Health preference research is undergoing structural renewal. The field is evolving in multiple directions at once: classic methods such as Time Trade-Off and Standard Gamble are increasingly complemented by modern approaches, including Discrete Choice Experiments. New protocols have been introduced to meet growing demand for internationally comparable value sets. At the same time, broader developments — including patient-centred definitions of value, consistent measurement across lifespan considerations, and expansion beyond traditional health outcomes — are reshaping how preference-based evidence is collected and used.

This workshop maps that evolving landscape, connecting recent methodological advances to four pressing challenges, including (i) scaling up valuation research to meet increasing global demand; (ii) valuing what matters to patients, particularly in the context of Value-Based Health Care; and (iii) expanding outcome spaces beyond traditional health measures toward child health, condition-specific, and broader wellbeing instruments. Across these areas, a common question is: how can research preserve the comparability that makes preference-based evidence useful for policy, while responding to legitimate demands for greater relevance and innovation?

This session explores how researchers are navigating that tension in practice. During this session several speakers, both EuroQol scientists and practioners, will provide a forward-looking exploration of health preference research, combining methodological innovation with practical and policy insights. We will highlight recent developments in valuation methods, examine the challenges of capturing preferences across different populations, and discuss how these methods inform evidence-based decision-making. Full speaker lineup coming soon!

The objective of this workshop is to illustrate how economic analysis can be (more) useful to policy development about antimicrobial resistance, and to identify priorities for research. As a global public good, the effectiveness of antimicrobial agents requires stewardship.  Both in-country and international collaboration to curb antimicrobial resistance has elements of a classic "prisoners' dilemma": descent to high-resistance is facilitated by individuals / countries because of high temptations to deviate from prudent use (i.e. for a free ride on others' prudence). Despite technological breakthroughs have increasingly produced new antimicrobials, postponing as such a return of a 'pre-antibiotic era', and despite the emergence of (inter)national cooperation schemes addressing the problem, many challenges remain in monitoring, policy development where a better understanding is needed of what works best.

The interplay of many sectors (a.o. human and animal health care, agriculture, aquaculture, the environment, finance, public-private partnerships) complicates analysing trends and reforms that do or do not contribute to better stewardship, i.e. to better governance of antimicrobial effectiveness as a global public good. In the EU/EEA alone, it is estimated that antimicrobial resistance is currently responsible for more than 35,000 deaths yearly, and that it costs billions of Euros for national healthcare systems and is considered one of the main European and Global health security threats. It is the leading cause of death around the world, with the highest burdens in low-resource settings.

The session will provide an update on recent initiatives that have established research priorities at global, OECD and European levels, aiming to delineate evidence-based interventions with the greatest impact. Then participants will discuss and co-create health economics considerations and approaches to address the challenges of antimicrobial resistance. More information, including full speaker lineup, coming soon!

Choice modelling is widely used in transport, marketing, environmental and health economics for understanding choice behaviour and forecasting demand for products and services. In health, choice modelling is used – among other applications – to measure patient preferences validly and reliably as well as accurately predict choice behaviour of patients. As such, it can help to tailor care to patients’ needs, and prevent (i) non-adherence to treatments (ii) waste in healthcare, (iii) poor policy decisions, (iv) trial-and-error policy implementations, and (v) supply and demand imbalance.

In this half-day workshop ‘Choice Modelling in Health’, participants will familiarize themselves with the practical steps for conducting a stated preference study (including a Discrete Choice Experiment) and modelling choice data. The theoretical underpinnings will be presented in an interactive environment.

Participants will be introduced to the R programming language and Apollo, commonly used for estimating choice models in academia and industry. During this workshop, which is at a beginner’s level, participants will learn the step-by-step modelling process for estimating the most commonly applied choice models in health: the Multinomial Logit (MNL), the Latent Class (LC) and Mixed Logit (MXL) models; familiarize themselves with preference heterogeneity, model output and model comparison; conduct post-estimation procedures to transform model outcomes to useful insights that suit the needs of stakeholders in health (e.g. Marginal Rates of Substitution (including Willingness-to-Pay or Maximum Acceptable Risk), relative attribute importance, choice probabilities, and market shares).

This workshop reviews recent developments in the measurement of health (care) inequality, the elicitation of aversion to it and applications to distributionally sensitive evaluation of cost effectiveness and population health. Measurement covers computation, normative foundations and limitations of rank-dependent measures of health inequality. Extensions to account for measurement properties of health and alternative attitudes to inequality are explained. Health (care) inequality is distinguished from health (care) inequity, and approaches to measuring the latter outlined. Aversion to health inequality is relevant to policy design and evaluation. Evidence on it is accumulating rapidly.

