Related Experiment Video
Updated: Mar 26, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
Identifying Frequent Users of an Urban Emergency Medical Service Using Descriptive Statistics and Regression Analyses
Chenelle Norman1, Michael Mello2, Bryan Choi3
1Brown University, School of Public Health, Providence, Rhode Island.
Abstract:
This retrospective cohort study provides a descriptive analysis of a population that frequently uses an urban emergency medical service (EMS) and identifies factors that contribute to use among all frequent users. For purposes of this study we divided frequent users into the following groups: low- frequent users (4 EMS transports in 2012), medium-frequent users (5 to 6 EMS transports in 2012), high-frequent users (7 to 10 EMS transports in 2012) and super-frequent users (11 or more EMS transports in 2012). Overall, we identified 539 individuals as frequent users. For all groups of EMS frequent users (i.e. low, medium, high and super) one or more hospital admissions, receiving a referral for follow-up care upon discharge, and having no insurance were found to be statistically significant with frequent EMS use (P<0.05). Within the diagnostic categories, 41.61% of super-frequent users had a diagnosis of "primarily substance abuse/misuse" and among low-frequent users a majority, 53.33%, were identified as having a "reoccurring (medical) diagnosis." Lastly, relative risk ratios for the highest group of users, super-frequent users, were 3.34 (95% CI [1.90-5.87]) for obtaining at least one referral for follow-up care, 13.67 (95% CI [5.60-33.34]) for having four or more hospital admissions and 5.95 (95% CI [1.80-19.63]) for having a diagnoses of primarily substance abuse/misuse. Findings from this study demonstrate that among low- and medium-frequent users a majority of patients are using EMS for reoccurring medical conditions. This could potentially be avoided with better care management. In addition, this study adds to the current literature that illustrates a strong correlation between substance abuse/misuse and high/super-frequent EMS use. For the subgroup analysis among individuals 65 years of age and older, we did not find any of the independent variables included in our model to be statistically significant with frequent EMS use.
More Related Videos
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
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
Comparing the Survival Analysis of Two or More Groups
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Steps in Outbreak Investigation
Kaplan-Meier Approach
Mechanistic Models: Compartment Models in Individual and Population Analysis