Valuation of Health State Using Virtual Reality (ReV-UTIL)

Valuation of Health States in the French General Population: Role and Interest of an Innovative Approach Based on Virtual Reality

Financials constraints of health systems require suitable indices and criteria to better allocate resources in order to enhance and maximize social welfare. Among multiple methods, the quality-adjusted life year (QALY) is used as a validated and preference-base measure for health care procedures in health economics studies such as cost-utility analyses.

In France, the methodological guide of the public agency of the High Authority for Health (HAS) recommends the valuation of health states with the use of a generic and descriptive instrument (EQ5D), validated by the Time Trade Off method (TTO) in samples from general French population.

Although it appears to be legitimate to distribute collective resources based on general population preferences, a major concern is that individuals do not face a real choice that can have a direct implication on their welfare and their life.

The existence of a discrepancy between revealed "hypothetical" preferences and real preferences would raise the problem concerning production of the currently available standards and norms. Hence, a methodological deepening of these preferences revelation process is necessary.

Virtual reality (VR) could play a key role in resolving this methodological problem. Widely used in the field of health (such as therapy, medical training...), VR is a simulation that seeks to approach the reality, without trying to be quite like it. It aims one or more individuals to explore a sensorimotor and cognitive activity in an artificial world in 3D, which can be "imaginary, symbolic or a simulation of some aspects of the real world" (Fuchs, 2006). VR could be well applied to the field of health economics by offering hypothetical scenarios of the different health states from the EQ5D that individuals might experience in the first person.

To date, existence of this discrepancy between revealed "hypothetical" preferences and actual preferences of individuals from the general population is extremely difficult to explore. However, this is an important methodological challenge in the revelation of preferences to guide health-related decisions.

Indeed, comparing the revealed preferences about health states established from a first person experience in VR to the revealed preferences established from the classic narrative approach without VR, may provide an accurate approach of actual and real preferences of individuals from the general population.

Moreover, another advantage of VR is to permit the assessment of a greater number of health states, this method being faster processed than the narrative approach: individuals are experimenting immediate experience of a situation when under VR. Thus, VR method may overcome technical constraints of the classic narrative approach concerning limited sample sizes in norms production.

To the investigators knowledge, VR has never been proposed for valuating health conditions.

This study would report the relevance and interest in using VR (immersive and immediate life situation experience) for the production of utility EQ5D health states values in the general population by the revelation of preferences method called the Time Trade Off (TTO), the currently approach recommended by the HAS.

Using VR could circumvent some limitations of the current narrative approach: it would provide a better feasibility and acceptability among subjects, fewer inconsistencies, an easier and wider access to disadvantaged individuals. Eventually revisions of available standards could be proposed to allow the HAS and policy makers to base their choices on more reliable, standardized and accurate classifications of health states conditions, that associate each health state to a predefined value.

Study Overview

• Status: Unknown
• Conditions: Public Health
• Intervention / Treatment: Procedure: Virtual reality experimentation sequency (VR); Procedure: Classical narrative approach (CN)

• Study Type: Interventional
• Enrollment (Anticipated): 140
• Phase: Not Applicable

Contacts and Locations

Study Locations

• France
  • Marseille, France, 13354
    • Assistance Publique Hopitaux de Marseille

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• Subject without major vision problem, judged clinically
• Subject without major auditive problem, judged clinically

Exclusion Criteria:

• Subject unable to read and understand French
• Subject covered by a the french social security system

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Crossover Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Group 1; First,Virtual reality approach (VR), then classical narrative approach (CN)	Procedure: Virtual reality experimentation sequency (VR); Procedure: Classical narrative approach (CN)
Active Comparator: Group 2; First, classical narrative approach (CN), then virtual reality approach	Procedure: Virtual reality experimentation sequency (VR); Procedure: Classical narrative approach (CN)

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Time Frame
Average number of overall inconsistency produced by an individual following health states preferences elicitation test under VR compared to test under the classic and conventional narrative approaches	6 hours

Collaborators and Investigators

• Sponsor: Assistance Publique Hopitaux De Marseille
• Investigators: Study Director: Ureielle DESALBRES, Assistance Publique Hopitaux de Marseille; Principal Investigator: Pascal AUQUIER, MD-PhD, Assistance Publique Hopitaux de Marseille

Study record dates

Study Major Dates

• Study Start: January 1, 2017
• Primary Completion (Anticipated): January 1, 2020
• Study Completion (Anticipated): January 1, 2021

Study Registration Dates

• First Submitted: September 12, 2016
• First Submitted That Met QC Criteria: September 19, 2016
• First Posted (Estimate): September 20, 2016

Study Record Updates

• Last Update Posted (Estimate): September 20, 2016
• Last Update Submitted That Met QC Criteria: September 19, 2016
• Last Verified: September 1, 2016

More Information

Terms related to this study

• Other Study ID Numbers: RCAPHM16_0016

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO