• Michael Redlener, David G Buckler, Samuel E Sondheim, Sai Kaushik Yeturu, George T Loo, Kevin G Munjal, Jeffrey Jarvis, and Remle P Crowe.
• Department of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York City, New York.
• Prehosp Emerg Care. 2024 Jan 1; 28 (5): 719726719-726.

BackgroundIn 2019, the National EMS Quality Alliance (NEMSQA) established a suite of 11 evidence-based EMS quality measures, yet little is known regarding EMS performance on a national level. Our objective was to describe EMS performance at a response and agency level using the National EMS Information System (NEMSIS) dataset.MethodsThe 2019 NEMSIS research dataset of all EMS 9-1-1 responses in the United States was utilized to calculate 10 of 11 NEMSQA quality measures. Measure criteria and pseudocode was implemented to calculate the proportion meeting measure criteria and 95% confidence intervals across all encounters and for each anonymized agency. We omitted Pediatrics-03b because the NEMSIS national dataset does not report patient weight. Agency level analysis was subsequently stratified by call volume and urbanicity.ResultsRecords from 9,679 agencies responding to 26,502,968 9-1-1 events were analyzed. Run-level average performance ranged from 12% for Safety-01 (encounter documented as initial response without the use of lights and siren to 82% for Pediatrics-02 (documented respiratory assessment in pediatric patients with respiratory distress) At the agency level, significant variation in measure performance existed by agency size and by urbanicity. At the individual agency performance analysis, Trauma-04 (trauma patients transported to trauma center) had the lowest agency-level performance with 47% of agencies reporting 0% of eligible runs with documented transport to a trauma center.ConclusionThere is a wide range of performance in key EMS quality measures across the United States that demonstrate a need to identify strategies to improve quality and equity of care in the prehospital environment, system performance and data collection.

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