Equity

Equity in Health and Health Care

Equity asks whether health, healthcare and the resources that shape them are distributed fairly. In health economics the term means fairness in distribution, not equity in the financial sense of an ownership stake. Equity differs from equality, applies to both the delivery and the financing of health care, and can be summarised with measures such as the concentration index and the Kakwani index. The narrower normative principle that everyone should have a fair opportunity to attain full health is treated separately as health equity.

Equity is about fairness, not identical treatment

Equity evaluates differences in health, access, financing or resource allocation by asking whether those differences are fair. Equality describes whether people receive the same resources or experience the same outcomes, but equity recognises that people may have different needs, risks, barriers and capacities to benefit.

Providing everyone with the same service is therefore not necessarily equitable. A fair response may require additional resources, adapted services or greater financial protection for people facing greater need or disadvantage.

• Equality gives people the same resources, opportunities or treatment.
• Equity distributes resources, opportunities or treatment according to a relevant principle of fairness.
• Health inequality is an observed difference in health between people or groups.
• Health inequity is a health difference judged to be unnecessary and avoidable and, in addition, unfair and unjust.
• An equitable policy may treat people differently when those differences respond to unequal needs or barriers.

Fairness can be judged in more than one way

Equity is not a single mathematical rule. Different ethical principles identify different features of a distribution as relevant, so a policy may appear equitable under one principle but not under another.

The principle used should be stated explicitly rather than hidden inside an analysis or decision. Decision makers may consider several principles together when no single principle captures every relevant concern.

• Equity based on need gives greater priority to people with greater health needs.
• Equity based on equal access seeks comparable opportunities to obtain appropriate care.
• Equity based on equal utilisation seeks equal use of services by people with equal need.
• Equity based on equal health outcomes seeks to reduce differences in health between groups.
• Equity based on capacity to benefit gives priority where resources can produce meaningful improvement.
• Equity based on severity gives additional importance to people with the most serious conditions or greatest lifetime health losses.
• Equity based on financial protection seeks to prevent healthcare payments from causing hardship.
• Equity based on priority to disadvantaged groups gives additional consideration to people experiencing social, economic or geographic disadvantage.

These principles can conflict. The health economics literature identifies four common definitions of equity in health care (equality of utilisation, distribution according to need, equality of access and equality of health) and argues that, in general, they are mutually incompatible, so meeting one can mean breaching another. The same analysis proposes equality of health as the dominant principle, with health care distributed to bring the distribution of health as close to equal as is feasible. Prioritising the greatest health gain may not reduce health inequalities, while prioritising the most disadvantaged group may produce fewer total health gains from a fixed budget.

Horizontal and vertical equity answer different questions

Horizontal equity asks whether people in relevantly similar circumstances are treated similarly. It is usually summarised as equal treatment of equals and, in the delivery of health care, as equal treatment for equal medical need, irrespective of other characteristics such as income, ethnicity or place of residence.

Vertical equity asks whether people in meaningfully different circumstances are treated differently in an appropriate way. It is usually summarised as appropriately unequal treatment of unequals. For example, people with greater health needs may require more intensive services, while households with greater ability to pay may be expected to contribute more towards the cost of care.

Both ideas apply to the delivery and to the financing of health care, and they ask different questions in each.

• In delivery, horizontal equity asks whether people with the same need receive the same care, whatever their income or social position.
• In delivery, vertical equity asks whether people with greater need receive appropriately more care.
• In financing, horizontal equity asks whether households with the same ability to pay make the same payments for health care.
• In financing, vertical equity asks whether households with greater ability to pay contribute appropriately more, and how much more is fair.
• The distinction depends on deciding which differences between people are relevant.
• An equity assessment should explain why a characteristic justifies similar or different treatment.

In practice the two ideas cannot be separated completely. Measuring horizontal inequity in health care use requires a vertical norm for how much more care people with greater need should receive, and empirical studies usually assume that the average relationship between need and use across the whole population is the appropriate one.

Equity may concern health, healthcare or healthcare financing

Equity can be assessed at several connected levels. A fair distribution of healthcare does not automatically produce equal health because health is also shaped by income, education, housing, environment, employment and other social conditions.

Analysts should therefore state the outcome and population to which an equity claim applies. A policy may improve equity in access while leaving inequalities in health outcomes unchanged, or it may improve average health while worsening financial protection.

