Safety of an Alternative Care Protocol for EMS Non-Transport in the COVID-19 Pandemic.

AIM: Our primary goal was to evaluate safety of a new emergency medical services (EMS) protocol directing non-transport of low-acuity patients during the COVID-19 pandemic. METHODS: We performed a retrospective cohort analysis of all patients in Marion County, Indiana, from March 23, 2020 to May 25, 2020 for whom a novel non-transport protocol was used by EMS for patients with low-acuity COVID-19 symptoms. We assessed paramedic compliance with the protocol to determine numbers and types of deviations. We further reviewed a statewide health information exchange database to identify any patients with emergency department (ED) visits, hospital admissions, or death within 30 days of the EMS non-transport. For ED and hospital visits, we collected ED or admission diagnoses to determine if the etiologies were COVID-related. RESULTS: Between March 24, 2020 and May 25, 2020, 222 patients were documented as "Treated, Released (per protocol)." The protocol was correctly applied 144 times (64.8%). The other 78 times, although the EMS clinicians documented use of the protocol, it was not actually used (e.g., another protocol such as "no medical emergency" was used). Of the 144 patients for whom the protocol was used, in 55 cases (38.2%), the clinicians documented patient factors that should have contraindicated use of the protocol (e.g., chest pain, past medical history of asthma). The protocol was applied 5 times (3.5%) in pediatric patients. Two patients were admitted to the hospital within 72 hours of incorrect application of the protocol; both were for COVID-related complaints. Two patients were admitted to the hospital within 72 hours of correct protocol use; one was for a COVID-related complaint. CONCLUSION: In this case series, paramedics demonstrated large deviations from the novel non-transport protocol. Several patients were admitted to the hospital within 72 hours of non-transport both when the protocol was used correctly, and when it was used incorrectly.

Incidence and characteristics of arterial thromboemboli in patients with COVID-19.

BACKGROUND: Studies have reported COVID-19 as an independent risk factor for arterial thromboemboli. METHODS: From a cross-sectional sample, we determined the incidence and location of arterial thromboemboli (myocardial infarction, ischemic stroke, peripheral artery), stratified by COVID-19 status, in the RECOVER database, which included data on patients at 45 United States medical centers in 22 states. Epidemiological factors, clinical characteristics and outcomes were collected through a combination of individual chart review and automatic electronic query and recorded in REDCap®. We investigated the association of baseline comorbidities on the development of arterial thromboemboli and analyzed results based on the presence or absence of concomitant COVID-19 infection, testing this association with Chi-squared. We also described use of anticoagulants and statins. RESULTS: Data were collected on 26,974 patients, of which 13,803 (51.17%) tested positive for COVID-19. Incidence of arterial thromboemboli during hospitalization was 0.13% in patients who tested positive for COVID-19 and 0.19% in patients who tested negative. Arterial thromboemboli tended to be more common in extremities than in core organs (heart, kidney, lung, liver) in patients with COVID-19, odds ratio 2.04 (95% CI 0.707 - 5.85). Patients with COVID-19 were less likely to develop an arterial thrombus when on baseline statin medication (p=0.014). Presence of metabolic syndrome predicted presence of core arterial thrombus (p=0.001) and extremity arterial thrombus (p=0.010) in those with COVID-19. Arterial thromboemboli were less common in patients with COVID-19 than in those who tested negative for COVID-19. CONCLUSIONS: Presence of a composite metabolic syndrome profile may be associated with arterial clot formation in patients with COVID-19 infection.

Fluid Resuscitation and Progression to Renal Replacement Therapy in Patients With COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is associated with respiratory symptoms and renal effects. Data regarding fluid resuscitation and kidney injury in COVID-19 are lacking, and understanding this relationship is critical. OBJECTIVES: To determine if there is an association between fluid volume administered in 24 h and development of renal failure in COVID-19 patients. METHODS: Retrospective chart review; 14 hospitals in Indiana. Included patients were adults admitted between March 11, 2020 and April 13, 2020 with a positive test for severe acute respiratory syndrome coronavirus 2 within 3 days of admission. Patients requiring renal replacement therapy prior to admission were excluded. Volumes and types of resuscitative intravenous fluids in the first 24 h were obtained with demographics, medical history, and other objective data. The primary outcome was initiation of renal replacement therapy. Logistic regression modeling was utilized in creating multivariate models for determining factors associated with the primary outcome. RESULTS: The fluid volume received in the first 24 h after hospital admission was associated with initiation of renal replacement therapy in two different multivariate logistic regression models. An odds ratio of 1.42 (95% confidence interval 1.01-1.99) was observed when adjusting for age, heart failure, obesity, creatinine, bicarbonate, and total fluid volume. An odds ratio of 1.45 (95% confidence interval 1.02-2.05) was observed when variables significant in univariate analysis were adjusted for. CONCLUSIONS: Each liter of intravenous fluid administered to patients with COVID-19 in the first 24 h of presentation was independently associated with an increased risk for initiation of renal replacement therapy, supporting judicious fluid administration in patients with this disease.

