Can public health registry data improve Emergency Medical Dispatch?

Area of Science:

• Emergency Medicine
• Public Health
• Health Informatics

Background:

• Emergency Medical Dispatchers (EMD) operate with limited information during critical events.
• Investigating enhanced data for EMD decision-making is crucial for improving patient outcomes.

Purpose of the Study:

• To determine if demographic and hospitalization history data improve precision in emergency medical dispatch.
• To assess the association of patient factors with adverse outcomes in time-critical emergencies.

Main Methods:

• A 30-day follow-up study analyzed 18 months of 112 calls in Denmark for time-critical emergencies (First Hour Quintet).
• Logistic regression examined the impact of age, sex, and hospitalization history on adverse outcomes.
• Predictive ability was measured using Area Under the Curve (AUC) and Hosmer-Lemeshow tests.

Main Results:

• Of 59,943 patients, 6.47% died within 1-2 days of calling 112.
• Increased risk of death was associated with ages 30-59 (OR 3.59), male sex (OR 1.37), and prior hospitalizations for nutritional deficiencies or liver disease.
• The model achieved an AUC of 0.74 for predicting death in trauma patients.

Conclusions:

• Age, male sex, and hospitalization history are significant predictors of 1-day mortality in First Hour Quintet emergencies.
• Further research is needed to integrate risk prediction tools into emergency medical dispatch protocols.