• Equity in health concerns the fairness of differences in health status or health outcomes.
• Equity in healthcare access concerns whether people can obtain appropriate services when they need them.
• Equity in healthcare use concerns whether service utilisation reflects relevant need rather than avoidable barriers.
• Equity in healthcare quality concerns whether people receive comparable standards of appropriate care.
• Equity in financing concerns how healthcare payments and financial risks are distributed.
• Equity in resource allocation concerns how budgets, staff, facilities and technologies are distributed across populations.

A widely used working definition, set out in work on equity for the World Health Organization European Region, defines equity in health care as equal access to available care for equal need, equal utilisation for equal need and equal quality of care for all. The same work treats a health difference as an inequity only when it is unnecessary and avoidable and is also considered unfair and unjust.

Measuring inequality and inequity in health and health care

Equity analysis needs measures that reflect how a health variable is distributed across the socioeconomic scale, not only differences between the best-off and worst-off groups. A comparison of the extreme groups ignores everyone in between, while measures such as the range or the index of dissimilarity can give a misleading picture of socioeconomic inequality.

A comparative review of these measures concluded that only the slope index of inequality and the concentration index were likely to give an accurate picture of socioeconomic inequalities in health. For the concentration index, people are ranked by socioeconomic status, usually income or consumption, and the concentration curve plots the cumulative share of the health variable against the cumulative share of the population. The concentration index is twice the area between this curve and the line of equality.

• The index is zero when there is no socioeconomic-related inequality.
• A negative value means the variable is concentrated among poorer people; for ill health, this means ill health is higher among the poor.
• A positive value means the variable is concentrated among richer people.
• For a binary variable the bounds are not minus one and one but depend on the mean of the variable, which complicates comparisons between variables with different means.

Inequality in health care use is not the same as inequity, because poorer people often have greater need. To measure horizontal inequity, use is first standardised for differences in need, usually proxied by age, sex and health status. Any remaining income-related inequality in need-standardised use is interpreted as horizontal inequity, which can favour the rich or the poor. The concentration index of need-standardised use then summarises the degree of horizontal inequity.

Equity in health financing, progressivity and the Kakwani index

Equity in health financing asks who pays for health care relative to ability to pay. Payments can come from direct taxes, indirect taxes, social insurance, private insurance and out-of-pocket payments, and each source can be distributed differently.

A financing system is proportional when payments take the same share of ability to pay at every income level. It is progressive when payments take a rising share as ability to pay rises, and regressive when they take a falling share. Which pattern is fair is a value judgement, but measuring the pattern shows whether a system meets the chosen vertical equity norm.

The Kakwani index is the most widely used summary measure of progressivity in both the tax and the health finance literatures. It equals the concentration index for health payments minus the Gini coefficient of ability to pay, which is twice the area between the payment concentration curve and the Lorenz curve.

• A positive Kakwani index indicates a progressive source or system.
• A negative Kakwani index indicates a regressive source or system.
• A value of zero is consistent with proportionality, but it can also arise when the two curves cross and the differences cancel, so graphical dominance analysis should accompany the index.
• Overall progressivity is found by weighting the index for each source of finance by its share of total health care revenue.

Compulsory payments can also redistribute income. Vertical redistribution occurs when payments are disproportionately related to ability to pay, while horizontal redistribution occurs when people with the same ability to pay contribute unequally.

Efficiency and equity are distinct decision objectives

Efficiency concerns how well resources are converted into valued outcomes. Equity concerns whether the distribution of those resources, opportunities, burdens and outcomes is fair.

The objectives can reinforce one another, but they can also create a trade-off. An intervention may generate the largest total health gain while directing most benefits toward an already advantaged population, whereas another intervention may generate a smaller total gain but reduce an important health inequality.

• An efficient allocation maximises valued outcomes from available resources under the chosen objective.
• An equitable allocation reflects an explicitly justified principle of fairness.
• Efficiency evidence does not determine whether the resulting distribution is fair.
• Equity concerns do not remove the opportunity cost of using resources.
• A transparent decision should report both total effects and their distribution when distribution matters.

Equity should not be treated as an unexplained adjustment made after the economic analysis. It should be incorporated through clearly stated objectives, relevant population groups, appropriate evidence and transparent value judgements.

How equity enters economic evaluation

Conventional economic evaluation often summarises costs and health outcomes across the population. Aggregated results can conceal who gains, who loses, who pays and who is displaced when resources are committed.

An equity-informed evaluation disaggregates relevant effects and examines their distribution alongside the total result. The analytical method should match the decision question and should not imply that a technical calculation can settle every ethical judgement.

