Related Experiment Video
Updated: Sep 27, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Emergency Medical Services Demand: An Analysis of County-Level Social Determinants
1School of Health Sciences, Western Carolina University, Cullowhee, NC, USA.
Objectives:
Variations in the demand for Emergency Medical Services (EMS) exist when observed at a local level. This unspecified heterogeneity leads to an investigation of social factors contributing to EMS demand.
Methods:
Data for this study were collected from publicly available EMS reports from Florida and Oklahoma for 2009 - 2015. Health and social data were gathered from County health rankings and roadmap reports. Data were combined into a single dataset, and pooled ordinary-least-squares models with time-fixed effects were utilized for tests of inference. EMS call volume was log-transformed to derive a semi-elasticity function.
Results:
A total of 874 county-year observations were analyzed. Increases in poor/fair health (95% CI: 0.6% - 3.9%), binge drinking (95% CI: 1.6% - 3.5%), teen birth rate (95% CI: 1.1% - 5.2%), unemployment rate (95% CI: 0.5% - 3.9%), and violent crime rate (95% CI: 1.0% - 3.0%) were associated with an increase in the EMS demand rate.
Conclusion:
The data supports the notion that some community measures have an effect on EMS demand as counties with higher levels of poor health, binge drinking, teen births, unemployment, and violent crime saw higher EMS demand. These factors may have been treated as spurious, or overlooked by policy makers and EMS leadership.
More Related Videos
06:59A Novel Approach for the Administration of Medications and Fluids in Emergency Scenarios and Settings
Published on: November 9, 2016
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Related Concept Videos
Statistical Methods for Analyzing Epidemiological Data
Manipulation and Analysis
Bystander Effect
Applications of GIS: Disaster Management and Emergency Response
Causality in Epidemiology
Steps in Outbreak Investigation