- ICH GCP
- US-Register für klinische Studien
- Klinische Studie NCT02907034
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.
Studienübersicht
Status
Bedingungen
Intervention / Behandlung
Studientyp
Einschreibung (Voraussichtlich)
Phase
- Unzutreffend
Kontakte und Standorte
Studienorte
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Marseille, Frankreich, 13354
- Assistance Publique Hôpitaux de Marseille
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Teilnahmekriterien
Zulassungskriterien
Studienberechtigtes Alter
Akzeptiert gesunde Freiwillige
Studienberechtigte Geschlechter
Beschreibung
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
Studienplan
Wie ist die Studie aufgebaut?
Designdetails
- Hauptzweck: Versorgungsforschung
- Zuteilung: Zufällig
- Interventionsmodell: Crossover-Aufgabe
- Maskierung: Keine (Offenes Etikett)
Waffen und Interventionen
Teilnehmergruppe / Arm |
Intervention / Behandlung |
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Experimental: Group 1
First,Virtual reality approach (VR), then classical narrative approach (CN)
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Aktiver Komparator: Group 2
First, classical narrative approach (CN), then virtual reality approach
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Was misst die Studie?
Primäre Ergebnismessungen
Ergebnis Maßnahme |
Zeitfenster |
|---|---|
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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
Zeitfenster: 6 hours
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6 hours
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Mitarbeiter und Ermittler
Ermittler
- Studienleiter: Ureielle DESALBRES, Assistance Publique Hôpitaux de Marseille
- Hauptermittler: Pascal AUQUIER, MD-PhD, Assistance Publique Hôpitaux de Marseille
Studienaufzeichnungsdaten
Haupttermine studieren
Studienbeginn
Primärer Abschluss (Voraussichtlich)
Studienabschluss (Voraussichtlich)
Studienanmeldedaten
Zuerst eingereicht
Zuerst eingereicht, das die QC-Kriterien erfüllt hat
Zuerst gepostet (Schätzen)
Studienaufzeichnungsaktualisierungen
Letztes Update gepostet (Schätzen)
Letztes eingereichtes Update, das die QC-Kriterien erfüllt
Zuletzt verifiziert
Mehr Informationen
Begriffe im Zusammenhang mit dieser Studie
Andere Studien-ID-Nummern
- RCAPHM16_0016
Plan für individuelle Teilnehmerdaten (IPD)
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