Join us on June 23 for the workshop “The Overburdened Healthcare System: How Simulation, Data Science, and AI Can Point the Way Forward”! The workshop is a pre-event of the ACM SIGSIM PADS 2026 conference and also connected to this year’s Digital Humanism Conference.

Two-tier healthcare, hospital closures, and growing budget deficits: the signals are clear — healthcare systems are under pressure, and “business as usual” is no longer an option. But what actually works? Which interventions create real, sustainable improvement rather than shifting problems from one part of the system to another? Answering these questions requires more than data. It requires understanding what the data mean, anticipating future consequences, and testing decisions before they are implemented. This workshop explores how simulation, data science, and AI can help healthcare systems move from crisis management to evidence-based, sustainable decision-making.

The first part of this event will be held in German, while the second part will be held in English.

Registration

We look forward to seeing you there, but we would kindly ask you to register for the workshop.

Program

Abstracts

Comparing the Incomparable: Multidimensional Digital Solutions for Fairer Evaluation (English)

More and more interventions, therapies, and digital solutions are competing for limited resources. At the same time, different stakeholders evaluate these measures along diverse dimensions – ranging from costs and effectiveness to broader societal impacts. Many interventions are difficult to compare, their effects are complex, and often only understandable through interdisciplinary perspectives. Against this background, the question arises: how can fair, transparent, and comparable evaluations be achieved? Following a short introduction to the WWTF-funded project HPVienna, we will discuss how digital infrastructures can make evaluation processes more efficient and transparent, how different disciplines – from genetics and social anthropology to satellite research and simulation – can collaborate, and what roles simulation and AI can play in this context.

Costs in Healthcare Systems: An Important Basis for Decision-Making or the Risk of an Economic Overfocus? / Kosten im Gesundheitssystemen: Wichtige Entscheidungsbasis oder die Gefahr einer ökonomischen Fokussierung?

Health economic evaluations are a key foundation for decisions in healthcare provision, prevention, and therapy. In Austria, a standardized and harmonized cost framework, as well as clear definitions of discounting and perspectives, is still under development. Following short keynote presentations on the international state of the art and the current situation in Austria, we will discuss the role a standardized cost basis plays in simulations, scenario analyses, and, ultimately, evidence-based decision-making — as well as the risks that arise when the focus is placed too strongly on costs.

Gesundheitsökonomische Bewertungen sind eine zentrale Grundlage für Entscheidungen in Versorgung, Prävention und Therapie. In Österreich befindet sich eine einheitliche, normierte Kostenbasis – ebenso wie klare Festlegungen zu Diskontierung und Perspektiven – noch im Aufbau. Nach kurzen Impulsvorträgen zum internationalen State of the Art und zu österreichischen Zuständen diskutieren wir, welche Rolle eine standardisierte Kostenbasis für Simulationen, Szenarienanalysen und letztendlich evidenzbasierte Entscheidungen spielt – und welche Risiken entstehen, wenn der Fokus zu stark auf Kosten gelegt wird.

Healthcare Systems Under Pressure – How Data and Simulation Can Help in Times of Limited Resources / Gesundheitssystem unter Druck - Wie Daten und Simulation bei begrenzten Ressourcen helfen können

Greater demand, fewer resources — healthcare systems are facing fundamental trade-offs amid demographic change, rising costs, and limited resources. But how do we make decisions when not everything can be achieved at the same time? Data, simulation, and AI promise to make complex interdependencies visible, support better prioritization, and enable resources to be distributed more efficiently, sustainably, and fairly. But how reliable are these models in practice? How can their results be transferred into the realities of complex healthcare systems, and what conditions are necessary for this? And ultimately, who decides what “better” actually means? In this panel, experts will discuss how models can help make decisions more transparent and evidence-based — and where their limitations lie.

