Identifying a Consensus Set of EMS Agency Licensure Elements and Definitions to Support Rural EMS Data Collection
Document Type
Policy Brief
Publication Date
11-2023
Keywords
MRHRC, rural, EMS, emergency medical services, data, licensure
Topics
Emergency Medical Services
Abstract
Prior FMT rural Emergency Medical Services (EMS) studies have identified critical information gaps facing EMS agencies and systems of care. These include difficulties in quantifying the amount of volunteer staffing and a concurrent lack of data on EMS agency staffing and service levels, and a limited understanding of the service areas of individual EMS agencies. The current study builds upon recommendations from the previous studies and identifies a consensus set of core EMS licensure elements and definitions for consideration by state EMS authorities.
Based on state licensure review and expert panel input, we offer suggested standardized measures and definitions for consideration by state EMS authorities to enhance their agency licensure application processes and to align their licensure data collection efforts with other states. This brief will help EMS authorities inform their efforts to improve the ability of national EMS data sets in supporting rural EMS systems of care.
FMI: John Gale, john.gale@maine.edu
Funding Organization
HRSA, Federal Office of Rural Health Policy
Grant Number
U27RH01080.
Recommended Citation
Gale, J., Jewell, C., & Pearson, K. (2023). Identifying a Consensus Set of EMS Agency Licensure Elements and Definitions to Support Rural EMS Data Collection. University of Southern Maine, Flex Monitoring Team.
Comments
This report was completed by the Flex Monitoring Team with funding from the Federal Office of Rural Health Policy (FORHP), Health Resources and Services Administration (HRSA), U.S. Department of Health and Human Services (HHS), under PHS Grant No. U27RH01080. The information, conclusions and opinions expressed in this document are those of the authors and no endorsement by FORHP, HRSA, or HHS is intended or should be inferred.