Estimating health state utility values for comorbid health conditions: a synopsis of the current evidence base

Background: Analysts frequently estimate the health state utility values (HSUVs) for combined health conditions (CHCs) using data from cohorts with single health conditions. The methods used to estimated the HSUVs can produce very different results and there is currently no consensus on the most appropriate technique that should be used. Objective: To conduct a detailed critical review of existing empirical literature to gain an understanding of the reasons for differences in results and identify where uncertainty remains that may be addressed by further research. Results: Of the eleven studies identified, ten assessed the additive method, ten the multiplicative method, seven the minimum method, and three the combination model. Two studies evaluated just one of the techniques while the others compared results generated using two or more. The range of the HSUVs can influence general findings and methods are sometimes compared using descriptive statistics that may not be appropriate for assessing predictive ability. None of the proposed methods gave consistently accurate results across the full range of possible HSUVs and the values assigned to normal health influence the accuracy of the methods. Conclusions: While there is no unequivocal evidence for supporting one particular method, the combination linear model appeared to give more accurate results in the studies reviewed. However, before a method can be recommended, research is required in datasets covering the full range of the preference-based indices and health conditions typically defined in decision analytic models. The methods used to assess performance and the statistics used when reporting results require improvement in general

Weighting must wait: incorporating equity concerns into cost effectiveness analysis may take longer than expected

Current practice in economic evaluation is to assign equal social value to a unit of health improvement (“a QALY is a QALY is a QALY”). Alternative views of equity are typically considered separately to efficiency. One proposal seeks to integrate these two sets of societal concerns by attaching equity weights to QALYs. To date, research in pursuit of this goal has focussed on candidate equity criteria and methods for estimating such weights. It has implicitly been assumed that should legitimate, valid, and reliable equity weights become available, it would be a straightforward task to incorporate them into as a separate simple calculation after estimating cost per unweighted QALY. This paper suggests that in many situations these simple approaches to incorporating equity weights will not appropriately reflect the preferences on which the weights are based and therefore equity weights must be incorporated directly into the cost effectiveness analysis. In addition to these technical issues, there are a number of practical challenges that arise from the movement from implicit to explicit consideration of equity. Equity weights should be incorporated in economic evaluation, but not until these challenges have been appropriately addressed

Multilevel modelling of cost data: an application to thrombolysis and primary angioplasty in the UK NHS

Cost data are frequently collected from several locations and tend to be non negative and skewed. Generalised linear multilevel models provide a means of dealing with each of these issues. This paper compares several statistical models within this class using data drawn from an observational study of 3,000 patients treated for heart attack in 15 UK NHS hospitals. A number of alternative link functions and covariates were considered. We demonstrate that whilst it is important to take account of clustering in the data, the precise manner in which this is done is equally important. Models which allow for correlation between the random effects components and heteroskedasticity across all hospitals performed best in terms of model fit and made substantial di¤erences to cost estimates

Efficiency, equity, and NICE clinical guidelines

The stated purpose of clinical guidelines from the United Kingdom's National Institute for Clinical Excellence (NICE) is to "help healthcare professionals and patients make the right decisions about healthcare in specific clinical circumstances." However, what constitutes "the right decisions" depends on your point of view. For individual patients the right decision is that which maximises their wellbeing, and this is properly the concern of the clinician. Yet in resource constrained healthcare systems this will not always coincide with the right decisions for patients in general or society as a whole, thereby leading to some understandable tensions. NICE is a national policy making body whose responsibility is clearly broader than the individual patient. This wider viewpoint is reflected in NICE's technology appraisals by the central role afforded to cost effectiveness. We argue that the methods currently used by the NICE clinical guideline programme confuse these two viewpoints

Weighting must wait: incorporating equity concerns into cost effectiveness analysis may take longer than expected

Current practice in economic evaluation is to assign equal social value to a unit of health improvement (“a QALY is a QALY is a QALY”). Alternative views of equity are typically considered separately to efficiency. One proposal seeks to integrate these two sets of societal concerns by attaching equity weights to QALYs. To date, research in pursuit of this goal has focussed on candidate equity criteria and methods for estimating such weights. It has implicitly been assumed that should legitimate, valid, and reliable equity weights become available, it would be a straightforward task to incorporate them into as a separate simple calculation after estimating cost per unweighted QALY. This paper suggests that in many situations these simple approaches to incorporating equity weights will not appropriately reflect the preferences on which the weights are based and therefore equity weights must be incorporated directly into the cost effectiveness analysis. In addition to these technical issues, there are a number of practical challenges that arise from the movement from implicit to explicit consideration of equity. Equity weights should be incorporated in economic evaluation, but not until these challenges have been appropriately addressed

Weighting must wait: incorporating equity concerns into cost effectiveness analysis may take longer than expected

Current practice in economic evaluation is to assign equal social value to a unit of health improvement (“a QALY is a QALY is a QALY”). Alternative views of equity are typically considered separately to efficiency. One proposal seeks to integrate these two sets of societal concerns by attaching equity weights to QALYs. To date, research in pursuit of this goal has focussed on candidate equity criteria and methods for estimating such weights. It has implicitly been assumed that should legitimate, valid, and reliable equity weights become available, it would be a straightforward task to incorporate them into as a separate simple calculation after estimating cost per unweighted QALY. This paper suggests that in many situations these simple approaches to incorporating equity weights will not appropriately reflect the preferences on which the weights are based and therefore equity weights must be incorporated directly into the cost effectiveness analysis. In addition to these technical issues, there are a number of practical challenges that arise from the movement from implicit to explicit consideration of equity. Equity weights should be incorporated in economic evaluation, but not until these challenges have been appropriately addressed

Tails from the Peak District: adjusted censored mixture models of EQ-5D health state utility values

Health state utility data generated using the EQ-5D instrument are typically right bounded at one with a substantial gap to the next set of observations, left bounded by some negative value, and are multi modal. These features present challenges to the estimation of the e¤ect of clinical and socioeconomic characteristics on health utilities. We present an adjusted censored model and then use this in a flexible, mixture modelling framework to address these issues. We demonstrate superior performance of this model compared to linear regression and Tobit censored regression using a dataset from repeated observations of patients with rheumatoid arthritis. We �nd that three latent classes are appropriate in estimating EQ-5D from function, pain and sociodemographic factors. Analysis of utility data should apply methods that recognise the distributional features of the data

Tails from the Peak District: adjusted censored mixture models of EQ-5D health state utility values

Health state utility data generated using the EQ-5D instrument are typically right bounded at one with a substantial gap to the next set of observations, left bounded by some negative value, and are multi modal. These features present challenges to the estimation of the e¤ect of clinical and socioeconomic characteristics on health utilities. We present an adjusted censored model and then use this in a flexible, mixture modelling framework to address these issues. We demonstrate superior performance of this model compared to linear regression and Tobit censored regression using a dataset from repeated observations of patients with rheumatoid arthritis. We �nd that three latent classes are appropriate in estimating EQ-5D from function, pain and sociodemographic factors. Analysis of utility data should apply methods that recognise the distributional features of the data