The use of health state utility values in decision models
As preference-based HRQoL data are often not collected in clinical trials, these data are frequently sourced from the literature. It is inappropriate to assume the baseline is perfect health if an individual does not have a specific health condition and while ideally the baseline HSUVs would be obta...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
London
National Institute for Health and Clinical Excellence (NICE)
2011, July 2011
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| Series: | NICE DSU technical support document
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| Online Access: | |
| Collection: | National Center for Biotechnology Information - Collection details see MPG.ReNa |
| Summary: | As preference-based HRQoL data are often not collected in clinical trials, these data are frequently sourced from the literature. It is inappropriate to assume the baseline is perfect health if an individual does not have a specific health condition and while ideally the baseline HSUVs would be obtained from cohorts without the health conditions or events modelled, this is not always possible. When these data are not available, using average values from the general population may be appropriate, particularly for less prevalent health conditions and those that do not have a substantial effect on HRQoL. Adjusting/combining HSUVs: Many of the economic models submitted to the Institute use HSUVs estimated for individuals with comorbidities using data from cohorts with single specific conditions. There is currently no consensus on the most appropriate technique and the standard methods used to adjust for comorbidities (such as the multiplicative, additive or minimum methods) generate very different values. These estimated values can have substantial errors when compared to the actual values. The existing evidence base is inconclusive and additional research is required to validate emerging techniques which appear promising. In the interim period, to facilitate consistency and thus comparison of results we would recommend the multiplicative method, using adjusted baselines, is used. Capturing uncertainty in HSUVS: Capturing uncertainty in economic model parameters is a key requirement of submissions to the Institute. Typically however, the uncertainty in the estimation of preference-based valuation weights has been ignored. Specifically we look at the data used to represent the HSUVs for individuals who do not have particular health conditions (i.e. the baseline used in calculating the incremental gain), the methods used to combine HSUVs for comorbidities and the methods used to capture uncertainty in HSUVs. We describe the current evidence base in this area, provide practical advice where possible, and identify areas where current knowledge does not permit detailed guidance to be offered and additional research is warranted. Baseline HRQoL data: When the HRQoL data in an economic model are derived from a randomised controlled trial, the HSUVs collected in the control group represent the baseline HRQoL and the HSUVs collected in the active treatment arm are used together with the baseline data to calculate the incremental QALY gain associated with treatment. Consequently the HSUVs used to inform both the baseline and the health status of the events and conditions are of equal importance. In order to be able to incorporate this aspect of uncertainty, analysts require the relevant data be made available from the developers of these preference weights. We provide the required data for the Institute's preferred instrument (EQ-5D). When data are predicted using relationships between variables, the uncertainty in the coefficients should be characterised and used in the probabilistic sensitivity analyses. Capturing uncertainty in synthesised data is a developing area and until suitable techniques are identified and published, a full range of univariate sensitivity analyses should be conducted to explore the effect on results from the economic model The National Institute for Health and Clinical Excellence (NICE) provides recommendations on health related quality of life (HRQoL) data used in submissions in their Guide to the Methods of Technology Appraisal. As different measures can produce different health state utility values (HSUV), the Institute state a preference for EQ-5D data to facilitate comparison across disease areas and interventions. However, inconsistencies in the methodologies used when applying HSUVs in economic models will produce discrepancies in results generated from decision analytic models, even when using the same measure, thus undermining policy decision making based on cost per quality adjusted life year (QALY) thresholds. The objective of this Technical Support Document is to provide guidance on some of the practical issues that arise when using utility data in economic models. |
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| Physical Description: | 1 PDF file (30 pages) |