The Maryland (USA) Critical Care Coordination Center (C4): From Pandemic to Permanence.

INTRODUCTION: The 2019 coronavirus disease (COVID-19) pandemic created overwhelming demand for critical care services within Maryland's (USA) hospital systems. As intensive care units (ICUs) became full, critically ill patients were boarded in hospital emergency departments (EDs), a practice associated with increased mortality and costs. Allocation of critical care resources during the pandemic requires thoughtful and proactive management strategies. While various methodologies exist for addressing the issue of ED overcrowding, few systems have implemented a state-wide response using a public safety-based platform. The objective of this report is to describe the implementation of a state-wide Emergency Medical Services (EMS)-based coordination center designed to ensure timely and equitable access to critical care. METHODS: The state of Maryland designed and implemented a novel, state-wide Critical Care Coordination Center (C4) staffed with intensivist physicians and paramedics purposed to ensure appropriate critical care resource management and patient transfer assistance. A narrative description of the C4 is provided. A retrospective cohort study design was used to present requests to the C4 as a case series report to describe the results of implementation. RESULTS: Providing a centralized asset with regional situational awareness of hospital capability and bed status played an integral role for directing the triage process of critically ill patients to appropriate facilities during and after the COVID-19 pandemic. A total of 2,790 requests were received by the C4. The pairing of a paramedic with an intensivist physician resulted in the successful transfer of 67.4% of requests, while 27.8% were managed in place with medical direction. Overall, COVID-19 patients comprised 29.5% of the cohort. Data suggested increased C4 usage was predictive of state-wide ICU surges. The C4 usage volume resulted in the expansion to pediatric services to serve a broader age range. The C4 concept, which leverages the complimentary skills of EMS clinicians and intensivist physicians, is presented as a proposed public safety-based model for other regions to consider world-wide. CONCLUSION: The C4 has played an integral role in the State of Maryland's pledge to its citizens to deliver the right care to the right patient at the right time and can be considered as a model for adoption by other regions world-wide.

Correlation between Emergency Medical Services Suspected COVID-19 Patients and Daily Hospitalizations.

Objective: We sought to determine if Emergency Medical Services (EMS) identified Persons Under Investigation (PUI) for COVID-19 are associated with hospitalizations for COVID-19 disease for the purposes of serving as a potential early indicator of hospital surge. Methods: A retrospective analysis was conducted using data from the Maryland statewide EMS electronic medical records and daily COVID-19 hospitalizations from March 13, 2020 through July 31, 2020. All unique EMS patients who were identified as COVID-19 PUIs during the study period were included. Descriptive analysis was performed. The Box-Jenkins approach was used to evaluate the relationship between EMS transports and daily new hospitalizations. Separate Auto Regressive Integrated Moving Average (ARIMA) models were constructed to transform the data into a series of independent, identically distributed random variables. Fit was measured using the Akaike Information Criterion (AIC). The Box-Ljung white noise test was utilized to ensure there was no autocorrelation in the residuals. Results: EMS units in Maryland identified a total of 26,855 COVID-19 PUIs during the 141-day study period. The median patient age was 62 years old, and 19,111 (71.3%) were 50 years and older. 6,886 (25.6%) patients had an abnormal initial pulse oximetry (<92%). A strong degree of correlation was observed between EMS PUI transports and new hospitalizations. The correlation was strongest and significant at a 9-day lag from time of EMS PUI transports to new COVID-19 hospitalizations, with a cross correlation coefficient of 0.26 (p < .01). Conclusions: A strong correlation between EMS PUIs and COVID-19 hospitalizations was noted in this state-wide analysis. These findings demonstrate the potential value of incorporating EMS clinical information into the development of a robust syndromic surveillance system for COVID-19. This correlation has important utility in the development of predictive tools and models that seek to provide indicators of an impending surge on the healthcare system at large.