Concept Architecture
Concept
Theoretically, Strict Dominance is a decision rule in economic evaluation whereby one intervention is considered unequivocally inferior because it is both more costly and less effective than an alternative. It is based on Pareto efficiency and decision theory and exists to eliminate inefficient options from consideration before incremental analysis is undertaken. In health economics, strict dominance forms a fundamental step in cost-effectiveness analysis and the construction of the efficiency frontier.
Mathematically, Strict Dominance is defined by simultaneous comparison of incremental costs and incremental health effects. An intervention is strictly dominated when it has higher costs and lower effectiveness than a comparator. Such interventions are excluded from further economic evaluation because no rational decision-maker seeking to maximise health outcomes for available resources would choose them.
In practice, Strict Dominance is identified by ordering interventions according to increasing effectiveness and comparing costs and outcomes between alternatives. Dominated interventions are removed before calculating incremental cost-effectiveness ratios or performing fully incremental analyses, ensuring that only non-dominated interventions remain on the efficiency frontier.
Purpose
Used to identify and eliminate interventions that are both more costly and less effective than an alternative before conducting incremental cost-effectiveness analysis.
Mathematical Formulae
Primary Formula
Intervention A is strictly dominated by intervention B if:
C? > C?
and
E? < E?
where:
- C = total cost
- E = total health effect
Supporting Formulae
Equivalent incremental form:
?C > 0
and
?E < 0
where:
- ?C = C? ? C?
- ?E = E? ? E?
Related Mathematical Methods
- Dominance Analysis
- Fully Incremental Analysis
- Incremental Cost-Effectiveness Ratio
- Efficiency Frontier
- Extended Dominance
Example
Three interventions are compared:
| Intervention | Cost (�) | QALYs |
|---|---|---|
| Standard Care | 8,000 | 4.20 |
| Treatment A | 9,500 | 4.00 |
| Treatment B | 10,500 | 4.60 |
Treatment A costs �1,500 more than Standard Care while producing 0.20 fewer QALYs.
?C = 9,500 ? 8,000 = �1,500
?E = 4.00 ? 4.20 = ?0.20
Because costs are higher and effectiveness is lower, Treatment A is strictly dominated and is excluded before incremental analysis.
Excel Implementation
| Function | Example Formula | Health Economics Application |
|---|---|---|
| IF | =IF(AND(B2>B1,C2<C1),""Strictly Dominated"",""Retain"") | Identifies strictly dominated interventions |
| AND | =AND(B2>B1,C2<C1) | Tests the dominance conditions |
| SORT | =SORT(A2:C10,3,1) | Orders interventions by effectiveness before dominance analysis |
| FILTER | =FILTER(A2:C10,D2:D10<>""Strictly Dominated"") | Removes dominated interventions prior to incremental analysis |
VBA (Optional)
Automate identification and removal of strictly dominated interventions before calculating incremental cost-effectiveness ratios and efficiency frontiers.
Sources
- Drummond MF, Sculpher MJ, Claxton K, Stoddart GL, Torrance GW. Methods for the Economic Evaluation of Health Care Programmes. Oxford University Press.
- Briggs A, Claxton K, Sculpher M. Decision Modelling for Health Economic Evaluation. Oxford University Press.
- Black WC. The CE plane: a graphic representation of cost-effectiveness. Medical Decision Making. 1990;10(3):212?214.
- Gold MR, Siegel JE, Russell LB, Weinstein MC. Cost-Effectiveness in Health and Medicine. Oxford University Press.
Related Concepts (2)
Library
Publications
2
Methods for the Economic Evaluation of Health Care Programmes — Drummond, Sculpher, Claxton, Stoddart & Torrance, 4th Edition ed., 2015 (Oxford University Press)
The standard international reference text for economic evaluation methods in health care, covering cost-effectiveness, cost-utility and cost-benefit analysis, measurement of costs and outcomes, evidence synthesis, and the characterisation of uncertainty.
