Gesundheitsökonomie & Qualitätsmanagement 2013; 18(4): 159-172
DOI: 10.1055/s-0032-1330500
Übersicht
© Georg Thieme Verlag KG Stuttgart · New York

Präferenzmessung im Gesundheitswesen: Grundlagen von Discrete-Choice-Experimenten

Measuring Preferences in Healthcare: Introduction to Discrete-Choice Experiments
A. C. Mühlbacher
,
S. Bethge
,
A. Tockhorn
Further Information

Publication History

Publication Date:
28 January 2013 (online)

Zusammenfassung

Discrete-Choice-Experimente werden zunehmend zur Präferenzmessung im Gesundheitswesen eingesetzt. Zielsetzung dieser Wahlmodellierung ist die Analyse von latenten Präferenzstrukturen, um Informationen über die Gestaltung, die Evaluation und die Prognose der Nachfrage oder Akzeptanz von Gesundheitsprodukten oder -dienstleistungen zu gewinnen. Die Experimente basieren auf diskreten Wahlentscheidungen von Befragten zwischen (hypothetischen) Alternativen. Auf Grundlage dieser Wahlentscheidungen werden die Wahlwahrscheinlichkeiten analysiert. Diese Studien können für die Berücksichtigung der Konsumentenpräferenzen bei der Bewertung von Gesundheitszuständen (health valuation), der Evaluation von Versorgungsprogrammen (healthcare evaluation) oder der Bewertung von Gesundheitstechnologien (health technology assessment) eingesetzt werden. Ein Vorteil dieser Methode ist die Fundierung in der mikroökonomischen Nachfragetheorie, wobei die Präferenzen in Form von Teilnutzenwerten für spezifische Eigenschaften oder Eigenschaftsausprägungen analysiert werden können. Die erklärende Variable resultiert aus den Entscheidungen der Studienteilnehmer zwischen Alternativen in den Wahlszenarien, wobei die unabhängigen Variablen durch die Eigenschaftsausprägungen der jeweiligen Alternativen bestimmt werden. Die Berechnung der Teilnutzenwerte kann mittels der Maximum-Likelihood-Methode erfolgen. Je nach zugrunde liegender Verteilungsfunktion können unterschiedliche statistische Schätzmethoden, wie z. B. Probit-, Logit-, Mixed-Logit- oder Latent-Class-Modelle, angewendet werden. Der Fokus dieses Beitrags liegt auf der Diskussion der Anwendungspotenziale, der zugrunde liegenden theoretischen Konzepte und der Studiendurchführung. Die Ausführungen sollen als Einführung in die Thematik verstanden werden und weniger als methodische Diskussion neuester Erkenntnisse und Verfahren.

Abstract

Discrete-choice experiments are increasingly used for preference measurement in healthcare. The aim of this choice modeling is the analysis of latent preference structures, in order to gain information on the design, assessment and forecast of demand and acceptance of healthcare products or services. The experiments are based on discrete choices of respondents between (hypothetical) alternatives. Based on these choices, the choice probabilities are analyzed. These studies can be used for the consideration of consumer preferences in the valuation of health states (health valuation), the evaluation of care programs (healthcare evaluation), or health technology assessment. An advantage of this method is it’s foundation in microeconomic demand theory, where preferences can be analyzed in the form of part-worths for specific properties or property characteristics. The explanatory variable is the result of the participant’s choices between alternative scenarios, whereby the independent variables are determined by the attribute characteristics of the alternatives in the question. The part-worth utilities can be calculated by means of the maximum likelihood method. Depending on the underlying distribution function different statistical estimation methods, such as probit, logit, mixed logit or latent class models are used. The focus of this paper is the discussion of the potential applications, the underlying theoretical concepts and the study conduct. The statements are to be understood rather as an introduction to the topic than as methodical discussion of the latest findings and techniques.

 
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