1. Define the population and alternatives. Specify whose health, costs, access or financial protection could change under each option.
2. Identify relevant equity characteristics. Select characteristics such as socioeconomic position, geography, ethnicity, sex, disability or disease severity only when they are justified by the decision context.
3. Estimate subgroup effects. Examine how costs, outcomes, access and other consequences differ between relevant groups.
4. Account for opportunity costs. Consider which people may lose health or resources when funding is redirected.
5. Apply an explicit equity principle. State whether the analysis prioritises need, severity, disadvantage, equal access, financial protection or another defensible concern.
6. Compare totals and distributions. Report overall outcomes together with the pattern of gains, losses and burdens across groups.
7. Test uncertain assumptions. Examine whether the equity conclusion changes when subgroup evidence, value judgements or model assumptions change.
8. Present unresolved trade-offs. Distinguish evidence from ethical judgement and show where decision-maker deliberation remains necessary.

Distributional analysis makes hidden effects visible

Distributional cost-effectiveness analysis extends conventional cost-effectiveness analysis by estimating how health benefits and opportunity costs are distributed across relevant population groups. It has two stages. The first models the social distribution of health under each option, and the second evaluates those distributions against the dual objectives of improving total population health and reducing unfair health inequality. It can therefore show whether an intervention changes total population health, health inequality or both.

Equity weighting is another possible approach in which outcomes received by different people or groups are assigned different social values. Any weighting system depends on normative choices and should therefore be reported transparently, tested in sensitivity analysis and presented alongside unweighted results.

• Subgroup analysis describes how costs and outcomes vary between groups.
• Distributional cost-effectiveness analysis estimates both total health effects and changes in the distribution of health.
• Equity weighting assigns different social values to outcomes according to an explicit fairness principle.
• Multi-criteria decision analysis may place equity alongside efficiency and other decision criteria.
• Extended cost-effectiveness analysis examines health gains, financial risk protection, costs to the policy maker and distributional consequences.

No method removes the need for judgement. The purpose of formal analysis is to make the consequences and value choices more visible, consistent and open to scrutiny.

How NICE treats equity in technology appraisal

The NICE technology appraisal and highly specialised technologies manual (PMG36) handles equity through the reference case and through structured committee decision-making rather than through routine equity weights. In the reference case, the committee regards all QALYs as being of equal weight (section 6.2.10). The committee can still consider other factors and decision-making modifiers, and in exceptional circumstances it can accept analysis that explores a different QALY weighting.

The named decision-making modifiers are severity, defined through absolute and proportional QALY shortfall, and the size of benefit for highly specialised technologies. Health inequalities are not a modifier. In May 2025 NICE updated the manual to add guidance on evidence about health inequalities and how it affects decision-making.

• If robust evidence shows that a technology substantially affects health inequalities, the committee considers how this affects its judgement about whether the technology is an effective use of NHS resources (section 6.2.35).
• Consideration of health inequality impacts is separate from NICE's legal obligations on equality and human rights, including under the Equality Act 2010 (section 6.2.36).
• When the health inequality impacts are substantial, the committee can apply flexibility to the range normally considered cost effective, but it must consider healthcare displacement and opportunity cost and give stakeholders a rationale (section 6.2.38).
• Evidence on health inequality impacts is not used to make optimised recommendations for subgroups defined solely by social characteristics (section 6.2.38).
• Aspects relating to health inequalities are among the factors the committee specifically considers when the most plausible ICER is above £25,000 per QALY gained, or £100,000 per QALY gained for highly specialised technologies (section 6.3.5).

Section 4.12 of the manual sets out the analytical side. A company should include a distributional cost-effectiveness analysis only when there is clear evidence, supported by quantitative data, of a significant burden of health inequalities in the eligible population. The analysis is supporting evidence only, and it should not weigh the costs or benefits of a technology differently according to the social characteristics of the people affected.

Illustrative example of an equity-efficiency choice

This hypothetical example uses no numbers because its purpose is to show the structure of the judgement. A health system must choose between two programmes using the same limited budget. Programme A produces a larger total health gain, while Programme B produces a smaller total health gain but directs more benefit toward a population experiencing substantially worse health and poorer access to care.

Efficiency evidence may favour Programme A if the objective is to maximise total health. An equity principle based on severity, disadvantage or reducing health inequality may give additional weight to Programme B.

The decision cannot be resolved by describing Programme B as equitable without further explanation. The analysis should state which population is considered disadvantaged, why that difference is ethically relevant, how much total health would be forgone, who bears the opportunity cost and how uncertainty affects the comparison.