BookView source →Applied Methods of Cost-Effectiveness Analysis in Healthcare — Gray, Clarke, Wolstenholme & Wordsworth, 1st Edition ed., 2011 (Oxford University Press)
A practical, worked-example guide to conducting cost-effectiveness analysis, structured around outcomes, costs, modelling with decision trees and Markov models, and presenting results. Volume 3 in the Handbooks in Health Economic Evaluation series, developed from the University of Oxford course.
BookView source →
Economic evaluation — National Institute for Health and Care Excellence, Technology appraisal and highly specialised technologies guidance manual ed., 2026 (NICE)
Official methods guidance for comparative economic evaluation, including incremental analysis, ICERs, comparators and the treatment of dominated options.
Web GuidanceView source →
Frequently Asked Questions (6)
What is strict dominance?
A situation where one intervention is unambiguously better than another because it is both less costly and more effective.
Source: Drummond MF, Sculpher MJ, Claxton K, Stoddart GL, Torrance GW. Methods for the Economic Evaluation of Health Care Programmes. 4th ed. Oxford University Press; 2015.
How is strict dominance established?
By comparing two options directly on both dimensions and finding that one costs less and produces more health. No threshold is required and no value judgement enters, since no willingness to pay could justify choosing an option that is worse on both counts. This makes it the strongest conclusion available in economic evaluation and the only one that survives disagreement about what a unit of health is worth. It can therefore be established by inspection as soon as costs and effects are tabulated, without any of the subsequent analysis being performed.
Source: Drummond et al. 2015
How does strict dominance differ from extended dominance?
Strict dominance means a single alternative beats the option on both cost and effect. Extended dominance means no single alternative does, but a combination of two others would deliver the same or more health for less money. An extendedly dominated option therefore survives the first inspection and must be removed by a separate check, and analyses stopping at strict dominance leave options on the frontier that a mixture would beat. The two are frequently conflated in reporting, and an analysis describing an option as dominated should say which form applies, since extended dominance rests on the additional assumption that options can be mixed.
Source: Drummond et al. 2015
Where does strict dominance occur in practice?
Most often where a cheaper technology outperforms an established one, as with generic substitution or with devices whose price has fallen while performance improved, and where a reorganisation of care both improves outcomes and reduces resource use. It is less common than published claims suggest, since submissions asserting both lower cost and better outcomes frequently rest on optimistic assumptions about avoided downstream care that would not survive scrutiny. Where a claim of dominance rests on avoided downstream costs rather than a lower unit price, the evidence for those avoided events deserves the same scrutiny as the effectiveness evidence.
Source: Drummond et al. 2015
Does strict dominance survive uncertainty?
Not always. It is established from point estimates, and once distributions are considered the ranges of cost and effect can overlap enough that the apparently dominated option is better in some simulations. Where a meaningful share of the distribution falls that way, describing the result as dominance overstates the conclusion. Reporting the proportion of simulations in which dominance holds is more informative than asserting it from the central estimate. Reporting the proportion of simulations falling in each quadrant is the informative presentation, since it shows how securely the result is established.
Source: Briggs, Claxton & Sculpher 2006
Why does strict dominance matter procedurally?
Because it must be checked before any ratio is calculated. An incremental ratio computed against a dominated option produces a figure that looks favourable and describes a comparison nobody should be making. Removing dominated options first, then calculating ratios between the survivors in order of increasing effect, is the correct sequence, and departing from it can recommend an option that is not the best available at any threshold. The check is also the reason results tables should list every option considered, including those removed, so a reader can verify that the sequence was applied correctly.
Source: Drummond et al. 2015
Trust Record
Verified by Dr Darrin Baines
British health economist
Professional identity: darrinbaines.org
Verification date: 8 Aug 2025
Content version: 1.0.0
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- Persistent URI
- https://healtheconomics.wiki/concept/strict-dominance
- Term code
- HE-EE-CEA-063
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