Download PDF
Gesundheitsökonomie & Qualitätsmanagement 2017; 22(03): 135-143
DOI: 10.1055/s-0042-117959
Originalarbeit
© Georg Thieme Verlag KG Stuttgart · New York

Attribute Non-Attendance in Discrete-Choice-Experimenten

Implikationen für Studien im Gesundheitswesen
Laura Bölter
,
Andrew Sadler
,
Axel C. Mühlbacher
Further Information

Publication History

Publication Date:
08 November 2016 (online)

Also available at
    Permissions and Reprints

Zusammenfassung

Ziel/Hintergrund Bei der Präferenzmessung mit Discrete-Choice-Experimenten (DCE) wird implizit angenommen, dass die Befragten alle gegebenen Informationen bei der Entscheidungsfindung berücksichtigen. Studien zeigten jedoch, dass in komplexen Befragungssituationen Verarbeitungsstrategien wie Attribute Non-Attendance (ANA) genutzt werden, um Wahlentscheidungen zu vereinfachen. Dies führt zu unvollständigen Trade-offs. Ziel der Studie war es, die Bedeutung von ANA in Präferenzmessmethoden, speziell DCEs, zu untersuchen und ANA-Strategien zu identifizieren.

Methodik Ausmaß und Folgen von ANA-Strategien in DCEs wurden aus der Literatur zusammengetragen. Der Schwerpunkt lag auf der Identifikation von ANA mit qualitativen und quantitativen Methoden, den Arten von ANA-Strategien, der Berücksichtigung von ANA bei der Auswertung und der Prävention von ANA in DCE-Studien.

Ergebnisse Durch die Berücksichtigung von ANA in der Ergebnisanalyse kann eine Verbesserung der Gütekriterien des statistischen Analysemodells erreicht werden. Den stärksten Einfluss hatte ANA auf die Berechnung der Zahlungsbereitschaft (WTP). In Studien wurden hohe Anteile von Befragten identifiziert, die das Kostenattribut ignorierten.

Fazit Die Nichtberücksichtigung von Verarbeitungsstrategien in DCEs kann zu verzerrten Ergebnissen und falschen gesundheitspolitischen Entscheidungen führen. Besondere Berücksichtigung von ANA in der Analyse erscheint dann erforderlich, wenn die WTP ermittelt werden soll.

Abstract

Aim/Background In Discrete Choice Experiments (DCE) it is implicitly assumed that respondents consider all given information to make their choices. However, studies have shown that in complex situations people often use attribute processing strategies such as attribute non-attendance (ANA) in order to simplify choice decisions. This leads to incomplete trade-offs. The aim of the study was to investigate the significance of ANA in preference measurement methods, especially DCEs, and identify ANA strategies.

Methods This paper investigates the impact of ANA on DCE studies. Focus was on identification of ANA with qualitative and quantitative methods used in the literature, identification of different types of ANA-strategies, consideration of ANA in the analysis and prevention of ANA in DCEs.

Results Accounting for ANA in analysis improved the fit criteria of a model. ANA had the most influential effect on the estimation of willingness to pay (WTP). Studies found a greater share of respondents who ignored the cost attribute.

Conclusion Not accounting for ANA in DCEs might lead to biased results and, in consequence, to false health policy decisions. Accounting for ANA is highly recommended when estimation of WTP is the main focus of a study.

Schlüsselwörter

Discrete-Choice-Experiment (DCE) - Attribute Non-Attendance (ANA) - Patientenpräferenzen - Präferenzmessung - Zahlungsbereitschaft

Key words

Discrete Choice Experiment (DCE) - Attribute Non-Attendance (ANA) - patient preferences - preference measurement - willingness to pay (WTP)
 

