Using data more effectively to describe ethnic health inequalities in the UK Lynne Carter NHS Equality and Diversity Manager and NIHR Knowledge Mobilisation Research Fellow

Lynne Carter was until recently a Knowledge Mobilisation Research Fellow supported by the National Institute for Health Research. The views expressed in this presentation are Lynne’s and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. Lynne’s fellowship was supported by the Collaboration for Leadership in Applied Health Research and Care - CLAHRC Yorkshire and Humber.

Background Knowledge Mobilisation Research Fellowship Case Studies Evidence and Ethnicity in Commissioning research project (Salway et al, 2013) Generation and use of evidence and knowledge is needed to raise awareness of the ethnic inequalities and to challenge and support key actors to find viable solutions Equality and Diversity professionals and others advocating for action to improve race equality often lack skills and confidence in data analysis and in accessing, appraising and applying research evidence

Case Study – an NHS mental health trust Reconfiguration of community based mental health services Data from: 2011 UK census Local Authority records Trust’s patient records Produced colour coded charts comparing the proportions of men and women of different ethnicities using different mental health services with the proportions of these groups of people in the local population

Feedback from stakeholders √ Indication of under-usage and over-usage of different services √ Fine ethnic categories and differences for women and men √ Possible connections between different services √ Very varied levels of recording of ethnicity X No indication of statistical significance X No indication of need

Case study – stage 2 Including prevalence data from the Adult Psychiatric Morbidity Survey, we then produced new charts comparing need (local men and women of different ethnicities likely to have common mental disorders) with receipt of treatment (local men and women of different ethnicities accessing NHS Increasing Access to Psychological Therapies (IAPT) services) Using the Chi Square test function in Microsoft Excel and broader ethnic categories we were able to show statistically significant differences Finally, using IAPT data published by NHS Digital, we produced charts showing the proportions of men and women of different ethnicities who finish an IAPT course of treatment, reliably improve and move to recovery in this locality compared to the whole of England

Next steps Some managers are now working to improve the recording of the ethnicity of their service users Some teams have looked at the data charts and discussed the factors leading to the inequalities the data describes using a fishbone diagram The local mental health commissioners will be receiving an update on this work

Learning from this stage of the case study √ Accurate and local data which describes the gap between need and receipt of services for women and men of different ethnicities √ Counter the frequently raised objection about lack of statistical significance √ Compare local performance with national performance X Broader ethnic categories may make understanding the causes of differences and identifying interventions more difficult

Case Study – Public Health’s BAME Health Needs Assessment In a city with a lower proportion of Black, Asian and Minority Ethnic people the Public Health team in the Local Authority produced a BAME Health Needs Assessment and identified mental health as an initial implementation project. Three different data sets showing population, prevalence and IAPT service usage & outcomes were brought together to describe for local people of different ethnicities: “population” – numbers of people with expected common mental disorders “reach” - numbers of these people being referred to the IAPT service “impact” – numbers of these people who complete the programme of treatment “outcome” – numbers of these people who reliably improve Using broad ethnic categories, statistically significant differences in reach and outcome for BAME men and women were described

Next steps An externally facilitated workshop for a range of stakeholders: IAPT managers and staff Mental Health commissioners Public Health staff Staff from a range of local third sector organisations The workshop explored reasons for the disparities shown by these data using Leeds GATE’s Road, Bridges and Tunnels model A plan to reduce the inequalities has been drawn up

Learning from this case study √ Accurate and local data which describes the gap between need, receipt of services and outcomes for women and men of different ethnicities √ Presented in easy-to-interpret charts √ Data rang true with service providers and community groups and stimulated discussion X Broader ethnic categories may make understanding the causes of differences and identifying interventions more difficult X Need to involve service users

Learning about knowledge creation and mobilisation Developing a methodology to create knowledge that is “good enough” – accurate and robust data – local, specific and easy to understand A method that doesn’t require qualified data analysts, researchers and lots of time Can potentially be used for other conditions: Health checks Hospital admissions Cancer Describing inequalities is only the first stage in reducing them!

Contact details Look at data sets in detail and provide feedback at a workshop in Leeds, UK on 11th July 2018 To book a place and /or get more details contact lynne.carter1@nhs.net Thanks to my mentor, Professor Sarah Salway, and my case study partners, Liz Johnson, Susan Hampshaw and Laurie Mott