Models for Assessing Strategies for Improving Hospital Capacity for Handling Patients during a Pandemic.

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 5 specific interventions and 2 critical shifts in care strategies to significantly increase hospital capacity is also described. CONCLUSIONS: These estimates enable hospitals to repurpose space, modify operations, implement crisis standards of care, collaborate with other health care facilities, or request external support, thereby increasing the likelihood that arriving patients will find an open staffed bed when 1 is needed.

Assessing resilience of hospitals to cyberattack.

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.

Strategies for Improved Hospital Response to Mass Casualty Incidents.

Mass casualty incidents are a concern in many urban areas. A community's ability to cope with such events depends on the capacities and capabilities of its hospitals for handling a sudden surge in demand of patients with resource-intensive and specialized medical needs. This paper uses a whole-hospital simulation model to replicate medical staff, resources, and space for the purpose of investigating hospital responsiveness to mass casualty incidents. It provides details of probable demand patterns of different mass casualty incident types in terms of patient categories and arrival patterns, and accounts for related transient system behavior over the response period. Using the layout of a typical urban hospital, it investigates a hospital's capacity and capability to handle mass casualty incidents of various sizes with various characteristics, and assesses the effectiveness of designed demand management and capacity-expansion strategies. Average performance improvements gained through capacity-expansion strategies are quantified and best response actions are identified. Capacity-expansion strategies were found to have superadditive benefits when combined. In fact, an acceptable service level could be achieved by implementing only 2 to 3 of the 9 studied enhancement strategies. (Disaster Med Public Health Preparedness. 2018;12:778-790).