CQC Insight 15: Ethnicity data recording in mental health

Page last updated: 12 May 2022
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In this article, we look at the quality of ethnicity data recording for mental health services within local health and care systems.

Background

Our 2020/21 annual State of Care report highlighted the impact of the pandemic on people’s mental health. This included the increased demand for services. We also shone a light on the fact that the pandemic has not affected everyone equally. For example, some people from deprived areas and people from Black and minority ethnic groups have been affected more.

As highlighted in State of Care, according to Public Health England, at the end of May 2021 the cumulative age-standardised mortality rate in the most deprived areas in England was 2.4 times the rate in the least deprived areas. The mortality rates in people from the Black and Asian groups were more than double the rate in people from the White group.

Inequality in care was also highlighted by the findings of our provider collaboration review on children and young people’s mental health. Again, this showed that the COVID-19 pandemic has demonstrated the inequalities faced by some people with mental health needs. In some cases, the pandemic made these inequalities worse.

Concerns around inequalities in mental health care were also highlighted by NHS Digital’s annual figures on the Mental Health Act, published in October 2021.

Not being able to access the right care and support at the right time increases the risk of an individual’s mental health deteriorating.

Health inequalities are a significant and long-standing concern for the NHS, with preventing inequality a key feature of the NHS Long Term Plan.

Some systems in our provider collaboration review told us how they were trying to address these inequalities. For example, some areas told us they were now working together better to identify children and young people who need mental health care and support. This included people from Black and minority ethnic groups, Travellers, and asylum seekers.

But we found that tackling inequalities was often not a main priority for systems. While some areas were using equalities monitoring data to identify children and young people in need of mental health support, the data was not always captured well. As a result, we were concerned that this could lead to missed opportunities to adapt care to meet the needs of individuals and local populations.

Quality of ethnicity recording in mental health data sets

Reliable, quality evidence is a fundamental tool in identifying, tackling and improving service equality.

In June 2021, the Nuffield Trust and NHS Race and Health Observatory published their report on Ethnicity coding in English health service datasets. This identified substantial data quality issues with many health datasets for hospitals and community health care. In particular, the report highlighted concerns that a large proportion of data was not linked to a known patient ethnicity. It also reported a notable and growing reliance on ‘not known’ and ‘not stated’ ethnicity codes. Without this information, health providers will not be able to use the data effectively to monitor equality and detect inequalities in access to services and outcomes.

The report recommended that assessing the quality of ethnicity coding should be made part of our inspections and ratings. Publishing this report is a first step in our work to consider how we can use quality of ethnicity data recording in our regulation.

Building on the findings from this report, and following the concerns raised in our provider collaboration review on mental health around data on ethnicity, we have looked at the quality of ethnicity coding for mental health services who report to the Mental Health Services Data Set (MHSDS). To do this, we analysed a sample of the MHSDS ethnicity data from June 2019 to May 2021.

In line with the national mandatory standard, the MHSDS data set groups ethnicity into 16+1 ethnic data categories. These have been grouped into the following categories for the purposes of this analysis:

  • Asian and Asian British
  • Black and Black British
  • Mixed
  • White
  • Other
  • Not known – ethnicity is missing or otherwise not known
  • Not stated – an individual chooses not to give their ethnicity.

Similarly to the report of the NHS Race and Health Observatory, we found that there was a substantial and growing proportion of patients whose ethnicity was recorded as ‘not known’ and ‘not stated’. In the most recent month analysed (May 2021), we found that the ethnicity of nearly one in six patients (15.2%) was recorded under these categories (figure 1).

Figure 1: Monthly proportion of mental health patient records with an ethnicity code of ‘not known’ or ‘not stated’, June 2019 to May 2021, England
 
Date value Not stated (%) Not known (%)
June 2019 5.94681399 5.852211707
July 2019 6.007114859 5.839332557
August 2019 5.944692093 5.540403897
September 2019 6.090631137 5.891935337
October 2019 6.168825043 6.185964162
November 2019 6.288931173 6.360124194
December 2019 6.175454576 6.2916029
January 2020 6.461465874 6.608754765
February 2020 6.504135051 6.893918469
March 2020 6.700602585 7.213820395
April 2020 6.139367436 5.530061418
May 2020 6.123534928 5.782840966
June 2020 6.269128197 6.1124943
July 2020 6.392329461 6.346312642
August 2020 6.421481372 6.528041261
September 2020 6.57957746 6.671885928
October 2020 6.794950748 6.905430205
November 2020 6.895199686 7.169057816
December 2020 6.846664179 7.064023747
January 2021 6.932100179 7.392807507
February 2021 7.031647454 7.516447446
March 2021 7.226385975 8.089166115
April 2021 7.012934671 7.759449107
May 2021 7.106260773 8.14806222

It is not clear why these categories have increasingly been reported. It is possible that the unprecedented demands of COVID-19 on health services may have reduced staff ability to make sure they are being recorded appropriately.

Systems with higher rates of not known and not stated will not be able to effectively understand, and in turn address, inequalities in the care being provided. How much the ‘not known’ and ‘not stated’ categories for recording ethnicity are used varies across integrated care systems. Together, use of these categories ranges from 4.8% to 29.5% (figure 2). Which code is used also varies across systems. For example, some integrated care systems tend to report greater levels of ‘not known’, while others report greater levels of ‘not stated’.

Figure 2: Proportion of mental health patient records with an ethnicity code of ‘not known’ or ‘not stated’, June 2019 to May 2021, England
 
System Not stated (%) Not known (%)
Lancashire & S Cumbria 15.1604764 14.3262567
Dorset 28.40653313 0.411394201
Devon 8.689369245 14.13949017
Sussex 16.45556436 5.761409577
Hamps & IoW 8.709549289 13.24189818
Northamptonshire 4.050982118 17.73892763
Staffordshire 18.87820088 2.180750228
Bucks, Oxfords, Berks 5.119778455 15.67591015
Norfolk & Waveney 15.51204933 4.846593274
Kent & Medway 1.951591174 17.71834492
Shrops, Telford & Wrekin 17.56323247 1.732142569
Leicestershire & Rutland 12.96880827 5.019711257
Surrey 11.70143832 4.920052568
Frimley 10.31934391 5.256912306
BANES, Swindon & Wilts 3.812544167 10.39084897
Greater Manchester 7.788181948 6.15109888
Bristol, N Somerset & S Glos 1.612358031 11.3997431
Herefordshire & Worcs 9.164771236 3.827858455
Cheshire & Mersey 4.048202077 8.81718928
Suffolk & NE Essex 5.591124222 7.075823392
Herts & W Essex 7.233962508 4.785207521
Black Country & W Birmingham 7.167172094 4.38744418
Coventry & Warwicks 3.154542937 8.077706578
Cambs & Peterborough 3.110036477 8.105105569
South East London 3.791374549 7.128956873
Beds, Luton & MK 5.157834979 5.752423921
Derbyshire 3.88309801 7.005866628
Gloucestershire 4.29147486 6.139956464
North London 8.367601748 1.3893063
Mid & South Essex 2.0263582 7.675537267
Birmingham & Solihull 5.399006385 3.960839867
W Yorks & Harrogate 2.584219511 6.700284611
North West London 5.130641423 3.360465752
Nottinghamshire 5.107341739 3.373053641
S Yorks & Bassetlaw 4.890605488 3.480755572
Somerset 5.643524728 2.605838032
Humber, Coast & Vale 3.049315582 5.176073505
East London 2.678055944 5.299927542
Cornwall & IoS 1.101032303 6.781760155
South West London 2.156226236 5.400514049
Lincolnshire 1.223077894 4.599924252
North East and N Cumbria 2.314941628 2.500268716

Why recording varies across systems is unclear. But local demographics, policy and leadership may all play a role. To try and explore this further, we looked at the use of ‘not known’ and ‘not stated’ categories against the ethnic diversity of each system’s local population (figure 3). While areas with the lowest proportion of the population identifying as White (7 out of 42) tended to have lower rates of MHSDS records with ethnicity recorded as “not known” or “not stated”, the analysis found no clear correlation between ethnic diversity and rates of data completion. We will continue to carry out work to better understand how the quality of ethnicity recording relates to other information we hold about quality at provider and ICS level.

Figure 3: Rate of ‘not known’ and ‘not stated’ categories versus proportion of White population by integrated care system, June 2019 to May 2021, England
 
System Percentage of population who are White Percentage of records with ethnicity not stated or not known
Bath and North East Somerset, Swindon and Wiltshire 95% 14%
Bedfordshire, Luton and Milton Keynes 78% 11%
Birmingham and Solihull 68% 9%
Bristol, North Somerset and South Gloucestershire 90% 13%
Buckinghamshire, Oxfordshire and Berkshire West 88% 21%
Cambridgeshire and Peterborough 91% 11%
Cheshire and Merseyside 96% 13%
Cornwall and the Isles of Scilly 98% 8%
Coventry and Warwickshire 86% 11%
Cumbria and North East 96% 5%
Devon 97% 23%
Dorset 96% 29%
East London Health and Care Partnership 51% 8%
Frimley Health 81% 16%
Gloucestershire 95% 10%
Greater Manchester Health and Social Care Partnership 84% 14%
Hampshire and the Isle of Wight 94% 22%
Healthier Lancashire and South Cumbria 91% 30%
Herefordshire and Worcestershire 96% 13%
Hertfordshire and West Essex 88% 12%
Humber, Coast and Vale 96% 8%
Joined Up Care Derbyshire 93% 11%
Kent and Medway 93% 20%
Leicester, Leicestershire and Rutland 78% 18%
Lincolnshire 98% 6%
Mid and South Essex 93% 10%
Norfolk and Waveney Health and Care Partnership 97% 20%
North London Partners in Health and Care 64% 10%
North West London Health and Care Partnership 53% 9%
Northamptonshire 91% 22%
Nottingham and Nottinghamshire Health and Care 88% 9%
Our Healthier South East London 65% 11%
Shropshire and Telford and Wrekin 96% 19%
Somerset 98% 8%
South West London Health and Care Partnership 70% 8%
South Yorkshire and Bassetlaw 91% 8%
Staffordshire and Stoke on Trent 94% 21%
Suffolk and North East Essex 95% 13%
Surrey Heartlands 90% 17%
Sussex and East Surrey 93% 22%
The Black Country and West Birmingham 71% 12%
West Yorkshire and Harrogate (Health and Care Partnership) 83% 9%

We are concerned that poor recording of ethnicity, and an overreliance on the categories of ‘not known’ and ‘not stated’, is masking equality issues. Poor-quality recording makes it more difficult for organisations to interrogate and use data to address potential inequalities and that services are meeting the needs of individuals. For mental health services, this will reduce their ability to understand variation in referrals, treatments and deaths by ethnicity.

As highlighted in our provider collaboration review of children and young people’s mental health services, looking forward, it is important for systems to continue to increase their focus on addressing health inequalities. We encourage services to support system-wide efforts in tackling existing, and preventing future, health inequalities by improving how data to monitor equalities is captured and used, and improving training for staff on coding.

However, this needs to be part of a system-wide approach. As highlighted in the report by the Nuffield Trust and NHS Race and Health Observatory and a King’s Fund report on Ethnicity coding in health records, a key element will be updating guidance on recording of ethnicity as current guidelines were published in 2001.

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CQC Insight: Issue 15


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