Public versus patient health preferences: protocol for a study to elicit EQ-5D-5L health state valuations for patients who have survived a stay in intensive care

INTRODUCTION: The value set used when calculating quality-adjusted life-years (QALYs) is most often based on stated preference data elicited from a representative sample of the general population. However, having a severe disease may alter a person’s health preferences, which may imply that, for some patient groups, experienced QALYs may differ from those that are estimated via standard methods. This study aims to model 5-level EuroQol 5-dimensional questionnaire (EQ-5D-5L) valuations based on preferences elicited from a sample of patients who have survived a stay in a Danish intensive care unit (ICU) and to compare these with the preferences of the general population. Further, the heterogeneity in the ICU patients’ preferences will be investigated. METHODS AND ANALYSIS: This valuation study will elicit EQ-5D-5L health state preferences from a sample of 300 respondents enrolled in two randomised controlled trials at Danish ICUs. Patients’ preferences will be elicited using composite time trade-off based on the EuroQol Valuation Technology, the same as that used to generate the EQ-5D-5L value set for the Danish general population. The patient-based and the public-based EQ-5D-5L valuations will be compared. Potential underlying determinants of the ICU preferences will be investigated through analyses of demographic characteristics, time since the ICU stay, self-reported health, willingness to trade-off length of life for quality of life, health state reference dependency and EQ-5D dimensions that patients have experienced themselves during their illness. ETHICS AND DISSEMINATION: Under Danish regulations, ethical approval is not required for studies of this type. Written informed consent will be obtained from all patients. The study results will be published in peer-reviewed scientific journals and presented at national and international conferences. The modelling algorithms will be publicly available for statistical software, such as Stata and R.