Analytics & Research

Data analytics refers to the collection, transformation, and interpretation of large sets of data by industry experts—delivering meaningful insights into diagnostic trends, predictive modeling, patient and physician outcomes that drive more informed decision-making.

Stakeholders without a foundation in emergency medicine, such as hospitals, other specialties, and the government have previously conducted analytics that negatively impacted emergency medicine. ACEP has the necessary combination of emergency physicians, scientists, and policymakers to generate nuanced analytics to improve patient and physician outcomes.

While data alone does not solve clinical problems, when analyzed and utilized by experts, comprehensive emergency care data can transform emergency medicine and health care by providing critical insights into the challenges of emergency practice and the factors that improve patient outcomes.

Since 2015, the EM Data institute has accumulated a wealth of comprehensive emergency medicine data, including from critical years of pandemic operations and changing health care models.

The CEDR database, a component of the EM Data Institute, contains encounter-level EHR and billing data from emergency department arrival to emergency department discharge. Research may be done on all 250+ elements in our database. Consistent with the mission and the nature of the data partnerships, all data is de-identified on ACEP premises prior to any external analyses and/or publication. Learn more in this article.

ACEP is continually seeking research, educational, and industry partners to use the data in this platform to facilitate clinically relevant research. See questions #8 and #9 for ways to get involved.

ACEP’s data science program targets research for improving health care data capture to describing late-breaking emergent trends and predictive models using AI, machine learning, and synthetic data. We are currently engaged in several projects –

• Substance use disorder measure development, with the NIH HEAL Initiative^®, an NIH-wide effort to speed scientific solutions to stem the national opioid public health crisis
• Pulmonary embolism measure development and natural language process implementation, with the Gordon and Betty Moore Foundation
• Research element standardization in acute diagnoses, with the Council of Medical Specialty Societies
• National-level data extraction for the Center of Disease Control’s national statistical surveys
• National-level naloxone usage during ED and pre-hospital encounters, with the FDA

ACEP has collaborated with various individuals and institutes in publications. View the complete list.

Reference List Here

We welcome all research and data access requests through our dedicated submission form. Your request will go directly to our Data Science team for review.

• Members interested in data analytics are encouraged to join the ACEP Quality and Patient Safety Section. Visit their website.
• Members interested in learning about how electronic quality data are collected should join the Health Information Technology Committee. Applications open on May 15. Visit their website.
• Members interested in how data can be used for academic and industry-partnered research can join the Emergency Medicine Data Institute Research Committee and/or Innovation Advisory Group. Contact us to apply.
• Consider partnering with ACEP when applying for novel grant funding opportunities such as proposals to CDC, FDA, NIH, PCORI, etc. Contact us to be a partner in grant submission.
• Collaborate with ACEP EM Data Institute subject matter experts on new research and publication opportunities in Annals of Emergency Medicine, JACEP Open, and the National Library of Medicine.

Companies and non-academic partners are critical EM stakeholders. We welcome the following research data requests:

• Targeted data queries against multiple years of data for any EM clinical use case
• Analytics and scientific report generation on any EM clinical use case
• Large data abstraction queries for model trainin

Please use our dedicated submission form. Your request will go directly to our Data Science team for review.