Individual and neighborhood-level social and deprivation factors impact kidney health in the GLOMMS-CORE study.

Prospective cohort studies of kidney equity are limited by a focus on advanced rather than early disease and selective recruitment. Whole population studies frequently rely on area-level measures of deprivation as opposed to individual measures of social disadvantage. Here, we linked kidney health and individual census records in the North of Scotland (Grampian area), 2011-2021 (GLOMMS-CORE) and identified incident kidney presentations at thresholds of estimated glomerular filtration rate (eGFR) under 60 (mild/early), under 45 (moderate), under 30 ml/min/1.73m2 (advanced), and acute kidney disease (AKD). Household and neighborhood socioeconomic measures, living circumstances, and long-term mortality were compared. Case-mix adjusted multivariable logistic regression (living circumstances), and Cox models (mortality) incorporating an interaction between the household and the neighborhood were used. Among census respondents, there were 48546, 29081, 16116, 28097 incident presentations of each respective eGFR cohort and AKD. Classifications of socioeconomic position by household and neighborhood were related but complex, and frequently did not match. Compared to households of professionals, people with early kidney disease in unskilled or unemployed households had increased mortality (adjusted hazard ratios: 95% confidence intervals) of (1.26: 1.19-1.32) and (1.77: 1.60-1.96), respectively with adjustment for neighborhood indices making little difference. Those within either a deprived household or deprived neighborhood experienced greater mortality, but those within both had the poorest outcomes. Unskilled and unemployed households frequently reported being limited by illness, adverse mental health, living alone, basic accommodation, lack of car ownership, language difficulties, and visual and hearing impairments. Thus, impacts of deprivation on kidney health are spread throughout society-complex, serious, and not confined to those living in deprived neighborhoods.

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.

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.