Abstract

BackgroundEconomic evaluation normally requires information to be collected on outcome improvement using utility values. This is often not collected during the treatment of substance use disorders making cost-effectiveness evaluations of therapy difficult. One potential solution is the use of mapping to generate utility values from clinical measures. This study develops and evaluates mapping algorithms that could be used to predict the EuroQol-5D (EQ-5D-5 L) and the ICEpop CAPability measure for Adults (ICECAP-A) from the three commonly used clinical measures; the CORE-OM, the LDQ and the TOP measures.MethodsModels were estimated using pilot trial data of heroin users in opiate substitution treatment. In the trial the EQ-5D-5 L, ICECAP-A, CORE-OM, LDQ and TOP were administered at baseline, three and twelve month time intervals. Mapping was conducted using estimation and validation datasets. The normal estimation dataset, which comprised of baseline sample data, used ordinary least squares (OLS) and tobit regression methods. Data from the baseline and three month time periods were combined to create a pooled estimation dataset. Cluster and mixed regression methods were used to map from this dataset. Predictive accuracy of the models was assessed using the root mean square error (RMSE) and the mean absolute error (MAE). Algorithms were validated using sample data from the follow-up time periods.ResultsMapping algorithms can be used to predict the ICECAP-A and the EQ-5D-5 L in the context of opiate dependence. Although both measures can be predicted, the ICECAP-A was better predicted by the clinical measures. There were no advantages of pooling the data. There were 6 chosen mapping algorithms, which had MAE scores ranging from 0.100 to 0.138 and RMSE scores ranging from 0.134 to 0.178.ConclusionIt is possible to predict the scores of the ICECAP-A and the EQ-5D-5 L with the use of mapping. In the context of opiate dependence, these algorithms provide the possibility of generating utility values from clinical measures and thus enabling economic evaluation of alternative therapy options.Trial registrationISRCTN22608399. Date of registration: 27/04/2012. Date of first randomisation: 14/08/2012.

Highlights

  • Economic evaluation normally requires information to be collected on outcome improvement using utility values

  • This study aims to map three clinical instruments that are often used in the routine care of addiction and opiate dependence (CORE-OM, Leeds Dependence Questionnaire (LDQ), and Treatment Outcomes Profile (TOP)) onto the EQ-5D-5 L and ICECAP-A measures, generating algorithms that can be used in future studies to aid reimbursement decisions in the absence of information related to EQ-5D-5 L and ICECAP-A

  • Similar to the CORE-OM measure, the results indicated that most models predicted the EQ-5D-5 L and ICECAP-A index scores closely in both samples and for both estimation approaches

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Summary

Introduction

Economic evaluation normally requires information to be collected on outcome improvement using utility values. This is often not collected during the treatment of substance use disorders making cost-effectiveness evaluations of therapy difficult. One potential solution is the use of mapping to generate utility values from clinical measures. In many healthcare systems around the world, resources are scarce and the demand for healthcare outweighs supply This scarcity warrants the need for economic evaluation to aid decision makers with information about the most efficient use of resources in order to maximise the health gained for every unit of currency spent. The outcomes of a cost-utility analysis are expressed in quality-adjusted life years (QALYs) [1]. The EQ-5D-5 L describes HRQOL through the dimensions of mobility, self-care, usual activities, pain and discomfort, and anxiety and depression

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