Journal Article

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

Lip, Gerald, Díaz, Magdalena Rzewuska, Bruhn, Hanne, Ramsay, Craig, Anderson, Lesley A., Newlands, Rumana

2024

Overview

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: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Algorithm / Algorithms / Artificial Intelligence / Breast / Breast cancer / Breast Neoplasms - diagnosis / Cancer / Care and treatment / COVID-19 - diagnosis / COVID-19 - epidemiology / Diagnosis / Early Detection of Cancer - methods / Evaluation / Female / Focus Groups / Health Administration / Health aspects / Health boards / Health care reform / Health Informatics / Humans / Medical screening / Medicine / Medicine & Public Health / Nursing Research / Oncology, Experimental / Patients / Public Health / Qualitative Research / Safety and security measures / SARS-CoV-2 / Scotland / Screening / Stakeholder analysis / Stakeholder Participation / United Kingdom / Womens health