Hungarians Choose Private Healthcare for Distance and Cost, Landmark Survey Finds

Hungary’s healthcare system has long operated on two parallel tracks: a tax-funded public sector that is free at the point of use but chronically underfunded, and a rapidly expanding private sector that patients pay for out of pocket. A new study published in Discover Social Science and Health offers one of the most detailed portraits yet of how Hungarian adults actually weigh their options when they step into the private market. Using a discrete choice experiment (DCE) on a quota-representative sample of 1,014 adults, researchers from the University of Debrecen found that patients approach private healthcare with striking pragmatism. The most powerful driver of their choices is not prestige, brand recognition or even the identity of the treating physician—it is how far they would have to travel, followed closely by what the visit will cost them.

The study, led by Balázs Kertesz of the Doctoral School of Business and Management at the University of Debrecen, together with Klára Bíró of the Institute of Health Economics and Management and Péter Balogh of the Institute of Methodology and Business Digitalization, was designed to fill a stubborn evidence gap. Hungary’s public system has faced well-documented underfunding, leading to long waiting lists and constrained access to specialists. Those frictions have become the engine of private-sector growth, as households increasingly pay directly for consultations, diagnostics and elective procedures. Yet until now, policymakers have had little rigorous information about which attributes of private services actually matter to the general adult population, rather than to existing private clinic customers. Understanding those preferences matters for anyone planning service networks, setting prices, or designing policies aimed at narrowing regional inequalities in access.

Methodologically, the researchers deployed a two-stage approach that is considered state of the art in stated-preference research. Before constructing the main choice experiment, they conducted a best-worst scaling (BWS) exercise to identify which candidate attributes of private healthcare were most relevant to respondents. BWS asks participants to repeatedly identify the best and worst options in small sets of attributes, producing a ranking of relative importance that is less vulnerable to the scale distortions of simple rating scales. From this preparatory work, five attributes survived into the final experimental design: the cost of the service, the distance to the provider, the availability of appointments, the reputation of the provider, and the type of clinic or provider.

The main survey then confronted each of the 1,014 respondents with a series of realistic decision scenarios. In each of eight choice situations, participants saw three hypothetical private healthcare offers described by varying combinations of the five attributes, alongside a fourth option: to decline all of them and remain in public healthcare. This opt-out alternative is methodologically crucial. Because Hungarian adults can always default to the public system, a well-designed experiment must allow them to express that preference rather than forcing them to choose among private options they might reject in real life. Including a no-choice option anchors the experiment in the genuine decision architecture of Hungary’s dual system and prevents the overstatement of demand that plagues forced-choice designs.

The statistical engine behind the analysis was a conditional logit (CL) model, the workhorse specification for discrete choice data. Conditional logit assumes that the utility an individual derives from a given healthcare option is a linear function of its attributes plus a random error term, and that the probability of choosing any one option is proportional to its estimated utility relative to the full choice set. From the estimated coefficients, the team could compute both the relative importance of each attribute and—critically for health economics—willingness-to-pay (WTP) figures. WTP calculations translate abstract utility weights into monetary terms: they answer the question of how much more a patient would be willing to pay for, say, a provider located half as far away, or an appointment available a week sooner.

The results are unambiguous in their hierarchy. Provider distance emerged as the single most important attribute, accounting for 40.01% of the explained preference structure. Cost followed at 32.31%, and appointment availability took third place at 19.13%. Together, these three practical attributes dominated roughly nine-tenths of the preference weight in the model. Institutional reputation and provider type—the attributes often emphasized in private clinics’ own marketing, from glossy branding to physician celebrity—were far less influential. In other words, Hungarian patients are not primarily buying prestige when they enter the private market; they are buying proximity, affordability and speed. The willingness-to-pay estimates reinforce this picture, quantifying exactly how much shorter travel times and faster appointments are worth relative to each other and to price.

These findings carry a counterintuitive edge that helps explain the trajectory of Hungary’s private healthcare market. Many observers might assume that private care functions as a status good, with patients choosing flagship downtown clinics and renowned specialists. The data suggest something more mundane and, arguably, more consequential: demand behaves like a market for convenience. A private clinic that opens closer to where people live or work, prices its services within reach of median households, and offers appointments without long delays will capture preference share even if its reputation is unremarkable. Conversely, a prestigious institution located far from patients, or charging fees well beyond their comfort zone, leaves much of the market on the table—or sends it back to the public system entirely, where the no-choice option remains a real and frequently exercised alternative.

For policymakers, the study’s implications extend beyond marketing strategy into questions of equity and system design. Distance as the dominant attribute is a red flag for regional inequality: patients in smaller towns and rural areas face systematically longer travel to private providers, meaning the convenience premium of private care is distributed unevenly across the country. If accessibility, rather than quality perception, is what patients weigh most heavily, then the geography of private investment decisions will shape health access patterns for years to come. The findings can inform service-planning discussions about where new capacity should be located, how pricing structures affect uptake among lower-income groups, and how the public system’s waiting times—the very frictions that push patients private—might be reduced to rebalance the two sectors. The authors frame their results as input for exactly these policy conversations on access, affordability and regional disparities in Hungary’s mixed public-private healthcare system.

The research also exemplifies a broader methodological trend in health services research: the pairing of best-worst scaling with discrete choice experiments to build more realistic, behaviorally grounded preference models. By using BWS to prune the attribute set before the DCE, the researchers reduced cognitive burden on respondents and improved the interpretability of the final estimates. The inclusion of the public-care opt-out, the quota-representative sampling frame, and the translation of utilities into willingness-to-pay values together produce evidence that speaks directly to both economics and policy. The study received ethical approval from the Research Ethics Committee of the Faculty of Economics at the University of Debrecen and was conducted under the ethical principles of the Declaration of Helsinki, with all participants providing informed consent. Open access funding was provided by the University of Debrecen, and the authors thank Dr. Péter Czine for verifying the analytical methods. As Hungary’s private healthcare sector continues to expand against the backdrop of public-sector strain, this experiment provides a rare quantitative answer to a deceptively simple question: what makes a Hungarian adult choose to pay for care? The answer—closer, cheaper, sooner—may disappoint brand strategists, but it should energize anyone committed to making healthcare genuinely accessible.

Subject of Research: Patient preferences for private healthcare services among the Hungarian adult population, measured with a discrete choice experiment

Article Title: Understanding patient preferences for private healthcare services among the general Hungarian adult population using discrete choice experiment

Article References: Kertesz, B., Bíró, K., & Balogh, P. (2026). Understanding patient preferences for private healthcare services among the general Hungarian adult population using discrete choice experiment. Discover Social Science and Health. https://doi.org/10.1007/s44155-026-00482-8

Image Credits: AI Generated

DOI: 10.1007/s44155-026-00482-8

Keywords: discrete choice experiment, private healthcare, Hungary, patient preferences, willingness to pay, best-worst scaling, conditional logit, healthcare access, regional inequality, health policy, University of Debrecen, out-of-pocket spending