Mehr Bedarf, weniger Ressourcen – das Gesundheitssystem steht im Lichte des demografischen Wandels, steigender Kosten und begrenzter Ressourcen vor grundlegenden Zielkonflikten. Doch wie treffen wir Entscheidungen, wenn nicht mehr alles gleichzeitig möglich ist? Daten, Simulation und AI versprechen, komplexe Zusammenhänge sichtbar zu machen, bessere Prioritäten zu setzen und damit auch Ressourcen effizienter, nachhaltiger und fairer verteilen zu können. Aber wie belastbar sind diese Modelle wirklich? Wie können Ergebnisse in die Praxis komplexer Versorgungssysteme übertragen werden und welche Voraussetzungen sind dafür notwendig? Und wer entscheidet letztlich, was „besser“ bedeutet? In diesem Panel diskutieren Expert:innen, wie Modelle helfen können, Entscheidungen transparenter und fundierter zu machen – und wo ihre Grenzen liegen.

Patient Participation: Simulating More Resilient and Targeted Healthcare Systems / Patientenbeteiligung: Simulation resilienter & zielgenauer Gesundheitssysteme

Which aspects of therapies and interventions are actually relevant to people? Too often, decisions and simulations fail to reflect real life because the underlying models do not adequately capture the lived realities of those affected. Decision-making frameworks — and, by extension, simulations — must therefore not only be evidence-based but also take patients’ needs and preferences into account. Underrepresented population groups are often already underrepresented in collected data, potentially further reinforcing existing inequalities. In this session, we discuss how participatory simulation can be designed, which adverse events and long-term effects should be included, and how current simulation research and AI can help systematically explore complex scenario spaces. Following a short introduction to the WWTF-funded BETTER project, we will discuss how a more comprehensive picture of the impacts of interventions can be developed.

Welche Aspekte von Therapien und Interventionen sind für Menschen tatsächlich relevant? Oft wird am Leben „vorbeientschieden“ und „vorbeisimuliert”, weil die Modelle an den Lebensrealitäten der Betroffenen vorbeigehen. Entscheidungsgrundlagen – und damit auch Simulationen – müssen daher nicht nur evidenzbasiert sein, sondern auch Bedürfnisse und Präferenzen von Patient:innen berücksichtigen. Schon in gesammelten Daten sind unterrepräsentierte Bevölkerungsgruppen unterrepräsentiert, wodurch sich Ungleichheiten möglicherweise weiter verstärken. In diesem Beitrag diskutieren wir, wie partizipative Simulation gestaltet werden kann, welche Adverse Events und Langzeiteffekte einbezogen werden sollten, und wie aktuelle Simulationsforschung sowie AI dabei helfen, komplexe Szenarienräume systematisch zu erschließen. Nach einer kurzen Vorstellung des WWTF-geförderten Projekts BETTER diskutieren wir, wie ein umfassenderes Bild der Auswirkungen von Maßnahmen entstehen kann – und wie Entscheidungsträger:innen in zukünftigen Krisen besser unterstützt werden können.

Shaping Health Futures with Simulation and AI: A Digital Humanism Perspective - From Epidemiology to Policy (English)

How do we decide what “better” means in complex health systems? Decisions increasingly rely on models, data, and simulations – yet the assumptions behind them, the uncertainties they carry, and the values they embed are often not fully visible. AI, simulation, and digital data infrastructures are not neutral: access to data, computational resources, and proprietary models is uneven, raising questions about who can participate in generating evidence and shaping decisions. As these tools become more central to policymaking, the question is no longer only what we can model, but how they shape our understanding of reality and influence collective choices. The panel brings together international experts from epidemiology, modeling, and policy to discuss how simulation can support better decision-making – from infectious disease dynamics to long-term system planning. We explore how evidence is generated, how uncertainty can be communicated, and how the impact of decisions can be made visible across different domains. Framed by the principles of Digital Humanism, the discussion also addresses limits of models, issues of access and governance, and the responsibility of using them in shaping the future of health systems.

Photographs and/or video will be taken at this event. By attending, you grant TU Wien Informatics full rights to use the material (and any reproductions or adaptations) for fundraising, publicity, or other purposes. This may include (but is not limited to) the right to use in our print and online publicity, social media, press releases, and funding applications. If you wish that no photographs explicitly depicting you are used for these purposes, please send us an informal message. — Thank you!

Curious about our other news? Subscribe to our news feed, calendar, or newsletter, or follow us on social media.