The NHS 5 Year Forward View gives a clear call for a re-balanced approach to prevention, clinical services, and community support and notes how important this is to help us tackle health inequalities and poor mental health.
But….those of those who are involved locally know that its all very well having the analysis and the aspiration – translating this into action is something else.
I want to focus on how our use of data shapes our approach to mental health and how this determines what we commission and provide – I think that this tends to leads us in one direction only – towards clinical solutions for social problems. We can see this in the report of the Independent Task Force on Mental Health to the NHS in England – although it recognises poverty as a significant driver for poor mental health its focus on inequalities is almost exclusively on ensuring equal access to clinical services – not on the social circumstances in which people with mental health problems live..
Lets look at the national data – because these set the tone for how we use data locally.
The Public Health England Public Health Profiles do include mental health indicators – but they only have two. These are for quite specific issues – incidence of suicide and deaths from drug misuse. There is nothing on broader issues such as anxiety and depression.
We know about the relationship between poor mental health – anxiety, depression and inequalities but most of the measures that pick up on inequality in the Public Health Profiles do so at a county/borough/city level – so the extent of inequality is masked by those who are better off.
There are more detailed mental health indicators that are produced by Public Health England. Two that are particularly helpful are the Common Mental Health Disorders and the Severe Mental Illness Profiles.
There is a tremendous amount of detail in both of these – with an overwhelming emphasis on data from statutory clinical health services. However once again they fail to locate the incidence of anxiety and depression within the wider socio-economic context of a particular district. There is a section on ‘Risk Factors’ which is deprivation related. But I think that the scale of the issue here is masked by a wider population effect.
As I have said almost all the data in the mental health datasets looks at the performance of the Health and Care mental health system. This means that there is a constant pull back towards clinical interventions.
Yet as the APHO 2007 report “indications of public health in the english regions 7 mental health” notes we need to focus on the needs of those who experience inequality most – this means focussing on:
- Housing Insecurity
- Problematic Debt
- Low wage and insecure employment
- Take up of welfare rights support
- Social Isolation
While some of this data sit in a background document to the Mental Health profiles (cmhd indicator list v5 march-2016) each indicator is presented in isolation and so does not give a coherent picture of the negative social factors that people with mental health problems experience.
This failure to present a coherent narrative about the relationship between mental health and inequality means that local health and care systems lack the evidence that will help them make the significant changes that are needed to rebalance services to focus more on prevention and community support.
What needs to happen
- PHE and NHS England need to start to produce a data set that describes the scale of the risk factors that are faced by populations of people with poor mental health AND data sets that focus on the risk factors faced by people in the bottom 20% of the population by income – compared to those in the top 20%
- More work needs to be done to bring key voluntary sector data into these profiles. There is plenty of data out there – for example voluntary sector and social landlords have good data on housing insecurity, Citizens Advice and Stepchange have excellent data on incidence of indebtedness and so on.
The recent report “The Missing Link” from the Money and Mental Health Policy Institute notes that:
“The IAPT recovery rate for people experiencing both depression and financial difficulty is likely to be just 22%, compared to 55% for people without financial difficulties. For anxiety, the IAPT recovery rate is likely to be just 38% among those with financial difficulties, while over half of patients without financial difficulties recover through IAPT.
We found that an intervention on financial difficulty boosts the likelihood of recovery for an individual with depression and financial difficulties from 22% to 48% and for an individual with anxiety and financial difficulties the likelihood of recovery increases from 38% to 50%.
What do you think?