Concept Architecture
Concept
Theoretically, Value Set Development is the methodological process through which preference-based values are estimated for the health states defined by a health-related quality-of-life instrument. It is grounded in expected utility theory, stated preference theory and psychometric measurement, providing a systematic method for representing the relative social value of different health states. In health economics, value set development enables generic or condition-specific descriptive systems to generate utility scores for cost-utility analysis.
Mathematically, value set development estimates a function linking health-state characteristics to elicited preference values. Data obtained through time trade-off, standard gamble, discrete choice experiments or hybrid designs are analysed using regression models that account for repeated observations, censoring, heteroskedasticity and the bounded nature of utility values. The estimated coefficients are used to predict values for the complete set of health states described by the instrument.
In practice, representative samples complete structured valuation tasks for selected health states generated through an experimental design. Responses undergo quality control and are analysed using candidate statistical models. Model selection considers theoretical consistency, predictive accuracy, logical ordering and goodness of fit. The final model produces a jurisdiction-specific value set for use in health technology assessment and economic evaluation.
Purpose
Used to estimate population-based preference values for health states and construct scoring systems that convert health-status responses into utilities for quality-adjusted life-year calculation.
Mathematical Formulae
Primary Formula
U(s) = ?? + ???x? + �
where:
- U(s) = observed or predicted value of health state s
- x? = health-state dimension and severity indicators
- ?? = estimated preference coefficients
- � = error term
Supporting Formulae
Conditional logit probability for discrete choice data:
P?? = exp(V??) / ??exp(V??)
Hybrid likelihood:
Lhybrid = LTTO ? LDCE
Predicted health-state value:
?(s) = ??? + ????x?
Mean absolute error:
MAE = (1/n) ? ?|U? ? ??|
Related Mathematical Methods
- Time Trade-Off
- Standard Gamble
- Discrete Choice Experiment
- Hybrid Modelling
- Maximum Likelihood Estimation
- Regression Analysis
Example
A national valuation study collects time trade-off responses for 86 health states and discrete choices for 196 paired comparisons. A hybrid model estimates utility decrements for each dimension and severity level.
For a health state with estimated decrements of 0.06, 0.09 and 0.18:
?(s) = 1 ? (0.06 + 0.09 + 0.18)
?(s) = 0.67
The estimated model is then used to assign values to all health states described by the instrument.
Excel Implementation
| Function | Example Formula | Health Economics Application |
|---|---|---|
| LINEST | =LINEST(ValueRange,IndicatorMatrix,TRUE,TRUE) | Estimates a basic linear health-state valuation model. |
| SUMPRODUCT | =SUMPRODUCT(StateIndicators,CoefficientRange) | Predicts utility from estimated coefficients. |
| EXP | =EXP(B2)/SUM(EXP($B$2:$B$5)) | Calculates conditional logit probabilities for discrete choice data. |
| AVERAGE | =AVERAGE(ABS(ObservedRange-PredictedRange)) | Calculates mean absolute prediction error in dynamic-array Excel. |
| LET | =LET(Pred,1-SUMPRODUCT(B2:F2,$B$20:$F$20),Pred) | Applies the developed value set to a health-state profile. |
VBA (Optional)
VBA can automate health-state coding, application of candidate valuation models and validation summaries during value set development.
Sources
- Oppe M, Devlin NJ, van Hout B, Krabbe PFM, de Charro F. A programme of methodological research to arrive at the new international EQ-5D-5L valuation protocol. Value in Health.
- Devlin NJ, Shah KK, Feng Y, Mulhern B, van Hout B. Valuing health-related quality of life: an EQ-5D-5L value set for England. Health Economics.
- Brazier J, Ratcliffe J, Salomon JA, Tsuchiya A. Measuring and Valuing Health Benefits for Economic Evaluation. Oxford University Press.
- ISPOR Good Research Practices for Health-State Utility Estimation.
- NICE. Health Technology Evaluation Manual.
Related Concepts (3)
Library
Publications
1
NICE DSU Technical Support Document 8: An Introduction to the Measurement and Valuation of Health for NICE Submissions — Brazier, Rowen, TSD 8 ed., 2011 (NICE Decision Support Unit (University of Sheffield))
An introduction to the measurement and valuation of health for NICE submissions — the QALY, health-state utility values, generic preference-based measures, and the requirements of the NICE reference case.
Frequently Asked Questions (6)
What is value set development?
The process of designing, conducting, and analysing a population valuation study to produce a scoring algorithm for a health status instrument.
Source: Brazier et al. 2007
What expertise does value set development require?
Producing a value set draws on several skills at once. It needs survey design to present health states clearly, fieldwork to recruit and interview a representative sample, and statistical modelling to turn the responses into a formula covering every state. Each stage carries choices that a specialist must make, from the valuation technique used to the model form fitted. Because the output governs every later economic evaluation using the instrument, the work is treated as a substantial research undertaking in its own right. Oppe and colleagues (2014) describe the effort involved.
Source: Oppe et al. 2014
What are the stages of value set development?
Value set development proceeds through designing the study, including choosing the sample, the states to value, and the elicitation method; conducting the valuation, in which respondents value the selected states under a standardised protocol; and analysing the data, modelling the valuations to estimate weights for all states. Each stage, from design through elicitation to modelling, shapes the resulting value set, and the process is documented so the value set can be appraised.
Source: Brazier et al. 2007
Why is value set development demanding?
Value set development is demanding because it requires eliciting valuations from a large, representative sample using a rigorous protocol, selecting states that support modelling of the whole descriptive system, and fitting models that extend the valued states to all states while respecting the properties of utilities. Each step involves methodological choices that affect the result, and errors propagate into the utilities. The effort and expertise required are why value sets are developed carefully and reused.
Source: Brazier et al. 2007
What choices affect value set development?
Key choices include the population sampled and whether it is representative; the elicitation method, such as the time trade-off or discrete choice experiment, which can yield different values; the states selected for direct valuation; the protocol governing the elicitation; and the modelling used to estimate weights for all states. Each choice influences the value set produced, so they are made deliberately and reported, since they determine the utilities the value set assigns.
Source: Brazier et al. 2007
How does value set development affect economic evaluation?
Value set development affects economic evaluation because it produces the utilities that weight length of life in quality-adjusted life years, so the design and conduct of the valuation study shape the outcome measure and hence the conclusions of evaluations. A value set from a flawed development may misrepresent preferences and bias results. Because the utilities used across many evaluations rest on it, sound value set development is important for the credibility of cost-utility analysis.
Source: Brazier et al. 2007
Trust Record
Verified by Dr Darrin Baines
British health economist
Professional identity: darrinbaines.org
Verification date: 2 Sep 2025
Content version: 1.0.0
Canonical Identity
- Term code
- HE-EE-HU-084
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