Feature / The finance case for tackling inequality

05 June 2023 Steve Brown

Nobody disagrees with the need to address health inequalities. But there are concerns that the current financial challenges in the NHS make it more difficult to make rapid progress in this area. To counter this view, the head of NHS England’s health inequalities work is adamant that there is a clear business case for improving equity and that reducing health inequalities can even contribute to an improved financial position in the short term.


Last year, finance directors told an HFMA survey that programmes tackling health inequalities and pursuing prevention and population health were the ones most at risk from financial pressures. But Bola Owolabi, GP and director of healthcare inequalities at NHS England, suggests that the argument that it costs more to improve equity – because of the need to meet previously unmet demand – is flawed.

‘Very often, the conversation around health inequalities can be grounded in moral and ethical imperatives, which are of course really important,’ she says. ‘But actually, it’s important to recognise that there is a business case for tackling health inequalities.’

She highlights Michael Marmot’s work that calculated the treatment costs of health inequalities to be in the region of £5.5bn a year. Productivity losses in the economy due to health inequalities amount to £33bn, while a further £32bn a year is spent on higher welfare payments. Add to this the fact that those from the most deprived areas with lower life expectancy also exhibit the highest healthcare costs, she suggests, and the case is made.

Dr Owolabi also dismisses the argument that addressing health inequalities incurs cost now, but only pays back in future years. ‘The interval between investment and seeing the return on investment does not need to be significant in terms of time,’ she says. ‘The first thing is to ascertain the cost of doing nothing.’

She cites a number of examples, including when she was the clinical commissioning lead for children and young people in a Midlands system. The service undertook a zero-day audit to explore how many children admitted to the paediatrics ward actually ended up staying for less than 24 hours – a proxy for not needing to be admitted at all.

‘We found that significant proportions of these kids were being admitted more as a safety mechanism for our junior medical colleagues rather than on the basis of clinical need,’ she says.

To address this, a direct phone advice line was introduced for GPs to ring an on-call team for help – which led to a significant reduction in zero-day admissions. This simple, inexpensive intervention resulted in a better experience for the children and reduced use of scarce capacity – the point being that not all interventions cost a fortune.


Reducing did-not-attends

More directly related to health inequalities, Dr Owolabi points to Birmingham Women’s and Children’s NHS Foundation Trust. It investigated why people were not attending appointments, which was having an impact on trust productivity.

The trust used volunteers to contact the people concerned and find out their reasons for non-attendance. Often the reasons were down to the need for interpretation or not realising that they could bring somebody with them. Even where transportation costs were an issue, this did not involve significant sums of money to fix.

‘With those sorts of intervention, they saw a major reduction in was-not-broughts within three months,’ says Dr Owolabi.

Similarly, the University Hospitals of Leicester NHS Trust has also seen a nearly 50 percentage point reduction in did-not-attends (DNAs) in a respiratory pilot programme, just by disaggregating the data by deprivation and ethnicity and supporting people to attend.

‘So, we get a win-win,’ she says. ‘People getting equitable access to care and productivity improving. And the expenditure on DNAs was dramatically reduced. These are all live examples of how the interval between investment and return doesn’t need to be measured in decades – you can measure it in months.’

But surely some work to address health inequalities work leads to higher costs, at least upfront? Seeking out currently unmet demand, for example, may involve taking new approaches to screening for specific populations or areas.


Dr Owolabi (pictured) acknowledges the theoretical potential to incur higher costs, but she says there is real-world evidence that this isn’t always the case. ‘We commissioned the NHS Business Services Authority to conduct an analysis comparing prescribing patterns among people from the 20% most deprived population groups – the core 20 – with those from the 20% most affluent. And we looked at it across three of the five clinical areas in the core20plus5 framework – mental health, respiratory and cardiovascular.

‘What we found in respiratory was that there was a higher tendency to prescribe rescue inhalers to people with chronic obstructive pulmonary disease (COPD) from that bottom quintile and fewer preventer inhalers.’

With fewer preventer inhaler prescriptions correlating with higher mortality, there is a clear human cost to this inequality. But there is also a financial cost. ‘It is a false economy because we are spending more on those rescue inhalers, which are not necessarily prolonging life, they are just relieving symptoms,’ she says. The result was both higher mortality and higher prescribing costs.

Dr Owolabi also argues that those people being prescribed more rescue inhalers are more likely to be admitted to hospital with worsening COPD – one in eight emergency admissions in winter is due to exacerbations of chronic respiratory disease. ‘The cost soon begins to mount,’ she says. ‘It is just that we need to get better at triangulating those data points.’

She points to the HEARTT tool developed by the University Hospitals of Coventry and Warwickshire NHS Trust to support inclusive waiting list recovery. Patients continue to be treated in order of clinical priority, but the tool helps the trust to identify people who may suffer more as a result of waiting – those who may have developed other serious conditions such as cancer while on the waiting list, for example. It also helps to highlight those who may have struggled with access to services, perhaps because they live in an area of high deprivation.

‘They have been able to demonstrate a narrowing of the gap in waiting times between the top quintile and the bottom quintile of the population for the same clinical prioritisation,’ says Dr Owolabi.

She describes a further example relating to cardiovascular disease. The management of lipids and blood pressure is not as good among ethnic minority populations, and specifically black African communities, and with the most deprived population groups. But there is less prescribing of NICE-approved therapeutics in these groups.

