Health Inequalities and Inequity: Using data to address issues of Parity of Esteem

I write this as a companion piece to my recent blog on health inequality and health inequity. See

It is easy to write on a subject about which you are passionate; but I take the view that we should be judged on actions not just words. Its fine to rage against the injustices of the world, but if you aren’t part of the solution then you may very well be part of the problem.

By their deeds shall we know them.

My company is in the privileged position of working with the NHS to help it address long-standing issues of health inequality and health inequity. We take the view that some of the answers to the problem lie in the existence of high-quality data and more importantly the insights that can be harvested from that data.

To this end I wanted to share a short story of some of the analytics and data science work that we are currently engaged in with Primary Care Networks (PCNs); work which is helping address issues related to parity of esteem.

Parity of esteem describes the need to value mental health equally to physical health. Simply put people with complex mental health needs should have the same access to health care services and support as people with physical health needs.

We are currently mining a linked data set in order to deliver insight into Severe Mental Illness (SMI). The work is currently focused on a consideration of gaps in care for a SMI cohort allied to an understanding of the effects of the social determinants of health on this cohort.

This is a work in progress, and we are pleased to share initial findings here.

Sollis have a deeper set of definitions to capture disease prevalence than standard Quality Outcomes Framework (QOF) registries and because of this we can quickly identify diagnostic gaps in care and thus create a more complete and representative view of population needs (see Fig 1).

Fig 1

We have taken these definitions and applied them in order to understand outcomes specific to this cohort (see Fig 2). In this example the adverse outcome under consideration was emergency admissions for mental health disorders.

Fig 2

Through our process of population screening and surveillance we quickly identified that one Primary Care Network (PCN) had a significantly higher prevalence of people with Serious Mental Illness who in turn visited A&E at a higher rate than we would expect when compared to a local benchmark.  Additionally, this same group also had an unusually high incidence of emergency inpatient admissions for mental health disorders (e.g. Psychotic Disorders, Substance Misuse etc.).

We also detected significant differences in outcomes based on local quintiles of deprivation, meaning that not only is there variability by organisation (e.g. PCN and GP Practice) but that inequalities exist across socioeconomic boundaries.


We investigated this further and examined the completeness of core health checks in general practice for the Serious Mental Illness cohort (see Fig 4).  What this revealed is that there is wide variability of engagements and completed health checks for this cohort between different registered populations.  Our population health analytics platform – Sollis™ Clarity – by exception can highlight the individual patients who haven’t had a health check in the past twelve months who live in specific areas and who are registered with specific practices that have also been accessing the urgent care pathway.  This investigation set the parameters for actionable worklists for PCNs to engage; this with a view to closing gaps in care.

Fig 4

The next step is to undertake a deep dive into the cohorts identified, with a view to presenting the results of that analysis back to clinicians and members of the Additional Roles Reimbursement Scheme (ARRS) team in order that proactive interventions might be put in place.

The hope is that these proactive and personalised interventions will result in much improved health outcomes for this SMI cohort.

The goal is to ensure that people with mental health problems receive equal access to the most effective and safest care and treatment available and that they are also in receipt of equal efforts from the health and care system to improve their quality of care.

It is just one short story in a much wider and larger narrative concerning health inequality and health inequity.

That said, a journey of a thousand miles begins with a single step.

N C Slone