The workshop introduces a budget-set experiment that elicits this inequality aversion and is applicable online with representative samples. Evidence obtained on aversion to health inequality, unidimensionally and in relation to non-health characteristics, is reviewed. Derivation of health equity weights is explained and their application in evaluation demonstrated. Workshop participants can do an experiment online in advance and will see the distribution of elicited health inequality aversion. Evaluations of health care interventions and population health are mostly based on averages. And yet, health inequality reduction is an objective of most health systems and public health agencies. This objective is not incorporated into standard cost-effectiveness analysis (CEA) and population health monitoring. Developments of distributionally sensitive CEA and population health measurement are beginning to change this.

The workshop focuses on a dominance-based approach to both extensions. This uses higher order stochastic dominance to robustly rank health distributions, with normative foundation in general ethical principles. The workshop will be organized in three sessions covering health inequality measurement, elicitation of health inequality aversion distributional CEA and population health applications of the evaluation of health distributions.

This workshop will be organised by the iHEA Specialist Interest Group (SIG) on the Economics Of Digital Health Technology. This SIG aims to bring together health economists and experts from other disciplines and stakeholders such as behavioural economics, cognitive sciences and social sciences. We aim to apply economic theory and advance the field of health economic research by enriching our understanding and generating evidence of DHTs to progress towards more equitable health and social care. More information coming soon!

This course aims to provide participants with an overview of behavioral experiments in health economics and thereby to convey a solid understanding of the state-of-the-art experimental methodology as well as practical insights to conduct own experiments. Topics covered, among others, are experiments on provider behavior, incentives, and elicitation preferences in health.

The course will present different types of experiments (lab, online, field) and give examples of their use to address health-economics issues complementing theory and empirical work. The intended learning objective is that by the end of the course, participants will know how to apply experimental methods in their own research.

This workshop will provide a unique opportunity to share scientific insights and practical experiences in the field of risk adjustment. The primary objective of this workshop is to equip participants with a practical toolkit for the design and evaluation of risk adjustment models, while drawing lessons from European experiences. The workshop is intended for academic researchers, consultants, policymakers, health insurers, healthcare providers, and other stakeholders who work with – or are interested in – the design and evaluation of risk adjustment models. It will address different applications of risk adjustment, including insurer payment, provider payment, and geographic allocation.

Background, objective, target audience, format and learning goals:

Do you work with risk adjustment models for insurer payment, provider payment or geographic allocation? If so, you are likely aware that designing and evaluating these models involves many methodological choices and complex trade-offs. Key questions include:

• What is the goal of risk adjustment?
• Which factors should be included in a risk adjustment model, and which should not?
• What information should be used to identify these factors?
• How should this information be translated into risk adjuster variables?
• How should the coefficients (payment weights) for these variables be estimated?
• What data should be used to estimate the payment weights?
• What data adjustments are needed to align the data with the policy setting of interest?
• How should model predictions be translated into actual payments?
• How should a risk adjustment model be aligned with other payment system features?

The goal of this workshop is to equip participants with a practical toolkit for the design and evaluation of risk adjustment models, while drawing lessons from European experiences.

The workshop is intended for academic researchers, consultants, policymakers, health insurers, healthcare providers, and other stakeholders who work with – or are interested in – the design and evaluation of risk adjustment models. It will address different applications of risk adjustment, including insurer payment, provider payment, and geographic allocation.

The workshop will be interactive and co-creative. Presentations by experts will be combined with discussions and small assignments in which participants will have the opportunity to share their knowledge and practical experience with risk adjustment. More specifically, participants will be asked about key features of the risk adjustment models they are familiar with (e.g., in terms of risk adjustor variables, data modifications and estimation methods). This way, we will be able to connect the conceptual framework with real-world risk adjustment applications. Moreover, this allows us to ‘map’ the key features of risk adjustment models in different countries and sectors.  

After this workshop, participants will be able to:

1. identify key design choices for risk adjustment (RA);
2. explain the advantages and disadvantages of different RA design options;
3. select and interpret meaningful evaluation measures for RA models;
4. summarize key features of risk adjustment models in different countries and sectors;
5. draw lessons from European experiences and apply them to their own setting.

Program:

The program consists of two parts. In the morning session, a conceptual framework will be introduced for the design and evaluation of risk adjustment (RA) models in payment systems. In the afternoon session, several speakers will present experiences with RA in their country/sector and highlight key lessons from which other countries/sectors can learn. The program will conclude with a plenary discussion – moderated by Wynand van de Ven – on the main takeaways from the workshop and the key challenges that remain for RA design in research, policy, and practice.

Organizers:

• Richard van Kleef, Erasmus School of Health Policy & Management
• Florian Buchner, Carinthia University of Applied Sciences, University of Duisburg-Essen
• Francesco Paolucci, University of Newcastle, University of Bologna

Speakers:

• Richard van Kleef, Erasmus University Rotterdam
• Florian Buchner, Carinthia University of Applied Sciences, University of Duisburg-Essen
• Francesco Paolucci, University of Newcastle, University of Bologna
• Wynand van de Ven, Erasmus University Rotterdam
• Andreea Panturu, Erasmus University Rotterdam
• Tadjo Gigengack, Erasmus University Rotterdam
• Laura Anselmi, University of Manchester