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Related Experiment Video

Updated: Dec 12, 2025

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
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Estimating EQ-5D utilities based on the Short-Form Long Term Conditions Questionnaire (LTCQ-8).

Apostolos Tsiachristas1, Caroline M Potter2, Stephen Rocks3

  • 1Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Richard Doll Building, Old Road Campus, Oxford, OX3 7LF, UK. apostolos.tsiachristas@ndph.ox.ac.uk.

Health and Quality of Life Outcomes
|August 16, 2020
PubMed
Summary

A new mapping algorithm estimates EuroQoL 5 Dimension (EQ-5D) utilities from Long-Term Conditions Questionnaire (LTCQ) data. This enhances the LTCQ

Keywords:
EQ-5D-5LIntegrated careLTCQMappingPROMsQuality of life

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Area of Science:

  • Health Economics
  • Outcomes Research
  • Psychometrics

Background:

  • The Long-Term Conditions Questionnaire (LTCQ) is a valuable tool for assessing patient health.
  • Estimating EuroQoL 5 Dimension (EQ-5D) utilities from LTCQ responses can expand its utility in economic evaluations.
  • Integrated care initiatives require comprehensive outcome measures for effective evaluation.

Purpose of the Study:

  • To develop and validate a mapping algorithm for converting Long-Term Conditions Questionnaire (LTCQ) responses into EuroQoL 5 Dimension (EQ-5D) utility values.
  • To enhance the LTCQ's utility as a comprehensive outcome measure for integrated care evaluations.
  • To facilitate economic analyses by providing EQ-5D utility estimates from LTCQ data.

Main Methods:

  • Combined data from three studies (N=1334) into estimation (N=1001) and internal validation (N=333) datasets.
  • Employed direct mapping models (regressing LTCQ-8 onto EQ-5D utilities) and response mapping models (predicting EQ-5D domain responses).
  • Compared several models based on mean squared error (MSE) and mean absolute error (MAE) for performance evaluation.

Main Results:

  • A two-part ordinary least squares (OLS) model demonstrated the best performance for estimating EQ-5D-5L utilities, with MSE of 0.038 and MAE of 0.147.
  • A multinomial response mapping model effectively predicted EQ-5D-5L response levels using LTCQ-8 data.
  • The developed algorithm provides a reliable method for generating utility values from LTCQ responses.

Conclusions:

  • A validated mapping algorithm now exists to estimate EQ-5D utilities from LTCQ responses.
  • This algorithm significantly broadens the applicability of the LTCQ, particularly in economic analyses.
  • The findings support the use of LTCQ in evaluating integrated care initiatives by providing crucial utility data.