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Akturk discusses how the definition of being German, Soviet, Russian and Turkish radically changed at the turn of the twenty-first century. Germany's ethnic citizenship law, the Soviet Union's inscription of ethnic origins in personal identification documents and Turkey's prohibition on the public use of minority languages, all implemented during the early twentieth century, underpinned the definition of nationhood in these countries. Despite many challenges from political and societal actors, these policies did not change for many decades, until around the turn of the twenty-first century, when Russia removed ethnicity from the internal passport, Germany changed its citizenship law and Turkish public television began broadcasting in minority languages. Using a new typology of 'regimes of ethnicity' and a close study of primary documents and numerous interviews, Sener Akturk argues that the coincidence of three key factors – counterelites, new discourses and hegemonic majorities – explains successful change in state policies toward ethnicity.

Pulmonary Function Testing (PFT) interpretation compares actual measurements with predicted values derived from a global dataset of healthy non-smokers. While race and ethnicity have historically informed these interpretations, their use is increasingly questioned due to their potential to perpetuate health disparities. To standardise PFT interpretation, the Global Lung Function Initiative (GLI) developed race-specific reference equations (2012), but limitations were recognised. In 2022, GLI introduced race-neutral equations. This study evaluates the impact of transitioning from race-specific to race-neutral equations on PFT interpretations in a local patient sample.A retrospective service evaluation using PFT data from 5716 patients aged 18–95. Datasets were reanalysed using GLI global 2022 race-neutral and compared to the existing GLI 2012 race-specific reference equations. Results were stratified by self-reported ethnicity (White, Black, and Other/Mixed) to assess clinical implications.The mean difference in FEV1 Z-scores between race-specific and race-neutral reference equations was -0.31 [LOA: 0.08; -0.71] in the white cohort, 0.53 (LOA: 0.93; 0.13) in the black cohort, and -0.06 (LOA: 0.36; -0.49) in the Other/Mixed cohort. Race-neutral equations predicted lower FEV1 Z-scores in Black individuals than race-specific equations, whereas in White individuals, they predicted slightly higher FEV1 Z-scores. Minimal differences were observed in the Other/Mixed cohort.Race-neutral equations increased the prevalence of lung function impairment by 1.9% in the White cohort, 11% in the Black cohort, and 0.65% in the Other/Mixed cohort. Applying race-neutral equations increased obstruction prevalence by 3.5% in the White cohort, with minimal changes in the Black and Other/Mixed cohorts. Restriction prevalence increased by 10.9% in the Black cohort but decreased by 4.6% and 3.2% in the White and Other/Mixed cohorts, respectively. Obstruction severity changed in 9.2% of White, 8% of Black, and 7.8% of Other/Mixed individuals. Overall, 8.1% of patients had interpretation changes from race-specific to race-neutral equations. (Figure 1)The adoption of GLI Global 2022 race-neutral reference equations will significantly impact spirometry interpretation, particularly in Black individuals. Clear communication with clinical teams is essential to ensure awareness of these changes and their implications. While the shift to race-neutral equations represents progress, further research, especially in non-white cohorts, is needed to fully evaluate its clinical impact.Abstract P15 Figure 1[Image Omitted. See PDF.]

Aims: The DIALOG scale has been implemented as a routine patient outcome and experience measure (PROM/PREM) in East London Foundation Trust (EL FT). We used large routinely collected DIALOG data to assess impact of treatment across different domains of life and whether the impact of treatment changed with Community Mental Health Transformation CMH (NHS Long Term Plan). We also carried out secondary disaggregation analysis of pooled data based on protected characteristics interrogating through an equity lens. Methods: EL FT had commissioned University of Plymouth for the review of CMH transformation. Anonymised pooled data set was obtained from the electronic patient records that were collected as a part of routine clinical practice. DIALOG (PROM and PREM) scores captured routinely from CMH services in ELFT over two time periods (2018–19 and 2021–22) were collected for this purpose. The anonymised and pooled data was linked with stages of treatment e.g. assessment, review and at discharge and protected characteristics (age, gender, ethnicity and a proxy of social deprivation). 14,813 DIALOG scores from 6,538 unique patients were identified. We analysed each domain of DIALOG separately and the numbers of return of scores on each domain varied depending on response rate. We compared domain based descriptive statistical analyses of mean pooled DIALOG scores looking at means across a range of variables for each domain and then conducted a series of multiple regressions for each of the DIALOG domains, to control for multiple variables together Results: Our results showed that service user satisfaction in each domain improved with treatment stage (from assessment to review to discharge) reaching statistical significance at each stage. There were minor differences between the two time periods (2018–19 and 2021–22) in a few domains. There was variation in outcomes across ethnicity, age and gender in a few domains. Conclusion: Large data sets of routinely collected DIALOG data offer valuable insight into the needs of the local population and impact of treatment. Assessment of the impact of the CMH service transformation was confounded by the pandemic. Disaggregated data on protected characteristics reveal interesting and useful information about experiences and outcomes of different population groups over time. Our study also validates DIALOG as a quality of life measure and patient experience measure scale that is sensitive to measure change. It affirms the value and depth that intelligence routine outcome data gathering can offer both to measure change as well as offering an assessment of population need.

BackgroundGlaucoma is the second leading cause of irreversible blindness. The iStent® Inject trabecular micro-bypass is a type of minimally invasive surgery that may effectively manage IOP and reduce dependence on medication. The outcome of the iStent procedure is poorly understood in different ethnic backgrounds and socio-economic groups.MethodologyOver a five-year period, 75 eyes (69 participants) were included in the audit. 47% of participants were from white ethnic background (English, Welsh, Scottish, Northern Irish or British, Irish, and any other White background) and 53% participants were from ethnic minority backgrounds (Asian, Black, mixed ethnic background and other ethnic group). Data logged retrospectively included: IOP, visual acuity, medical therapy, ocular co-morbidities, co-morbidities, ethnicity and socioeconomic data. The following outcomes were measures a) Reduction in IOP < 18 mmHg b) Reduction of IOP by >20% c) Reduction in topical medical therapy.ResultsMean pre-op IOP was 18.3 (SD 6.3). Post-operatively 92% of patients had achieved IOP <18 (Mean IOP 12.6 SD 4.6). Of all eyes operated on, 55% had IOP reduced by 20% or more. Post-operatively, medication use was reduced by 69%. Of the patients who had achieved all three outcomes, 64% of patients were of white ethnicity background and 86% were from middle class and above socioeconomic background.ConclusionThis retrospective audit shows that iStent procedure has been successful in reducing IOP and reducing the burden of medical therapy on patients. Results indicate that ethnicity and socioeconomic data do play a role in the outcome of iStent procedure.

Methods: We conducted a secondary analysis of the pre-intervention phase of a multicenter, multinational before-and-after study engaging families in the hands-on care of the patient so that they feel more empowered in the ICU. Families who identified race as 'Other' were more likely to use the sense of touch (applied lotion, held patient's hands, assist with turning) to help care for their loved ones than whites (p= 0.05) Conclusions: Different races and ethnicities have varying preferences on how to provide support and get involved in the care of their loved ones care through the stressful time of being in the ICU.