A stress test for the (Austrian) healthcare system


A retirement wave, mass quarantine, or lack of interest to work in the countryside: There are numerous reasons why a more-than-average number of medical practices could be closing at the same time. The system usually can compensate for some of these shortfalls. But there is a point where the situation can become critical. Until recently, it was not possible to accurately predict where that point is.

A research team of (mainly) CSH scientists proposes a method to identify (tipping) points at which an adequate medical treatment of the population can no longer be guaranteed: the first stress test for a healthcare system.

In their newest publication in Nature Communications, the scientists use data from Austria to show how many resident physicians and medical specialists can drop out before patients don’t find a new doctor within a reasonable distance. Yet, the authors emphasize that their method can be used in any country that has the relevant data available.

Schematic overview scaled 1


For their simulations, the scientists had access to anonymized patient data from 2018. They combined them with publicly available data on the office hours of doctors.

“Our data show that patients do not choose physicians at random but rather via naturally emerging networks,” explains Michaela Kaleta, who was a researcher at CSH until June.

For example, if a gynecologist goes on vacation, her patients usually will go to a particular other doctor as a substitute, and vice versa. If the same gynecologist retires, her patients are very likely to switch permanently to that colleague.

“We see that such patient-doctor-networks and patient flows are surprisingly constant, especially in rural areas,” says former CSH scientist Jana Lasser, now at Graz University of Technology; Jana has been involved in this work since her time at CSH and shares the first authorship on this paper with Michaela.

The researchers now feed the real-world networks into a computer model and “shock” the system by removing physicians – just like in a disease wave, for instance. “We can take one network node, i.e., doctor avatar, out of the system at a time and observe where the patients are moving on to within the network – and at what point a sufficient healthcare can no longer be provided,” says Jana.


The scientists found that the resilience of local health care depends on more than just the number of physicians in that region, known as “physician density.”

“Take ophthalmology in Styria and Vorarlberg as an example,” explains Jana. “According to our dataset from 2018, both Austrian provinces had about the same number of contracted eye doctors per person, in other words, about the same physician density. However, we see that a shock in Vorarlberg can be four times larger than in Styria before patients don’t find proper eye treatment anymore.” According to this model, in Styria 7% of eye doctors can be removed before healthcare becomes critical, compared to 28% in Vorarlberg.

“Our stress test shows very precisely in which regions in Austria the healthcare system is resilient, and where health authorities would have to take urgent steps to improve the situation,” Jana points out. “The regional differences in Austria can be quite significant.”

Critical Limits EN
The numbers show what percentage of physicians from different medical fields can be removed in the nine Austrian provinces before a critical limit in public healthcare is reached.


“In many areas, such as the banking sector, stress tests have long been conducted to better prepare for crises,” emphasizes project leader Peter Klimek (CSH & MedUni Vienna). “For healthcare, a stress test has long been missing.” Yet, the pandemic has shown that medical care can quickly reach critical limits when a large number of personnel is not available at a time.

“We will have to deal with such crises in the future too,” says Peter. “That’s why all countries face the challenge of rebuilding their healthcare systems: Not only do they need to keep them affordable, but they also have to restructure them in a way that they become more resistant to shocks.”

The approach presented here is a way to reach that goal. “We strongly recommend health authorities to look at how well their networks can absorb shocks. We can only find the balance between cost efficiency and crisis resilience when we know the weaknesses and strengths of the system,” Peter concludes.


The study “Stress-testing the resilience of the Austrian healthcare system using agent-based simulation” by Michaela Kaleta, Jana Lasser, Elma Dervic, Liuhuaying Yang, Johannes Sorger, D. Ruggiero Lo Sardo, Stefan Thurner, Alexandra Kautzky-Willer, and Peter Klimek, just appeared in Nature Communications.

The data visualization is available at https://vis.csh.ac.at/care-network-resilience/

The pandemic has taught us not only to think about making healthcare more cost-effective. We also need to make it more resilient, urges a team of Hub scientists – and developed a stress test to figure out the weaknesses and strengths of healthcare systems.

Their newest study “Stress-testing the resilience of the Austrian healthcare system using agent-based simulation” has just appeared in Nature Communications.

To make their multi-dimensional dataset more accessible, our visualization experts Liuhuaying Yang and Johannes Sorger developed an impressive interactive visualization.


M. Kaleta, J. Lasser, E. Dervic, L. Yang, J. Sorger, D.R. Lo Sardo, S. Thurner, A. Kautzky-Willer, P. Klimek
Nature Communications

Explore the resilience of the Austrian healthcare system using agent based simulation

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