  • Literatur

  • 1 Organisation for Economic Co-operation and Development (OECD). OECD Gesundheitsdaten 2014: Deutschland im Vergleich. Im Internet: 2014 http://www.oecd.org/els/health-systems/Briefing-Note-DEUTSCHLAND-2014-in-German.pdf (Zugriff: 25.01.2016)
    PubMedGoogle Scholar
  • 2 Organisation for Economic Co-operation and Development (OECD). Value for Money in Health Spending. Paris: OECD Publishing; 2010
    Google Scholar
  • 3 Gerard K. Ryan M. Amaya-Amaya M. Introduction – Benefit Valuation in health economics. In: Ryan M. Gerard K. Amaya-Amaya M. Hrsg. Using Discrete Choice Experiments to Value Health and Health Care. Dordrecht: Springer Verlag; 2008: 1-10
    Google Scholar
  • 4 Mühlbacher AC. Bethge S. Tockhorn A. Präferenzmessung im Gesundheitswesen: Grundlagen von Discrete-Choice-Experimenten. Gesundheitsökonomie & Qualitätsmanagement 2013; 18: 159-172
    Article in Thieme ConnectPubMedGoogle Scholar
  • 5 Mühlbacher AC. Bethge S. Potenziale der Präferenzmessung. Gesellschaftspolitische Kommentare 2013; 7: 1-5
    PubMedGoogle Scholar
  • 6 Mühlbacher AC. Juhnke C. Patienten- und Bürgerpartizipation in der Entscheidungsfindung im Gesundheitswesen insbesondere bei der Bewertung von Arzneimitteln. Zeitschrift für Evidenz, Fortbildung und Qualität im Gesundheitswesen 2016; 110: 36-44
    PubMedGoogle Scholar
  • 7 Mühlbacher AC. Juhnke C. Beyer AR. Patient-Focused Benefit-Risk Analysis to Inform Regulatory Decisions: The European Union Perspective. Value in Health 2016; 6: 734-740
    PubMedGoogle Scholar
  • 8 Ho MP. Gonzalez JM. Lerner HP. et al. Incorporating patient-preference evidence into regulatory decision making. Surgical endoscopy 2015; 29: 2984-2993
    CrossrefPubMedGoogle Scholar
  • 9 Hauber AB. Gonzalez JM. Groothuis-Oudshoorn CG. et al. Statistical Methods for the Analysis of Discrete Choice Experiments: A Report of the ISPOR Conjoint Analysis Good Research Practices Task Force. Value Health 2016; 19: 300-315
    CrossrefPubMedGoogle Scholar
  • 10 Clark MD. Determann D. Petrou S. et al. Discrete Choice Experiments in Health Economics: A Review of the Literature. PharmacoEconomics 2014; 32: 883-902
    CrossrefPubMedGoogle Scholar
  • 11 Lancaster KJ. A New Approach to Consumer Theory. The Journal of Political Economy 1966; 74: 132-157
    CrossrefPubMedGoogle Scholar
  • 12 McFadden D. Conditional logit analysis of qualitative choice behavior. In: Zarembka P. Hrsg. Frontiers in Econometrics. New York: Academic Press; 1974: 105-142
    Google Scholar
  • 13 Iles RA. Rose JM. Stated Choice design comparison in a developing country: recall and attribute nonattendance. Health economics review 2014; 4: 25
    CrossrefPubMedGoogle Scholar
  • 14 Lagarde M. Investigating attribute non-attendance and its consequences in choice experiments with latent class models. Health economics 2013; 22: 554-567
    CrossrefPubMedGoogle Scholar
  • 15 Kessels R. Jones B. Goos P. Bayesian optimal designs for discrete choice experiments with partial profiles. Journal of Choice Modelling 2011; 4: 52-74
    CrossrefPubMedGoogle Scholar
  • 16 Campbell D. Lorimer VS. Aravena C. et al. Attribute processing in environmental choice analysis: implications for willingness to pay. Edinburgh: Agricultural Economics Society Annual Conference; 2010
    PubMedGoogle Scholar
  • 17 Scarpa R. Gilbride TJ. Campbell D. et al. Modelling attribute non-attendance in choice experiments for rural landscape valuation. European Review of Agricultural Economics 2009; 36: 151-174
    CrossrefPubMedGoogle Scholar
  • 18 Alemu MH. Mørkbak MR. Olsen SB. et al. Attending to the Reasons for Attribute Non-attendance in Choice Experiments. Environmental and Resource Economics 2012; 54: 333-359
    PubMedGoogle Scholar
  • 19 Hole AR. Attribute non-attendance in patients’ choice of general practitioner appointment. Oulton Hall, Leeds: Second international choice modelling conference; 2011
