Impact of COVID-19 on Emergency Medical Services Utilization and Severity in the U.S. Upper Midwest
Boggust, B.; McCoy, R.; Shalom, M.; Myers, L.; Rogerson, C.
Show abstract
The COVID-19 pandemic has claimed nearly one million lives and has drastically changed how patients interact with the healthcare system. Emergency medical services (EMS) are essential for emergency response, disaster preparedness, and responding to everyday emergencies. We therefore examined differences in EMS utilization and call severity in 2020 (pandemic period) compared to trends from 2015-2019 (pre-pandemic period) in a large, multi-state advanced life support EMS agency serving the U.S. Upper Midwest. Specifically, we analyzed all 911 calls made to Mayo Clinic Ambulance, the sole advanced life support EMS provider serving a large area in Minnesota and Wisconsin, in 2020 compared to those made between 2015-2019. We compared the number of emergency calls made in 2020 to the number of calls expected based on trends from 2015-2019. We similarly compared caller demographics, call severity, and proportions of calls made for overdose/intoxication, behavioral health, and motor vehicle accidents. Subgroup analyses were performed for rural vs. urban areas. We identified 262,232 emergent EMS calls in the pre-pandemic period and 53,909 calls in the pandemic period, corresponding to a decrease of 28.7% in call volume during the pandemic period. Caller demographics shifted towards older patients (mean age 59.7 [SD, 23.0] vs. 59.1 [SD, 23.7] years; p<0.001) and to rural areas (20.4% vs. 20.0%; p=0.007). Call severity increased, with 95.3% of calls requiring transport (vs. 93.8%; p<0.001) and 1.9% resulting in death (vs. 1.6%; p<0.001). The proportion of calls for overdose/intoxication increased from 4.8% to 5.5% (p<0.001), while the proportion of calls for motor vehicle collisions decreased from 3.9% to 3.0% (p<0.001). All changes were more pronounced in urban areas. These findings underscore the extent to which the COVID-19 pandemic impacted healthcare utilization, particularly in urban areas, and suggest that patients may have delayed calling EMS with potential implications on disease severity and risk of death.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- EMS injury cause codes more accurate than emergency department visit ICD-10-CM codes for firearm injury intent in North Carolina 96%
- The COVID-19 health equity twindemic: Statewide epidemiologic trends of SARS-CoV-2 outcomes among racial minorities and in rural America 94%
- Derivation and validation of a triage tool for acutely ill adults with suspected COVID-19: The PRIEST observational cohort study 94%
Similar papers in this journal
- Variation in ambulance pre-alert process and practice: Cross-sectional survey of ambulance clinicians 95%
- Accuracy of the National Early Warning Score version 2 (NEWS2) in predicting need for time-critical treatment: Retrospective observational cohort study 94%
- Emergency medicine patient wait time multivariable prediction models: a multicentre derivation and validation study 93%
Similar papers in this journal
- Establishing consensus on emergency department interventions that could be conducted in sub-acute care settings for non-emergent paramedic transported visits: A RAND/UCLA modified Delphi study 95%
- Derivation And Validation Of A Clinical Score To Predict Death Among Non-Palliative COVID-19 Patients Presenting To Emergency Departments: The Ccedrrn COVID Mortality Score 93%
- Analyzing Supply and Demand on a General Internal Medicine Ward: A Cross-Sectional Study 92%
Similar papers in this journal
- Socioeconomic and comorbid factors affecting mortality and length of stay in COVID-19 94%
- Changes in emergency department utilization in vulnerable populations after COVID-19 shelter in place orders 93%
- Severe bandemia is not associated with increased risk for adverse events in general pediatric emergency department patients 92%
Similar papers in this journal
- Restrictions on top speed and nighttime usage substantially decrease the incidence of electric scooter injuries 93%
- Score for Emergency Risk Prediction (SERP): An Interpretable Machine Learning AutoScore–Derived Triage Tool for Predicting Mortality after Emergency Admissions 93%
- Suicide Deaths during the Stay-at-Home Advisory in Massachusetts 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.