EURO 2024 Copenhagen
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432. Comparison of HB Shrinkable Estimators and DCE Simulators for Demand for Care

Invited abstract in session WC-47: MCDA in medicine, stream Multiple Criteria Decision Analysis.

Wednesday, 12:30-14:00
Room: 50 (building: 324)

Authors (first author is the speaker)

1. Christine C Huttin
Business and Economics of healthcare, Univ Aix Marseille and Endepusresearch, Inc

Abstract

OBJECTIVES: this communication aims to discuss how and in which context a random price generator for health care markets can be useful in comparison with other approaches for economic modeling and pricing of medical products and services
METHODS: a comparison of the different approaches used will be discussed with their statistical limitations: nested logit models, cumulative logit models, latent model of choices , shrinkable estimators with Hierarchical Bayesian approach, combination of robust pricing optimization with multinomial logit choice models, and choice models with random price generators and current model application of the BLP model on NGS sequencing.
RESULTS: random generators proved to be useful but do not fit any kind of structural conditions to adjust supply and demand of health re markets in more or less regulated health and economic systems. an approach by sets of alternatives and choice models allow to adjust for heterogeneity of demand but lack of price data in some markets make it useful to rely on shrinkable estimators with HB approaches. In duopoly cases, the use of BLP is currently tested and may help for investigation of antitrust policies.
CONCLUSIONS: the complexity of health care markets lead to consider various combinations of models and even participatory modeling to reach growing consensus with various layers of decision makers both on the payer side and the economic actors switching to data driven models for both drug and vaccines.

Keywords

Status: accepted

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