Expanding the evidence base with data from more than 2,000 organizations
The ESO Data Collaborative consists only of entities that have voluntarily agreed to allow use of their de-identified records for research and benchmarking purposes. In 2020, the Collaborative included data from over 2,000 EMS agencies, fire departments, and hospitals.
Annual Research Dataset
Built from the ESO Data Collaborative for research use and is made available in the second quarter of the following year.
Access to the Research Dataset
Access to this dataset is provided following a research proposal process and review from the Research Leadership Group.
ESO Data Collaborative Research Projects
The ESO Data Collaborative has powered more than 70 research projects.
Annual Public Use Research Dataset
Each year, a standardized core dataset is built from the ESO Data Collaborative for research use and is made available in the second quarter of the following year. Access to this dataset is provided following a research proposal process and review from the Research Leadership Group.
Over 8 million encounters in the dataset
The 2019 ESO Data Collaborative public release research dataset contained 8,340,148 EMS encounters. The majority of included EMS responses occurred in the South (58%) US Census region, followed by the Midwest (22%), West (16%) and Northeast (5%). Based on the US Census urbanicity categorizations, most encounters occurred in urbanized areas (76%) or urban clusters (18%).
Linking hospital outcome info with HDE
Approximately, 17% of records with EMS emergency response and patient transport had linked hospital outcome information through the HDE software, with representation from 25% of all agencies participating in the Data Collaborative.
More than 70 research projects
The ESO Data Collaborative has powered more than 70 research projects, including award-winning presentations at national conferences and peer-reviewed manuscripts in journals like Prehospital Emergency Care, Annals of Emergency Medicine, Resuscitation, and Journal of the American College of Emergency Physicians Open.
Initial Prehospital Rapid Emergency Medicine Score (REMS) as a Predictor of Patient Outcomes
The Rapid Emergency Medicine Score (REMS) uses six variables commonly collected in the prehospital setting (patient age, pulse rate, mean arterial pressure, respiratory rate, oxygen saturation and Glasgow Coma Scale score) to compute a weighted value for severity of illness or injury. REMS values range from 0 to 26, with 26 representing severe illness or injury. The study objective was to assess predictive characteristics of first prehospital REMS for ED disposition and overall patient mortality. This study used linked prehospital and Health Data Exchange (HDE) records for adult patients (18 or older) from the national ESO Data Collaborative in 2019. After analyzing 484,865 linked records, a REMS of 5 or lower demonstrated optimal statistical prediction for ED discharge versus admission/ transfer/death (AUROC: 0.68). A REMS of 7 or lower was statistically optimal for predicting survival (AUROC: 0.79).
The Cincinnati Prehospital Stroke Scale Compared to Stroke Severity Tools for Large Vessel Occlusion Stroke Prediction
The objective of this study was to describe prehospital ketamine use, patient outcomes, and the potential contribution of ketamine to patient death. In this sample of more than 11,000 patients across the U.S. who received prehospital ketamine, the most common indication was for trauma/pain (49%, 5,575), followed by altered mental status/behavioral (34%, 3,795), cardiovascular/pulmonary (13%, 1,454), seizure (2%, 248), and other indications (2%, 219). Doses observed fell within accepted therapeutic ranges and nearly all patients were transported to a hospital. Ketamine could not be ruled out as a contributing factor in 2 on scene deaths (0.02% of exposures) and 6 hospital deaths (0.3% of exposures). Following ketamine administration, hypoxia and hypercapnia were documented in 8.4% (897) and 17.2% (1,311) of patients, highlighting the importance of continuous SpO2 and EtCO2 monitoring.
2021 ESO Research Leadership Group Volunteers
The use of the data from the Data Collaborative is governed by the ESO Research Leadership Group (RLG). The RLG is comprised of volunteers who are leaders in the industry and are charged with evaluation of requests for utilization of the Collaborative to assure the data are sufficient to answer the intended question as well as to assure appropriate constraints regarding commercial bias and potential conflicts of interest.
All members are serving as individuals and are not representing any organization.
- Lawrence Brown, PhD
- Robin Garza, RN
- Amy Hanifan, OC, OREMT
- Michael Hubble, PhD, NRP
- Jeff Jarvis, MD, MS, EMT-P, FAEMS, FACEP
- Jason McMullan, MD, MS, FAEMS
- Jason Moats, PhD
- Kate Remick, MD, FAAP, FACEP, FAEMS
- Mary Ann Spott, PhD
- Henry Wang, MD