Out-of-hospital cardiac arrest volumes and characteristics during the COVID-19 pandemic.

AIM: The COVID-19 pandemic has significantly impacted Emergency Medical Services (EMS) operations throughout the country. Some studies described variation in total volume of out-of-hospital cardiac arrests (OHCA) during the pandemic. We aimed to describe the changes in volume and characteristics of OHCA patients and resuscitations in one urban EMS system. METHODS: We performed a retrospective cohort analysis of all recorded atraumatic OHCA in Marion County, Indiana, from January 1, 2019 to June 30, 2019 and from January 1, 2020 to June 30, 2020. We described patient, arrest, EMS response, and survival characteristics. We performed paired and unpaired t-tests to evaluate the changes in those characteristics during COVID-19 as compared to the prior year. Data were matched by month to control for seasonal variation. RESULTS: The total number of arrests increased from 884 in 2019 to 1034 in 2020 (p = 0.016). Comparing 2019 to 2020, there was little difference in age [median 62 (IQR 59-73) and 60 (IQR 47-72), p = 0.086], gender (38.5% and 39.8% female, p = 0.7466, witness to arrest (44.3% and 39.6%, p = 0.092), bystander AED use (10.1% and 11.4% p = 0.379), bystander CPR (48.7% and 51.4%, p = 0.242). Patients with a shockable initial rhythm (19.2% and 15.4%, p = 0.044) both decreased in 2020, and response time increased by 18 s [6.0 min (IQR 4.5-7.7) and 6.3 min (IQR 4.7-8.0), p = 0.008]. 47.7% and 54.8% (p = 0.001) of OHCA patients died in the field, 19.7% and 19.3% (p = 0.809) died in the Emergency Department, 21.8% and 18.5% (p = 0.044) died in the hospital, 10.8% and 7.4% (p = 0.012) were discharged from the hospital, and 9.3% and 5.9% (p = 0.005) were discharged with Cerebral Performance Category score ≤ 2. CONCLUSION: Total OHCA increased during the COVID-19 pandemic when compared with the prior year. Although patient characteristics were similar, initial shockable rhythm, and proportion of patients who died in the hospital decreased during the pandemic. Further investigation will explore etiologies of those findings.

Can we predict which COVID-19 patients will need transfer to intensive care within 24 hours of floor admission?

BACKGROUND: Patients with COVID-19 can present to the emergency department (ED) at any point during the spectrum of illness, making it difficult to predict what level of care the patient will ultimately require. Admission to a ward bed, which is subsequently upgraded within hours to an intensive care unit (ICU) bed, represents an inability to appropriately predict the patient's course of illness. Predicting which patients will require ICU care within 24 hours would allow admissions to be managed more appropriately. METHODS: This was a retrospective study of adults admitted to a large health care system, including 14 hospitals across the state of Indiana. Included patients were aged ≥ 18 years, were admitted to the hospital from the ED, and had a positive polymerase chain reaction (PCR) test for COVID-19. Patients directly admitted to the ICU or in whom the PCR test was obtained > 3 days after hospital admission were excluded. Extracted data points included demographics, comorbidities, ED vital signs, laboratory values, chest imaging results, and level of care on admission. The primary outcome was a combination of either death or transfer to ICU within 24 hours of admission to the hospital. Data analysis was performed by logistic regression modeling to determine a multivariable model of variables that could predict the primary outcome. RESULTS: Of the 542 included patients, 46 (10%) required transfer to ICU within 24 hours of admission. The final composite model, adjusted for age and admission location, included history of heart failure and initial oxygen saturation of <93% plus either white blood cell count > 6.4 or glomerular filtration rate < 46. The odds ratio (OR) for decompensation within 24 hours was 5.17 (95% confidence interval [CI] = 2.17 to 12.31) when all criteria were present. For patients without the above criteria, the OR for ICU transfer was 0.20 (95% CI = 0.09 to 0.45). CONCLUSIONS: Although our model did not perform well enough to stand alone as a decision guide, it highlights certain clinical features that are associated with increased risk of decompensation.

