Paramedic Out-of-Hospital Cardiac Arrest Case Volume Is a Predictor of Return of Spontaneous Circulation

Jenna E. Tuttle, MHS, NRP; Michael W. Hubble, PhD, NRP


Western J Emerg Med. 2018;19(4):654-659. 

In This Article


Data Sources

With institutional review board approval from Western Carolina University, we conducted a retrospective observational study of the influence of cardiac-arrest case volume on ROSC using the North Carolina Prehospital Care Reporting System (PreMIS) database. PreMIS is the data collection and management system that collects statewide data from over 400 North Carolina EMS agencies. Data are submitted to PreMIS for all EMS responses in North Carolina, and the data points for collection are a subset of the National Emergency Medical Services Information System (NEMSIS) dataset.[5]

Outcome Measures

The primary outcome measure was prehospital ROSC. We did not make any distinction between transient or persistent ROSC.

Study Setting

North Carolina is the nation's ninth most populous state with approximately 10 million people dispersed across a land mass of 48,617 square miles.[6] Demographically, the state is comprised of urban, suburban, and rural populations, with 33.9% of the population living in rural areas.[7] Cardiovascular disease is the second leading cause of death in the state, resulting in 18,467 deaths in 2015.[8]


We queried the PreMIS database to identify individuals who suffered a cardiac arrest in North Carolina between January 1, 2012, and June 30, 2014. These records were then filtered to meet our inclusion and exclusion criteria. Inclusion criteria consisted of all adult patients (≥18 years) suffering a bystander- or EMS-witnessed, non-traumatic cardiac arrest. The PreMIS database was then queried by the primary paramedic attending to each patient in the sample to determine his/her number of cardiac arrest cases treated in the previous five years. In determining the historical OHCA case volume, no distinction was made as to whether the paramedic was the primary attending paramedic, or "code leader," or assumed a secondary ("skills") role on the resuscitation team. We believed that any experience in OHCA resuscitation, whether in a primary or secondary role, would contribute positively to the cumulative resuscitation experience.

Statistical Analysis

We analyzed abstracted data using IBM SPSS Statistics version 24 (IBM Corporation, Somers, NY) with p ≤ 0.05 indicating statistical significance. Continuous variables and time intervals are presented as means (standard deviation), and categorical variables are presented using frequency distributions and percentages. We compared continuous variables using Student's t-test or the Mann-Whitney test. Categorical data were analyzed using the chi square test, continuity correction, or Fisher's exact test as appropriate. We calculated an adjusted odds ratio (OR) for the influence of OHCA case volume using logistic regression to control for potentially confounding variables identified a priori as patient age, gender, and non-Caucasian race; shockable presenting rhythm; layperson/first responder CPR; and EMS response time.