    PubMedGoogle Scholar
  • 20 Carlsson F. Kataria M. Lampi E. Dealing with Ignored Attributs in Choice Experiments on Valuation of Sweden’s Environmental Quality Objectives. Environmental and Resource Economics 2010; 47: 65-89
    CrossrefPubMedGoogle Scholar
  • 21 Hole AR. Kolstad JR. Gyrd-Hansen D. Inferred vs. Stated attribute non-attendance in choice experiments: A study of doctors’ prescription behaviour. Journal of Economic Behavior & Organization 2013; 96: 21-31
    CrossrefPubMedGoogle Scholar
  • 22 Campbell D. Lorimer VS. Accommodating attribute processing strategies in stated choice analysis: do respondents do what they say they do?. Amsterdam: European Association of Environmental and Resource Economists Annual Conference; 2009
    PubMedGoogle Scholar
  • 23 Erdem S. Campbell D. Hole AR. Accounting for Attribute-Level Non-Attendance in a Health Choice Experiment: Does it Matter?. Health economics 2015; 24: 773-789
    CrossrefPubMedGoogle Scholar
  • 24 Hole AR. A discrete choice model with endogenous attribute attendance. Economics Letters 2011; 110: 203-205
    CrossrefPubMedGoogle Scholar
  • 25 DeShazo JR. Fermo G. Implications of Rationally-Adaptive Pre-choice Behavior for the Design and Estimation of Choice Models. Working paper; Los Angeles: School of Public Policy and Social Research; University of California; 2004
    PubMedGoogle Scholar
  • 26 Hess S. Hensher DA. Making use of respondent reported processing information to understand attribute importance: a latent variable scaling approach. Transportation 2013; 40: 397-412
    CrossrefPubMedGoogle Scholar
  • 27 Hess S. Hensher DA. Using conditioning on observed choices to retrieve individual-specific attribute processing strategies. Transportation Research Part B 2010; 44: 781-790
    CrossrefPubMedGoogle Scholar
  • 28 Mariel P. Hoyos D. Meyerhoff J. Stated or inferred attribute non-attendance? A simulation approach. Economía Agraria y Recursos Naturales-Agricultural and Resource Economics 2013; 1: 51-67
    PubMedGoogle Scholar
  • 29 Ryan M. Watson V. Entwistle V. Rationalising the ‘irrational’: a think aloud study of discrete choice experiment responses. Health economics 2009; 18: 321-336
    CrossrefPubMedGoogle Scholar
  • 30 Weller P. Oehlmann M. Mariel P. et al. Stated and inferred attribute non-attendance in a design of designs approach. Journal of Choice Modelling 2014; 11: 43-56
    CrossrefPubMedGoogle Scholar
  • 31 Hensher DA. How do respondents process stated choice experiments? Attribute consideration under varying information load. Journal of Applied Econometrics 2006; 21: 861-878
    CrossrefPubMedGoogle Scholar
  • 32 Steiner M. Nachfrageorientierte Präferenzmessung: Bestimmung zielgruppenspezifischer Eigenschaftssets auf Basis von Kundenbedürfnissen [Dissertation]. Deutscher Universitäts-Verlag – GWV Fachverlage GmbH, Wiesbaden: Universität Jena; 2007
    Google Scholar
  • 33 Reed Johnson F. Lancsar E. Marshall D. et al. Constructing experimental designs for discrete-choice experiments: report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force. Value Health 2013; 16: 3-13
    CrossrefPubMedGoogle Scholar
  • 34 Crabbe M. Vandebroek M. Using appropriate prior information to eliminate choice sets with a dominant alternative from D-efficient designs. Journal of Choice Modelling 2012; 5: 22-45
    CrossrefPubMedGoogle Scholar
  • 35 Auspurg K. Liebe U. Choice-Experimente und die Messung von Handlungsentscheidungen in der Soziologie. KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie 2011; 63: 301-314
    CrossrefPubMedGoogle Scholar
  • 36 Louviere JJ. Hensher DA. Swait JD. Stated Choice Methods – Analysis and Applications. Virtual Publishing: Cambridge University Press; 2003
    Google Scholar
  • 37 Telser H. Zweifel P. Validity of discrete-choice experiments evidence for health risk reduction. Applied Economics 2007; 39: 69-78
    CrossrefPubMedGoogle Scholar