Intersectional Inequalities England Stroke
Research type
Research Study
Full title
Examining intersectional inequalities in effective stroke care and stroke mortality across England
IRAS ID
348954
Contact name
Timea Putnoki
Contact email
Clinicaltrials.gov Identifier
23/089, NHS Research Registration Number
Duration of Study in the UK
1 years, 0 months, 1 days
Research summary
This project will aim to identify the intersectional inequalities in the effective coverage of stroke care and post-stroke outcomes and provide evidence for improvement. While existing research focusing on individual disparities in stroke care and stroke outcomes has been previously conducted, there are no current studies in the UK examining the additive effect of these inequalities through an intersectionality lens. Furthermore, no research has been conducted that examines the geographical disparities in stroke care and outcomes within England.
This research is the quantitative part of the larger CoastGEM project created in partnership between the University of Essex and the East Suffolk and North Essex Foundation Trust to better address inequalities in stroke and to ensure no one gets left behind. This research will be a part of a PhD thesis.
Aim:
• To identify the existing inequalities in the stroke care delivery system, their determinants, and their negative health consequences within England and provide evidence for improvement.
The methodology part of this paper will consist of two sections:
1. A quantitative analysis of data from the Sentinel Stroke National Audit Programme (SSNAP) set to examine the intersectional inequalities in the effective coverage of stroke care. Effective coverage will be defined using the Tanahashi framework (Availability, Accessibility, Contact Coverage, Quality, and Acceptability). The analysis will be conducted using the MAIHDA model, as this model is specifically tailored for intersectional analysis.
2. A quantitative analysis of linked Hospital Episode Statistics and Office of National Statistics mortality data from NHS Digital to examine the intersectional inequalities in mortality at 30 days and 1-year post-stroke, and a sequence data analysis to identify the inequalities in the care pathways 1-year post-stroke.
The analysis will be conducted using the MAIHDA model, as this model is specifically tailored for intersectional analysis, and sequence data analysis to identify care pathways.
REC name
South Central - Berkshire B Research Ethics Committee
REC reference
25/SC/0020
Date of REC Opinion
21 Jan 2025
REC opinion
Favourable Opinion