Preferences of Hungarian consumers for quality, access and price attributes of health care services — result of a discrete choice experiment

In 2010, a household survey was carried out in Hungary among 1037 respondents to study consumer preferences and willingness to pay for health care services. In this paper, we use the data from the discrete choice experiments included in the survey, to elicit the preferences of health care consumers about the choice of health care providers. Regression analysis is used to estimate the effect of the improvement of service attributes (quality, access, and price) on patients’ choice, as well as the differences among the socio-demographic groups. We also estimate the marginal willingness to pay for the improvement in attribute levels by calculating marginal rates of substitution. The results show that respondents from a village or the capital, with low education and bad health status are more driven by the changes in the price attribute when choosing between health care providers. Respondents value the good skills and reputation of the physician and the attitude of the personnel most, followed by modern equipment and maintenance of the office/hospital. Access attributes (travelling and waiting time) are less important. The method of discrete choice experiment is useful to reveal patients’ preferences, and might support the development of an evidence-based and sustainable health policy on patient payments.

Trading between perceived risks and benefits related to biosimilar biological treatment in Crohn’s disease; discrete choice experiment among gastroenterologists

Objective: The objective of the study is to explore preferences of gastroenterologists for biosimilar drugs in Crohn’s Disease and reveal trade-offs between the perceived risks and benefits related to biosimilar drugs. Method: Discrete choice experiment was carried out involving 51 Hungarian gastroenterologists in May, 2014. The following attributes were used to describe hypothetical choice sets: 1) type of the treatment (biosimilar/originator) 2) severity of disease 3) availability of continuous medicine supply 4) frequency of the efficacy check-ups. Multinomial logit model was used to differentiate between three attitude types: 1) always opting for the originator 2) willing to consider biosimilar for biological-naïve patients only 3) willing to consider biosimilar treatment for both types of patients. Conditional logit model was used to estimate the probabilities of choosing a given profile. Results: Men, senior consultants, working in IBD center and treating more patients are more likely to willing to consider biosimilar for biological-naïve patients only. Treatment type (originator/biosimilar) was the most important determinant of choice for patients already treated with biologicals, and the availability of continuous medicine supply in the case biological-naïve patients. The probabilities of choosing the biosimilar with all the benefits offered over the originator under current reimbursement conditions are 89% vs 11% for new patients, and 44% vs 56% for patients already treated with biological. Conclusions: Gastroenterologists were willing to trade between perceived risks and benefits of biosimilars. The continuous medical supply would be one of the major benefits of biosimilars. However, benefits offered in the scenarios do not compensate for the change from the originator to the biosimilar treatment of patients already treated with biologicals.

A diszkrét kiválasztási modell becslése Cox-regresszióval (Parameter estimation for multinomial discrete choice model using Cox-regression)

Considering the so-called "multinomial discrete choice" model the focus of this paper is on the estimation problem of the parameters. Especially, the basic question arises how to carry out the point and interval estimation of the parameters when the model is mixed i.e. includes both individual and choice-specific explanatory variables while a standard MDC computer program is not available for use. The basic idea behind the solution is the use of the Cox-proportional hazards method of survival analysis which is available in any standard statistical package and provided a data structure satisfying certain special requirements it yields the MDC solutions desired. The paper describes the features of the data set to be analysed.