Distributional cost-effectiveness analysis: Shaping the future of health equity within health economics

A roundtable discussion

Rebecca:
The move towards considering health equity more explicitly within health technology assessment (HTA) is gaining international momentum. This is highlighted in the 2025 China Guidelines for Pharmacoeconomic Evaluation, which encourage researchers to use various methods, including distributional cost-effectiveness analysis (DCEA), to assess the impact of new medical technologies on social inequality. This shift towards more explicitly considering health equity is also reflected in the approach taken by NICE in 2025, which recommends the use of DCEA in the development of public health guidelines and HTA. By adopting these methods, policymakers can better evaluate the trade-offs between maximising population health and reducing systemic inequalities.

In this blog, I’ve brought together colleagues from York Health Economics Consortium: Hayden Holmes (Director of Digital Health Consulting), Robert Malcolm (Project Director), and Angel Varghese (Project Director). Here you can read their discussion, where they share different perspectives on issues surrounding health inequalities and how methods such as DCEA can help to tackle them.

What is health equity?

Rebecca:
Equity and inequalities in healthcare are often mentioned, but when it comes to economic evaluation, how do we measure fairness? Rob, let’s start with the basics. What are we actually talking about when we say ‘health equity’?

Rob:
Simply put, inequalities are the unfair, avoidable differences between groups, whether those are social, economic or geographic. Health equity is the gold standard where everyone can reach their full potential for health and wellbeing. The method we’re discussing today, DCEA, builds on cost-effectiveness analysis by providing information about equity in the distribution of costs and effects.

Angel:
There’s plenty of evidence showing why this matters. Take colorectal cancer: it’s long been established that incidence and diagnosis of colorectal cancer is disproportionate between those from lower and upper socioeconomic groups. Recent data even show further disparity in the treatment provided. Another example is maternal care. As highlighted by the recent MBRRACE-UK reports, there’s a substantially increased risk of maternal and neonatal deaths in more deprived groups when compared with least deprived groups.

Hayden:
Completely agree, Angel. Historically, we’ve conflated equality with equity. Policy documents often focus on “equal access”, assuming that if all populations have the same access and use that access in the same way, the outcome will be the same, but that’s inaccurate. Health equity is primarily driven by the wider determinants of health and isn’t attributable to one simple input such as access. As Angel mentioned, we know that many diseases have a strong association with socio-economic status. However, when you have 20% to 25% fewer GPs per capita in lower-income areas, equal access isn’t equal for everyone. This contributes to a culture of waiting and mistrust in the health system.

How can DCEA help?

Rebecca:
So, how does DCEA help address that balance?

Angel:
A real strength of DCEA is that if a new treatment comes along, we can use these methods to see if it’s going to close that gap or potentially widen it. Or, if we have a policy specifically designed to reduce disparity, DCEA allows us to estimate if this has been achieved. It allows us to quantify the downstream impact of these policies on both health and cost outcomes by some measure of deprivation.

Rob:
Right, and there are two different approaches that we can take. The first is full DCEA – this is the deep dive. It aims to model the cumulative impact across the whole journey of disease and treatment: incidence, treatment uptake, adherence, and treatment effectiveness. It’s complex because it requires data on social variation at every stage, which can be challenging to identify. The other is aggregate DCEA, which is more streamlined, and simplifies the analysis. This focuses on inequalities generated by differences in healthcare need, like disease prevalence, and utilisation, but we are assuming in this case aspects such as treatment effectiveness are the same across different groups.

Hayden:
It’s about the trade-off. Humans are generally altruistic; we don’t derive pleasure from seeing other people go untreated and are generally supportive of measures to reduce inequalities. But as Rob pointed out, there’s often a tug-of-war between maximising total population health and reducing inequality. DCEA doesn’t tell a politician “one unit of health is worth X amount of inequality reduction”, but it does visualise these competing factors so they can make better informed decisions.

A growing international interest

Rebecca:
Do you think the methods textbooks and training courses developed by Richard Cookson and the Centre for Health Economics have increased understanding of DCEA?

Rob:
Absolutely. We’re seeing NICE in the UK recommending it, ICER in the US considering it, and countries like China incorporating it into their guidelines. It’s a really clear sign of the direction of travel, because it accounts for opportunity cost and gives policy makers a really useful way to quantify the potential impacts for both population health and health equity. It’s not just about who benefits, but who loses out when health resources are displaced, which can have a big impact on both factors.

Angel:
It’s also about societal values. Inequalities have always existed, so having methods to explore this appropriately is necessary, particularly to capture if policies are actually hitting the intended targets. However, what this balance looks like may vary by country, driven by differences in preference for how much they value maximising total health versus reducing equity gaps.

Hayden:
Most countries have policies that aim to increase total population health from within a prescribed funding envelope. We’ve been great at funding things that increase overall life expectancy, but those gains haven’t been shared equally. It’s challenging because there are many differing views of what ‘good’ looks like in this context. Now, organisations like Pharmac in New Zealand, PBAC in Australia, and CDA in Canada are using language that includes sustainability, health need, and societal factors.

The risks of DCEA

Rebecca:
It sounds like a breakthrough, but what are the risks of using DCEA in these evaluations?

Hayden:
Consistency is the big one. There’s a risk that people only run a DCEA when they expect a positive result for equity. If an intervention might negatively impact equity, they might just say the analysis wasn’t relevant. Currently, decision makers aren’t always given information on equity or inequalities, so it only ends up being factored into a small proportion of decisions. We need it to be routine.

Rob:
There are also other tools we can use. We have extended cost-effectiveness analysis (ECEA) that focuses on evaluating the consequences across multiple domains, including health gains and costs to the policymaker, and the GRACE framework in the US that focuses on incorporating patient preferences related to disease severity and risk aversion.

Hayden:
Ultimately, any approach to attempt to quantify inequalities will be a great step forward. Uptake data is also really important; we should be thinking about how we can reach the right people and what that means for implementation costs and population health.

Angel:
Agreed. Since there are a few approaches you can use to explore equity, it’s really important to understand what each approach does and doesn’t capture. To do this effectively, people must be informed about what these methods are and what components are captured. Simpler methods can be of value to decision makers; some information is better than no information, as long as we’re clear on the limitations of these simpler analyses over a DCEA.

A global perspective

Rebecca:
Let’s consider what this means internationally. What are the key things to consider globally?

Hayden:
International consistency is really important. I’ve seen posters at conferences described as DCEAs that are really just simpler methods of capturing inequalities. We also need to be careful about ‘willingness to pay’, which produces very different results in developed countries where the willingness to pay for healthcare is often much higher than the health system opportunity cost. In the US, I’ve seen DCEA models using $150,000 per QALY, making everything look cost effective and equity-reducing. If we don’t ground these models in the actual opportunity cost of the health system, we risk making incorrectly informed decisions.

Angel:
As the area gains traction, we just need to tailor the complexity of the method to the problem at hand. The tools are there; we just have to use them wisely.

Rob:

It’s not one-size-fits-all. Different interventions in different countries require different approaches. Our recent research suggests many countries already have the data to implement DCEA, but even if they do not, there are alternative approaches that can be used.

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