A stakeholder analysis to prepare for real-world evaluation of integrating artificial intelligent algorithms into breast screening (PREP-AIR study): a qualitative study using the WHO guide

Author:

Newlands Rumana1,Bruhn Hanne1,Díaz Magdalena Rzewuska1,Lip Gerald2,Anderson Lesley A.1,Ramsay Craig1

Affiliation:

1. University of Aberdeen

2. NHS Grampian

Abstract

Abstract

Background The national breast screening programme in the United Kingdom is under pressure due to workforce shortages and having been paused during the COVID-19 pandemic. Artificial intelligence has the potential to transform how healthcare is delivered by improving care processes and patient outcomes. Research on the clinical and organisational benefits of artificial intelligence is still at an early stage, and numerous concerns have been raised around its implications, including patient safety, acceptance, and accountability for decisions. Reforming the breast screening programme to include artificial intelligence is a complex endeavour because numerous stakeholders influence it. Therefore, a stakeholder analysis was conducted to identify relevant stakeholders, explore their views on the proposed reform (i.e., integrating artificial intelligence algorithms into the Scottish National Breast Screening Service for breast cancer detection) and develop strategies for managing ‘important’ stakeholders. Methods A qualitative study (i.e., focus groups and interviews, March-November 2021) was conducted using the stakeholder analysis guide provided by the World Health Organisation and involving three Scottish health boards: NHS Greater Glasgow & Clyde, NHS Grampian and NHS Lothian. The objectives included: A) Identify possible stakeholders B) Explore stakeholders’ perspectives and describe their characteristics C) Prioritise stakeholders in terms of importance and D) Develop strategies to manage ‘important’ stakeholders. Seven stakeholder characteristics were assessed: their knowledge of the targeted reform, position, interest, alliances, resources, power and leadership. Results Thirty-two participants took part from 14 (out of 17 identified) sub-groups of stakeholders. While they were generally supportive of using artificial intelligence in breast screening programmes, some concerns were raised. Stakeholder knowledge, influence and interests in the reform varied. Key advantages mentioned include service efficiency, quicker results and reduced work pressure. Disadvantages included overdiagnosis or misdiagnosis of cancer, inequalities in detection and the self-learning capacity of the algorithms. Five strategies (with considerations suggested by stakeholders) were developed to maintain and improve the support of ‘important’ stakeholders. Conclusions Health services worldwide face similar challenges of workforce issues to provide patient care. The findings of this study will help others to learn from Scottish experiences and provide guidance to conduct similar studies targeting healthcare reform. Study registration: researchregistry6579, date of registration: 16/02/2021

Publisher

Research Square Platform LLC

Reference40 articles.

1. UK NSC. Criteria for a population screening programme. 2022; Available at: https://www.gov.uk/government/publications/evidence-review-criteria-national-screening-programmes/criteria-for-appraising-the-viability-effectiveness-and-appropriateness-of-a-screening-programme#the-screening-programme. Accessed May.

2. NHS B. NHS breast screening (BSP) programme. Available at: https://www.gov.uk/topic/population-screening-programmes/breast. Accessed 22/11/22.

3. National Health Service (NHS) Inform. Breast Screening in Scotland. May, 2022; Available at: https://www.nhsinform.scot/healthy-living/screening/breast/breast-screening. Accessed 24, May, 2022.

4. NICE. Artificial intelligence in mammography. 2021.

5. Public Health Scotland. Breast Screening. December, 2021; Available at: http://www.healthscotland.scot/health-topics/screening/breast-screening. Accessed May, 2022.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3