Objective:
The aim of this study was to investigate the performance of key hospital units associated with emergency care of both routine emergency and pandemic (COVID-19) patients under capacity enhancing strategies.
Methods:
This investigation was conducted using whole-hospital, resource-constrained, patient-based, stochastic, discrete-event simulation models of a generic 200-bed urban U.S. tertiary hospital serving routine emergency and COVID-19 patients. Systematically designed numerical experiments were conducted to provide generalizable insights into how hospital functionality may be affected by the care of COVID-19 pandemic patients along specially designated care paths under changing pandemic situations from getting ready to turning all of its resources to pandemic care.
Results:
Several insights are presented. For example, each day of reduction in average ICU length of stay increases intensive care unit patient throughput by up to 24% for high COVID-19 daily patient arrival levels. The potential of five specific interventions and two critical shifts in care strategies to significantly increase hospital capacity is described.
Conclusions:
These estimates enable hospitals to repurpose space, modify operations, implement crisis standards of care, prepare to collaborate with other health care facilities, or request external support, increasing the likelihood that arriving patients will find an open staffed bed when one is needed.
Objective This paper investigates the impact on emergency hospital services from initiation through recovery of a ransomware attack affecting the emergency department, intensive care unit and supporting laboratory services. Recovery strategies of paying ransom to the attackers with follow-on restoration and in-house full system restoration from backup are compared. Methods A multi-unit, patient-based and resource-constrained discrete-event simulation model of a typical U.S. urban tertiary hospital is adapted to model the attack, its impacts, and tested recovery strategies. The model is used to quantify the hospital's resilience to cyberattack. Insights were gleaned from systematically designed numerical experiments. Results While paying the ransom was found to result in some short-term gains assuming the perpetrators actually provide the decryption key as promised, in the longer term, the results of this study suggest that paying the ransom does not pay off. Rather, paying the ransom, when considered at the end of the event when services are fully restored, precluded significantly more patients from receiving critically needed care. Also noted was a lag in recovery for the intensive care unit as compared with the emergency department. Such a lag must be considered in preparedness plans. Conclusion Vulnerability to cyberattacks is a major challenge to the healthcare system. This paper provides a methodology for assessing the resilience of a hospital to cyberattacks and analyzing the effects of different response strategies. The model showed that paying the ransom resulted in short-term gains but did not pay off in the longer term.
Drought and decrease in the level of lakes in recent years due to global warming and excessive use of water resources feeding lakes is of great importance and this research has provided a structure to investigate this issue. First, the information required for simulating lake drought is provided with strong references and necessary assumptions. Entity-Component-System (ECS) structure has been used for simulation which can consider assumptions flexibly in simulation. Three major users (i.e., Industry, agriculture, and Domestic users) consume water from ground water and surface water (i.e., streams, rivers and lakes). Lake Mead has been considered for simulation, and the information necessary to investigate its drought has also been provided. The results are presented in the form of scenario-based design and optimal strategy selection. For optimal strategy selection a deep reinforcement algorithm is developed to select the best set of strategies among all possible projects. These results can provide a better view of how to plan to prevent lake drought.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.