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Patients do not access physicians at random but rather via naturally emergingnetworks of patient flows between them. As retirements, mass quarantines andabsence due to sickness during pandemics, or other shocks thin out thesenetworks, the system might be pushed closer to a tipping point where it losesits ability to deliver care to the population. Here we propose a data-drivenframework to quantify the regional resilience to such shocks of primary andsecondary care in Austria via an agent-based model. For each region and medicalspecialty we construct detailed patient-sharing networks from administrativedata and stress-test these networks by removing increasing numbers ofphysicians from the system. This allows us to measure regional resilienceindicators describing how many physicians can be removed from a certain areabefore individual patients won't be treated anymore. We find that such tippingpoints do indeed exist and that regions and medical specialties differsubstantially in their resilience. These systemic differences can be related toindicators for individual physicians by quantifying how much their hypotheticalremoval would stress the system (risk score) or how much of the stress from theremoval of other physicians they would be able to absorb (benefit score). Ourstress-testing framework could enable health authorities to rapidly identifybottlenecks in access to care as well as to inspect these naturally emergingphysician networks and how potential absences would impact them.

Stress-testing the Resilience of the Austrian Healthcare System Using Agent-Based Simulation