Equity claims require careful evidence

Observed differences between groups do not automatically establish inequity. Analysts must distinguish measurable inequality from the judgement that a difference is unfair, while recognising that the evidence needed to explain a difference may be incomplete.

Subgroup estimates can also be uncertain because studies may not include enough participants, measure relevant characteristics consistently or represent populations facing the greatest barriers. An apparently precise equity conclusion may therefore rest on weak or missing distributional evidence.

• Equity analysis should pre-specify relevant groups where possible rather than search for convenient differences after observing the data.
• Equity analysis should report absolute and relative differences because the two measures can lead to different interpretations.
• Equity analysis should consider intersecting characteristics rather than assuming that each characteristic operates independently.
• Equity analysis should distinguish differences caused by need from differences caused by avoidable barriers.
• Equity analysis should report missing data and uncertainty for each relevant group.
• Equity analysis should avoid treating membership of a population group as a complete explanation of individual need or experience.

Common mistakes when interpreting equity

Equity is often weakened when it is used as a general expression of concern without identifying the distribution, population or fairness principle involved. A useful equity claim must say what is distributed, between whom, according to which principle and with what evidence.

Several recurring mistakes can make an assessment appear more conclusive than it is.

• Equity is not the same as giving everyone an identical quantity of care.
• A difference between groups is not automatically an inequity until its fairness and avoidability have been considered.
• Unequal use of health care is not in itself horizontal inequity, because use must first be standardised for need.
• Improving average population health does not necessarily reduce health inequality.
• Improving access does not guarantee equal use, equal quality or equal outcomes.
• A subgroup analysis does not become an equity analysis unless the distributional differences are interpreted using an explicit fairness principle.
• Equity weights should not be applied without explaining their ethical basis and testing their consequences.
• Equity should not be presented as cost-free because prioritising one group may create opportunity costs elsewhere.
• A single summary measure should not conceal important gains, losses or burdens experienced by particular populations.

What an equity-informed result should communicate

A clear equity assessment shows both what is known and what remains a matter of judgement. It allows readers to understand who is affected, how the distribution changes and which fairness principle informs the interpretation.

The final presentation should preserve the distinction between empirical evidence and normative choice. Decision makers can then consider efficiency, equity, affordability and other objectives without implying that one measure provides the complete answer.

An equity-informed result should communicate each of the following points.

• which outcomes, resources or burdens were assessed;
• which population groups were compared and why they were relevant;
• how benefits, harms, costs and opportunity costs were distributed;
• which principle of fairness was applied;
• whether total outcomes and distributional outcomes moved in the same or opposite directions;
• how uncertainty affected the equity conclusion; and
• which value judgements still require transparent deliberation.

Sources

• Culyer AJ, Wagstaff A. Equity and equality in health and health care. Journal of Health Economics. 1993;12(4):431-457.
• Wagstaff A, van Doorslaer E. Equity in health care finance and delivery. In: Culyer AJ, Newhouse JP, editors. Handbook of Health Economics, Volume 1B. Elsevier. 2000. Chapter 34, pp. 1803-1862.
• Whitehead M. The concepts and principles of equity and health. Health Promotion International. 1991;6(3):217-228.
• Wagstaff A, Paci P, van Doorslaer E. On the measurement of inequalities in health. Social Science and Medicine. 1991;33(5):545-557.
• Kakwani NC. Measurement of tax progressivity: an international comparison. Economic Journal. 1977;87(345):71-80.
• O'Donnell O, van Doorslaer E, Wagstaff A, Lindelow M. Analyzing Health Equity Using Household Survey Data: A Guide to Techniques and Their Implementation. World Bank. 2008.
• Asaria M, Griffin S, Cookson R. Distributional cost-effectiveness analysis: a tutorial. Medical Decision Making. 2016;36(1):8-19.
• Cookson R, Griffin S, Norheim OF, Culyer AJ, editors. Distributional Cost-Effectiveness Analysis: Quantifying Health Equity Impacts and Trade-Offs. Oxford University Press. 2020.
• Verguet S, Kim JJ, Jamison DT. Extended cost-effectiveness analysis for health policy assessment: a tutorial. PharmacoEconomics. 2016;34(9):913-923.
• National Institute for Health and Care Excellence. NICE technology appraisal and highly specialised technologies guidance: the manual (PMG36). Published 31 January 2022, last updated 13 October 2026.