Prehospital COVID-19-Related Encounters Predict Future Hospital Utilization

Area of Science:

• Public Health
• Epidemiology
• Emergency Medicine

Background:

• The COVID-19 pandemic placed unprecedented strain on healthcare systems globally.
• Accurate prediction of hospital utilization is crucial for resource allocation and patient care management during surges.
• Prehospital data, particularly from emergency medical services (EMS), offers a potential early indicator of disease trends.

Purpose of the Study:

• To determine if prehospital patient encounters related to SARS-CoV-2 (COVID-19) can predict subsequent hospital utilization.
• To assess the predictive value of EMS encounter data for medical-surgical and intensive care unit (ICU) bed usage.
• To validate these predictions across different COVID-19 surge periods.

Main Methods:

• Retrospective analysis of EMS data from NEMSIS systems in Minnesota for COVID-19-related prehospital encounters.
• Data included influenza-like illness (ILI) and COVID-19-specific calls during two surge periods (April-July 2020 and July-August 2020).
• EMS encounter data was correlated with hospital general medical-surgical and ICU bed utilization, with a 2019 ILI dataset used for validation.

Main Results:

• A total of 6,460 ILI calls and 2,161 COVID-19-specific calls were analyzed, alongside 24,806 medical-surgical and 20,208 ICU bed-days.
• EMS encounters strongly correlated with medical-surgical bed utilization 10 days in the future (r² = 0.85) and ICU bed utilization 16 days in the future (r² = 0.86).
• Each EMS encounter predicted 7.1 medical-surgical beds and 4.5 ICU beds. Similar correlations were observed during the second surge, with no significant correlation found for 2019 ILI data.

Conclusions:

• Prehospital COVID-19 encounters in Minnesota accurately predict hospital bed utilization one to two weeks in advance.
• The predictive relationship was consistent across two distinct COVID-19 surges.
• Trends in EMS patient encounters serve as a valuable early warning system for predicting COVID-19 surges and their impact on hospital capacity.