We focus on two aspects of organisational readiness as conceptualised by Weiner (2009) for AI technology specifically and answer the questions (1) what are the views of the technology adopters in a healthcare organisation to the use of AI technology in the case of breast screening? (2) What are some of the emerging organisation factors that are likely to effect adoption and spread and are any unique to AI technology? METHODS A prospective mixed methods study of the real-world development of AI tools for use in the National Breast Screening Programme in England. We recruited 67 radiologists and reporting radiographers in four breast screening services and 18 organisational leaders who were the AI project decision-makers. Data was collected using an online survey of breast screening staff (adopters), semi-structured interviews with organisational leaders, participant observation of project meetings and document review. Data regarding organisational and adopter readiness for technology adoption was analysed over the duration of the project. RESULTS Sixty-seven clinicians and eighteen organisational leaders participated the study. Commitment to adoption is positive but adopters want to see clinical evidence of AI safety and accuracy. Decision-makers and other organisational adopters do not yet have shared views on their resources, capacity and capability to adopt and spread the technology and significant challenges related to task demands and situational factors emerged during the project causing substantial delays to adoption. The nature of AI and ML technology surfaced novel complexities not encountered by traditional health technology related to explainability and meaningful decision-support. CONCLUSIONS The case study shows that adopter commitment in this case and AI technology in breast screening is growing but gaps remain in the collective capability of organisations to adopt these novel technologies. CLINICALTRIAL Not applicable

scholarly journals Using Record Linkage to Examine the Impact of Poor Mental Health on Breast Screening Uptake

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Emma Ross ◽  
Dermot O'Reilly
Keyword(s):  
Mental Health ◽  
Breast Screening ◽  
Census Data ◽  
Breast Cancer Mortality ◽  
Poor Mental Health ◽  
Breast Screening Programme ◽  
Screening Uptake ◽  
National Breast ◽  
The Impact ◽  
Prescribing Information

BackgroundThe UK National Breast Screening Programme is estimated to reduce breast cancer mortality by 20%. To maximise the benefits of the programme, we first need to understand the underlying factors contributing to variations in screening uptake. One potentially significant factor which may contribute to these gradients in screening uptake is poor mental health. ObjectivesThe objectives of this study were to examine the impact of poor mental health on breast screening uptake, and whether this explained any of the previously observed socio-demographic gradients in screening uptake. MethodsBreast screening records were obtained from the National Breast Screening System (NBSS) and were subsequently linked to 2011 Census data within the Northern Ireland Longitudinal Study (NILS). The NILS encompasses 28\% of Census data. This was then linked to psychotropic prescribing information from the Enhanced Prescribing Database (EPD), to produce a de-identified research dataset containing 57,328 women. FindingsWomen with self-reported poor mental health were over 20% less likely to attend screening compared to their counterparts who didn't have poor mental health. Using psychotropic prescribing information as a proxy for the presence of mental illness yielded similar results, with those taking anxiolytics, antipsychotics or hypnotics in the three months before screening invitation significantly less likely to attend than those who were not. ConclusionWomen with poor mental health were significantly less likely to attend breast screening. However, poor mental health did not explain any of the previously determined socio-demographic gradients in screening uptake.

Evolution of the National Breast Screening Programme in Ireland: Two-year interval analysis (2004–2013) of BreastCheck

2017 ◽  
Vol 25 (4) ◽  
pp. 191-196 ◽  
Author(s):  
Patricia E Fitzpatrick ◽  
Gráinne Greehy ◽  
Marie T Mooney ◽  
Fidelma Flanagan ◽  
Aideen Larke ◽  
...  
Keyword(s):  
Cancer Detection ◽  
Digital Mammography ◽  
Carcinoma In Situ ◽  
Breast Screening ◽  
Screening Programme ◽  
Ductal Carcinoma ◽  
Detection Rates ◽  
Breast Screening Programme ◽  
National Breast

Objective Monitoring breast screening programmes is essential to ensure quality. BreastCheck, the national breast screening programme in the Republic of Ireland, commenced screening in 2000, with full national expansion in 2007, and digital mammography introduced in 2008. We aimed to review the performance of BreastCheck from 1 January 2004 to 31 December 2013. Methods Using the customised clinical and administrative database, performance indicator data were collected from BreastCheck and compared with programme and European guideline standards. Results Over the decade, 972,236 screening examinations were performed. Uptake initially rose following national expansion, but fell in the subsequent years to <70% in 2012–2013. Following the introduction of digital mammography, initial recall rates increased from 5.2% in 2004–2005 to 8.1% in 2012–2013. Subsequent recall rates remained within the target of <3%. On average, invasive cancer detection rates were 6.6/1000 for initial and 4.5/1000 for subsequent women. Small cancer detection rates were for <15 mm 43.4% (initial women) and 51.7% (subsequent) and for ≤10 mm 24.0% (initial) and 29.5% (subsequent). Ductal carcinoma in situ detection as a percentage of all cancers averaged 21.2% for initial and 20.0% for subsequent women. The majority were intermediate or high-grade ductal carcinoma in situ. The positive predictive value was 11.9% for initial and 21.8% for subsequent women. Standardized detection ratios remained above the programme target. Conclusion Revised indicators to reflect the digital mammography era are anticipated in revised European Guidelines on breast cancer screening.

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