[German "Triage Act"-Regulation with fatal consequences]. / "Triagegesetz" ­ Regelung mit fatalen Folgen.

With the coming into force of § 5c of the Infection Protection Act (IfSG), the so-called Triage Act, on 14 December 2022, a protracted discussion has come to a provisional conclusion, the result of which physicians and social associations but also lawyers and ethicists are equally dissatisfied. The explicit exclusion of the discontinuation of treatment that has already begun in favor of new patients with better chances of success (so-called tertiary or ex-post triage) prevents allocation decisions with the aim of enabling as many patients as possible to beneficially participate in medical care under crisis conditions. The result of the new regulation is de facto a first come first served allocation, which is associated with the highest mortality even among individuals with limitations or disabilities and was rejected by a large margin as unfair in a population survey. Mandating allocation decisions based on the likelihood of success but which are not permitted to be consistently implemented and prohibiting, for example the use of age and frailty as prioritization criteria, although both factors most strongly determine the short-term probability of survival according to evident data, shows the contradictory and dogmatic nature of the regulation. The only remaining possibility is the consistent termination of treatment that is no longer indicated or desired by the patient, regardless of the current resource situation; however, if a different decision is made in a crisis situation than in a situation without a lack of resources, this practice would not be justified and would be punishable. Accordingly, the highest efforts must be set on legally compliant documentation, especially in the stage of decompensated crisis care in a region. The goal of enabling as many patients as possible to beneficially participate in medical care under crisis conditions is in any case thwarted by the new German Triage Act.

[Bed capacity management in times of the COVID-19 pandemic : A simulation-based prognosis of normal and intensive care beds using the descriptive data of the University Hospital Augsburg]. / Bettenkapazitätssteuerung in Zeiten der COVID-19-Pandemie : Eine simulationsbasierte Prognose der Normal- und Intensivstationsbetten anhand der deskriptiven Daten des Universitätsklinikums Augsburg.

BACKGROUND: Following the regional outbreak in China, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread all over the world, presenting the healthcare systems with huge challenges worldwide. In Germany the coronavirus diseases 2019 (COVID-19) pandemic has resulted in a slowly growing demand for health care with a sudden occurrence of regional hotspots. This leads to an unpredictable situation for many hospitals, leaving the question of how many bed resources are needed to cope with the surge of COVID-19 patients. OBJECTIVE: In this study we created a simulation-based prognostic tool that provides the management of the University Hospital of Augsburg and the civil protection services with the necessary information to plan and guide the disaster response to the ongoing pandemic. Especially the number of beds needed on isolation wards and intensive care units (ICU) are the biggest concerns. The focus should lie not only on the confirmed cases as the patients with suspected COVID-19 are in need of the same resources. MATERIAL AND METHODS: For the input we used the latest information provided by governmental institutions about the spreading of the disease, with a special focus on the growth rate of the cumulative number of cases. Due to the dynamics of the current situation, these data can be highly variable. To minimize the influence of this variance, we designed distribution functions for the parameters growth rate, length of stay in hospital and the proportion of infected people who need to be hospitalized in our area of responsibility. Using this input, we started a Monte Carlo simulation with 10,000 runs to predict the range of the number of hospital beds needed within the coming days and compared it with the available resources. RESULTS: Since 2 February 2020 a total of 306 patients were treated with suspected or confirmed COVID-19 at this university hospital. Of these 84 needed treatment on the ICU. With the help of several simulation-based forecasts, the required ICU and normal bed capacity at Augsburg University Hospital and the Augsburg ambulance service in the period from 28 March 2020 to 8 June 2020 could be predicted with a high degree of reliability. Simulations that were run before the impact of the restrictions in daily life showed that we would have run out of ICU bed capacity within approximately 1 month. CONCLUSION: Our simulation-based prognosis of the health care capacities needed helps the management of the hospital and the civil protection service to make reasonable decisions and adapt the disaster response to the realistic needs. At the same time the forecasts create the possibility to plan the strategic response days and weeks in advance. The tool presented in this study is, as far as we know, the only one accounting not only for confirmed COVID-19 cases but also for suspected COVID-19 patients. Additionally, the few input parameters used are easy to access and can be easily adapted to other healthcare systems.