2015
DOI: 10.1007/s10198-015-0721-x
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Comparative analysis of decision maker preferences for equity/efficiency attributes in reimbursement decisions in three European countries

Abstract: 2 AbstractBackground: In addition to cost-effectiveness, national guidelines often include other factors in reimbursement decisions. However, weights attached to these are rarely quantified, thus decisions may strongly depend on decision-maker preferences.Objective: To explore the preferences of policymakers and healthcare professionals involved in the decision-making process for different efficiency and equity attributes of interventions and analyse crosscountry differences.Method: Discrete choice experiments… Show more

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Cited by 14 publications
(13 citation statements)
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“…The preference for severity of disease aligns with the findings of similar studies conducted in Norway, Israel, Austria and Hungary, Brazil and Uganda (10,26,27). A review of popular preferences also listed the severity of illness as a criterion for health resource allocation (28).…”
Section: Discussionsupporting
confidence: 70%
“…The preference for severity of disease aligns with the findings of similar studies conducted in Norway, Israel, Austria and Hungary, Brazil and Uganda (10,26,27). A review of popular preferences also listed the severity of illness as a criterion for health resource allocation (28).…”
Section: Discussionsupporting
confidence: 70%
“…Discrete choice methods have proved in recent empirical research (e.g. Baji, García-Goñi, Gulácsi, Mentzakis, E., & Paolucci, F., 2016;Mirelman et al, 2012) to be very useful in eliciting population's preferences (Dukić, 2012). Thus, it can be argued that aligning supply (through evaluation of health-care interventions) and demand (through evaluating patients' preferences) is the key of resources allocation in publicly funded health systems (Dukić, Tomas Žiković, & Žiković, 2015).…”
Section: Focus On Efficiency Of Health Systemsmentioning
confidence: 99%
“…In that sense, effectiveness captures several of the distinct criteria that are classified here as 'clinical' . Individual health benefits strongly influence policy decisions in various countries [28]. The number of patients in 'need of treatment' adds information to the decision about the likelihood that a population will benefit from a medication or intervention [29,30].…”
Section: Effectivenessmentioning
confidence: 99%