OpenMRS as an emergency EMR-How we used a global good to create an emergency EMR in a week.

BACKGROUND: As the coronavirus pandemic progressed through the United States, Indianapolis Emergency Medical Services (IEMS) identified a gap between the health system capacity and the projected need to support an overwhelmed health care system. In addressing emergencies or special cases, each medical institution in a metropolitan area typically has a siloed process for capturing emergency patient records. These approaches vary in technical capabilities and may include use of an electronic medical record system (EMR) or a hybrid paper/EMR process. Given the projected volume of patients for the COVID-19 pandemic and the proposed multi-institutional team approach needed in case of significant provider illness, IEMS sought a simple, efficient, consolidated EMR solution to support planning for the potential capacity gap. IEMS approached Regenstrief Institute (RI), an established partner with experience in supporting OpenMRS, a global good EMR platform that had been deployed in multiple settings globally. OBJECTIVE: The purpose of this project was to determine if OpenMRS, a global good, could be used to quickly stand up a system that would meet the needs for health emergency data collection and reporting. DESIGN AND IMPLEMENTATION METHODS: The team used an "all hands on deck" approach, bringing together technical and subject matter experts, and a human-centered and iterative process to ensure the system met the key needs of IEMS. The OpenMRS Reference Application was adapted to the specific need and deployed as Docker containers to servers within the Indiana Health Information Exchange. PROJECT OUTCOMES AND LESSONS LEARNED: In less than two weeks, the Regenstrief team was able to install, configure and set up a working version of OpenMRS to support the desired electronic record requirements for the IEMS disaster field clinics. Using a human-centered approach, the RI team developed, tested, and released a user-friendly, installation-ready solution complete with an end user manual and a base support plan. IEMS and RI are sharing this approach to demonstrate how a global good can quickly generate a solution for COVID-19 and other disaster responses. CONCLUSIONS: Open source global goods can rapidly be adapted to meet local needs in an emergency. OpenMRS can be adapted to meet the needs of basic emergency medical services registration, triage, and basic data collection.

Characteristics of COVID-19 patients with bacterial coinfection admitted to the hospital from the emergency department in a large regional healthcare system.

INTRODUCTION: The rate of bacterial coinfection with SARS-CoV-2 is poorly defined. The decision to administer antibiotics early in the course of SARS-CoV-2 infection depends on the likelihood of bacterial coinfection. METHODS: We performed a retrospective chart review of all patients admitted through the emergency department with confirmed SARS-CoV-2 infection over a 6-week period in a large healthcare system in the United States. Blood and respiratory culture results were abstracted and adjudicated by multiple authors. The primary outcome was the rate of bacteremia. We secondarily looked to define clinical or laboratory features associated with bacteremia. RESULTS: There were 542 patients admitted with confirmed SARS-CoV-2 infection, with an average age of 62.8 years. Of these, 395 had blood cultures performed upon admission, with six true positive results (1.1% of the total population). An additional 14 patients had positive respiratory cultures treated as true pathogens in the first 72 h. Low blood pressure and elevated white blood cell count, neutrophil count, blood urea nitrogen, and lactate were statistically significantly associated with bacteremia. Clinical outcomes were not statistically significantly different between patients with and without bacteremia. CONCLUSIONS: We found a low rate of bacteremia in patients admitted with confirmed SARS-CoV-2 infection. In hemodynamically stable patients, routine antibiotics may not be warranted in this population.

Impact of COVID-19 Pandemic on Drug Overdoses in Indianapolis.

We described the change in drug overdoses during the COVID-19 pandemic in one urban emergency medical services (EMS) system. Data was collected from Marion County, Indiana (Indianapolis), including EMS calls for service (CFS) for suspected overdose, CFS in which naloxone was administered, and fatal overdose data from the County Coroner's Office. With two sample t tests and ARIMA time series forecasting, we showed changes in the daily rates of calls (all EMS CFS, overdose CFS, and CFS in which naloxone was administered) before and after the stay-at-home order in Indianapolis. We further showed differences in the weekly rate of overdose deaths. Overdose CFS and EMS naloxone administration showed an increase with the social isolation of the Indiana stay-at-home order, but a continued increase after the stay-at-home order was terminated. Despite a mild 4% increase in all EMS CFS, overdose CFS increased 43% and CFS with naloxone administration increased 61% after the stay-at-home order. Deaths from drug overdoses increased by 47%. There was no change in distribution of age, race/ethnicity, or zip code of those who overdosed after the stay-at-home order was issued. We hope this data informs policy-makers preparing for future COVID-19 responses and other disaster responses.