Stress-testing the resilience of the Austrian healthcare system using agent-based simulation.

Patients do not access physicians at random but rather via naturally emerging networks of patient flows between them. As mass quarantines, absences due to sickness, or other shocks thin out these networks, the system might be pushed to a tipping point where it loses its ability to deliver care. Here, we propose a data-driven framework to quantify regional resilience to such shocks via an agent-based model. For each region and medical specialty we construct patient-sharing networks and stress-test these by removing physicians. This allows us to measure regional resilience indicators describing how many physicians can be removed before patients will not be treated anymore. Our model could therefore enable health authorities to rapidly identify bottlenecks in access to care. Here, we show that regions and medical specialties differ substantially in their resilience and that these systemic differences can be related to indicators for individual physicians by quantifying their risk and benefit to the system.

The pulmonary nodule: clinical and radiological characteristics affecting a diagnosis of malignancy.

The role of computed tomography (CT) in the diagnosis of the solitary pulmonary nodule (SPN) is constantly expanding. CT helps to detect a growing number of increasingly small lesions, but, as with chest radiography, the primary goal in the evaluation of small pulmonary nodules is to exclude malignancy. Despite the availability of numerous, variously invasive, diagnostic tests, diagnostic accuracy tends to decline as the size of the nodule decreases. The role of the radiologist is therefore to help the clinician determine the most appropriate management strategy by using all available modalities [CT, magnetic resonance (MR) imaging, positron emission tomography (PET)] and evaluating the patient's clinical history and the imaging features leading to a diagnosis of benignity or malignancy. Imaging features include nodule size, margins, calcifications and fatty component, internal features (cavitations, pseudocavitations, air bronchogram, halo sign), as well as advanced techniques for characterisation (growth rate, contrast enhancement) and management (computer-aided diagnosis, Bayesian analysis, neural networks). The aim of this paper is to summarise the approach to pulmonary nodules from the point of view of the radiologist, oncologist and thoracic surgeon.