Dr Owolabi argues that this is a false economy as there are higher rates of heart attacks and strokes among these groups.


One step ahead

This can have devastating consequences for the individuals, while also costing far more than the upfront prescribing. ‘By triangulating the data points, it helps us to see the true cost of doing nothing,’ she says. ‘If we optimally manage people’s blood pressure and their lipids, yes, there will be higher expenditure in terms of prescribing costs. However, we will reduce the incidence of heart attacks and strokes and the attendant cost of that, not only on the healthcare system but also on the social care system as a result of any disability incurred.

‘If we begin to look at the level of social care expenditure required to support somebody who’s then had a stroke or a heart attack and lost some of their functioning, it’s a false economy not to invest early in the optimisation of those conditions.’

Information is the foundation for making the case for much of this work on health inequalities. Or as Dr Owolabi puts it: ‘Data is central and mission critical’.

She champions the routine disaggregation of data to unearth disparities, rolling out a headline statistic from the pandemic. In January 2021, Covid vaccination looked to be proceeding well, with more than 80% of the population taking up the vaccination offer. But analysing the data by different communities showed that this ‘good’ response was far from universal.

The uptake was just 38% among black Africans and 44% for Pakistanis. For the most deprived 20% of the population, regardless of ethnicity, the rate was similarly 45%. ‘It was that disaggregation that drove a number of interventions that began to narrow the gap,’ she says. ‘That is the first thing we need to do – disaggregate the data. And then we need to triangulate it.’


Downstream impact

So, look at the prescribing cost, but also look at the downstream impact. ‘And I don’t mean five to 10 years,’ says Dr Owolabi. ‘I mean downstream the same financial year or within 18 months to two years. Triangulate the initial expenditure with non-elective admissions, A&E attendances, acute exacerbations and the treatment costs of advanced disease. What we need is to create a data warehouse of the lead and lag indicators, with numbers beside them so we can see the true return on investment.’

She offers one further example. Early cancer diagnosis is one of the five clinical areas in the core20plus5 framework. Shifting detection from stage 3 or 4 to early stages 1 and 2 can have a huge impact on survival rates. The benefits to individuals are enormous, but treatment costs in the early stages are also much lower than late-stage treatment. The costs associated with earlier detection could be quickly outstripped by the avoided costs of complex treatment.

‘That is the level of sophistication in data triangulation that we need to begin to build as a finance community that will help us with our business case design, our resource allocation and our assurance mechanisms to be able to give the true rather than the narrow narrative of return on investment.’

The NHS faces a huge task in recovering services, while facing significant financial challenges. However, Dr Owolabi says the priorities set out in the priorities and planning guidance – including elective and emergency care recovery and improved primary care access – should all be viewed through a health equity lens.

She makes a specific plea to finance leaders. ‘Let’s disaggregate the data [across different groups and levels of deprivation] and triangulate the data,’ she says. ‘Then let’s reorientate our resource allocation to address unmet need and to address the inequities that we surface once we have disaggregated the data. And finally, let’s understand that health inequalities equate to productivity inequalities. Any investment we make in reducing health inequalities materially reduces our productivity inequalities.’

She highlights the tools and resources now being brought out by the HFMA as part of work with the NHS England healthcare inequalities improvement team (see box) and wants finance managers to share these resources and amplify the message.

‘We need to cascade these resources across all teams to help us deliver in a measurable way a reduction in the health inequalities gap over the next three to five years,’ she says. ‘I want us to reorientate the way we do our business cases and procurement frameworks and move beyond simply completing an equality and health inequality impact assessment template. We need to change our resource allocation and the way we measure return on investment. And, over the next three to five years, I want to tell a data-based story of health inequalities improvement.’

Bola Owolabi will be a judge in this year’s HFMA Addressing Health Inequalities through NHS Finance Action Award. This is the second year the award has been run. For details of last year’s winners see the HFMA Awards 2022 supplement – see hfma.to/jun239


Six steps to change

 A recent HFMA briefing – Health inequalities: establishing the case for change – sets out six steps that need to be taken to develop an effective local case for addressing health inequalities.

  1. Identify the specific financial or performance pressures and work with business analytics colleagues to develop the underlying activity data.
  2. Overlay deprivation, geographical and protected characteristic data to the activity information and determine any trends and correlation.
  3. Use costing data and other financial information to estimate the impact of delivering an equitable service.
  4. Identify national policy drivers or local priorities that would support further work to be done in this area.
  5. Find a clinical champion within the organisation to support the work.
  6. Work with system partners to understand if they are seeing similar impacts or related issues.

A further publication – Resources and funding to reduce health inequalities – attempts to unpick the complex funding arrangements for addressing health inequalities and highlights the difficulties in releasing these resources. Given that addressing health inequalities is one of four core aims for all integrated care boards, it says: ‘The entirety of ICB and system funding (and cost) should be focused on reducing health inequalities.’

While the allocation formula that sets funding for ICBs takes account of deprivation, the allocation approach is informed by previous use of services. So there is a separate adjustment to take account of unmet need and health inequalities – currently accounting for 10% of boards’ core allocations.

Separately identified funding in 2022/23 has now been rolled into ICB baselines. So, a big chunk of resources is allocated on the basis of a measure of health inequalities. The challenge facing boards and providers is moving money from existing commitments to meet specific activities to reduce health inequalities.

The briefing also flags up potential extra sources of funding for health inequalities work, including the MedTech funding mandate and digital funds.

Supporting documents
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