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.

EMS utilization predictors in a Mobile Integrated Health (MIH) program.

BACKGROUND: The provision of unnecessary Emergency Medical Services care remains a challenge throughout the US and contributes to Emergency Department overcrowding, delayed services and lower quality of care. New EMS models of care have shown promise in improving access to health services for patients who do not need urgent care. The goals of this study were (1) to identify factors associated with EMS utilization (911) and (2) their effects on total EMS calls and transports in an MIH program. METHODS: The study sample included 110 MIH patients referred to the program or considered high-users of EMS services between November 2016 and September 2018. The study employed descriptive statistics and Poisson regressions to estimate the effects of covariates on total EMS calls and transports. RESULTS: The typical enrollee is a 60-year-old single Black male living with two other individuals. He has a PCP, takes 12 medications and is compliant with his treatment. The likelihood of calling and/or being transported by EMS was higher for males, patients at high risk for falls, patients with asthma/COPD, psychiatric or behavioral illnesses, and longer travel times to a PCP. Each prescribed medication increased the risk for EMS calls or transports by 4%. The program achieved clear reductions in 911 calls and transports and savings of more than 140,000 USD in the first month. CONCLUSIONS: This study shows that age, marital status, high fall risk scores, the number of medications, psychiatric/behavioral illness, asthma/COPD, CHF, CVA/stroke and medication compliance may be good predictors of EMS use in an MIH setting. MIH programs can help control utilization of EMS care and reduce both EMS calls and transports.

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.

A profile of middle-aged and older adults admitted to nursing homes: 2000-2008.

Middle-aged adults are becoming an increasing share of the nursing home population. Minimum Data Set assessment data for 2000 and 2008 are used to explore similarities and differences in sociodemographic, residential, medical, and psychiatric characteristics of newly admitted middle-aged adults (31-64) compared to their older counterparts (65+). Relative to their share of the state population, Black middle-aged adults are overrepresented in nursing homes across 45 states and the District of Columbia. Chronic conditions, including diabetes, renal failure, chronic obstructive pulmonary disease, asthma, and circulatory/heart disorders, appeared to contribute to the increasing presence of middle-aged adults. There were substantial increases in diagnoses of psychiatric disorders at admission; psychiatric diagnoses were significantly higher among middle-aged adults. Middle-aged adults were also more likely to have residential histories of prior stays in psychiatric facilities relative to older adults. States' rebalancing efforts need to attend to the increasing presence of disability associated with chronic medical and psychiatric conditions among middle-aged adults.