Can public health registry data improve Emergency Medical Dispatch?

Emergency Medical Dispatchers make decisions based on limited information. We aimed to investigate if adding demographic and hospitalization history information to the dispatch process improved precision.

This 30-day follow-up study evaluated time-critical emergencies in contact with the emergency phone number 112 in Denmark during 18 months. 'Time-critical' was defined as suspected First Hour Quintet (FHQ) (cardiac arrest, chest pain, stroke, difficulty breathing, trauma). The association of age, sex, and hospitalization history with adverse outcomes was examined using logistic regression. The predictive ability was assessed via area under the curve (AUC) and Hosmer-Lemeshow tests.

Of 59,943 patients (median age 63 years, 45% female), 44-45.5% had at least one chronic condition, 3880 (6.47%) died the day or the day after (primary outcome) calling 112. Age 30-59 was associated with increased adjusted odds ratio (OR) of death on day 1 of 3.59 [2.88-4.47]. Male sex was associated with an increased adjusted OR of death on day 1 of 1.37 [1.28-1.47]. Previous hospitalization with nutritional deficiencies (adjusted OR 2.07 [1.47-2.92]) and severe chronic liver disease (adjusted OR 2.02 [1.57-2.59]) was associated with a higher risk of death. For trauma patients, the discriminative ability of the model showed an AUC of 0.74 for death on day 1.

Increasing age, male sex, and hospitalization history was associated with increased risk of death on day 1 for FHQ 112 callers. Additional efforts are warranted to clarify the role for risk prediction tools in emergency medical dispatch.