A Comparison of direct and indirect methods for the estimation of health utilities from clinical outcomes

Mónica Hernández Alava, Allan Wailoo, Fred Wolfe, Kaleb Michaud

Research output: Contribution to journalArticle

23 Scopus citations

Abstract

Background: Analysts frequently estimate health state utility values from other outcomes. Utility values like EQ-5D have characteristics that make standard statistical methods inappropriate. We have developed a bespoke, mixture model approach to directly estimate EQ-5D. An indirect method, "response mapping," first estimates the level on each of the 5 dimensions of the EQ-5D and then calculates the expected tariff score. These methods have never previously been compared.

Results: The linear model fits poorly, particularly at the extremes of the distribution. The bespoke mixture model and the indirect approaches improve fit over the entire range of EQ-5D. Mean average error is 10% and 5% lower compared with the linear model, respectively. Root mean squared error is 3% and 2% lower. The mixture model demonstrates superior performance to the indirect method across almost the entire range of pain and HAQ. These lead to differences in cost-effectiveness of up to 20%.

Methods: We use a large observational database from patients with rheumatoid arthritis (N = 100,398). Direct estimation of UK EQ-5D scores as a function of the Health Assessment Questionnaire (HAQ), pain, and age was performed with a limited dependent variable mixture model. Indirect modeling was undertaken with a set of generalized ordered probit models with expected tariff scores calculated mathematically. Linear regression was reported for comparison purposes. Impact on cost-effectiveness was demonstrated with an existing model.

Conclusions: There are limited data from patients in the most severe HAQ health states. Modeling of EQ-5D from clinical measures is best performed directly using the bespoke mixture model. This substantially outperforms the indirect method in this example. Linear models are inappropriate, suffer from systematic bias, and generate values outside the feasible range.

Original languageEnglish (US)
Pages (from-to)919-930
Number of pages12
JournalMedical Decision Making
Volume34
Issue number7
DOIs
StatePublished - Oct 1 2014

Keywords

  • EQ-5D
  • mapping
  • rheumatoid arthritis
  • statistical methods

ASJC Scopus subject areas

  • Health Policy

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