Abstract

PurposeThe aim of this work was to develop a mapping algorithm for estimating EuroQoL 5 Dimension (EQ-5D) utilities from responses to the Long-Term Conditions Questionnaire (LTCQ), thus increasing LTCQ’s potential as a comprehensive outcome measure for evaluating integrated care initiatives.MethodsWe combined data from three studies to give a total sample of 1334 responses. In each of the three datasets, we randomly selected 75% of the sample and combined the selected random samples to generate the estimation dataset, which consisted of 1001 patients. The unselected 25% observations from each dataset were combined to generate an internal validation dataset of 333 patients. We used direct mapping models by regressing responses to the LTCQ-8 directly onto EQ-5D-5L and EQ-5D-3L utilities as well as response (or indirect) mapping to predict the response level that patients selected for each of the five EQ-5D-5L domains. Several models were proposed and compared on mean squared error and mean absolute error.ResultsA two-part model with OLS was the best performing based on the mean squared error (0.038) and mean absolute error (0.147) when estimating the EQ-5D-5L utilities. A multinomial response mapping model using LTCQ-8 responses was used to predict EQ-5D-5L responses levels.ConclusionsThis study provides a mapping algorithm for estimating EQ-5D utilities from LTCQ responses. The results from this study can help broaden the applicability of the LTCQ by producing utility values for use in economic analyses.

Highlights

  • In the global context of ageing populations who are likely to experience multi-morbidity, there is an increasing drive towards integrated models of care that bring together formal health services, social care provision, and community-based services to support local population needs [1, 2]

  • The valuation of the EuroQoL 5 Dimension (EQ-5D)-5L was based on the UK value set [15] and the cross-walk to derive EQ-5D-3L utilities [16] following the latest position of National Institute for Health and Care Excellence (NICE) [12]

  • A similar mean utility was recorded in the baseline dataset from the Feeling Safe study among a sample with mental health conditions and a higher utility recorded in the sample with dementia or mild cognitive impairment from the additional validation of the Long-Term Conditions Questionnaire (LTCQ)

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Summary

Introduction

In the global context of ageing populations who are likely to experience multi-morbidity, there is an increasing drive towards integrated models of care that bring together formal health services, social care provision, and community-based services to support local population needs [1, 2]. For example in England, the economic impacts of integrated care initiatives (including pooled budgets) between Clinical Commissioning Groups responsible for health care planning and Local Authorities responsible for social care provision need to be assessed via outcomes relevant for both health and social care (e.g. well-being, independence). Most existing outcome measures for economic evaluation, such as the EQ-5D [3], are based on the construct of Health-Related Quality of Life (HRQoL). HRQoL and SCRQoL are each arguably too narrow for evaluating integrated health and social care interventions, which will simultaneously seek to minimise symptom burden (and associated use of health resources) and to maximise the efficacy of social support for ‘living well’ in its broadest sense

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