Increasing emergency number utilisation is not driven by low-acuity calls: an observational study of 1.5 million...

The Emergency Medical Service (EMS) in Germany is increasingly challenged by strongly rising demand. Speculations about a greater utilisation for minor cases have led to intensive media coverage, but empirical evidence is lacking. We investigated the development of low-acuity calls from 2018 to 2021 in the federal state of Berlin and its correlations with sociodemographic characteristics.

We analysed over 1.5 million call documentations including medical dispatch codes, age, location and time using descriptive and inferential statistics and multivariate binary logistic regression. We defined a code list to classify low-acuity calls and merged the dataset with sociodemographic indicators and data on population density.

The number of emergency calls (phone number 112 in Germany) increased by 9.1% from 2018 to 2021; however, the proportion of low-acuity calls did not increase. The regression model shows higher odds of low-acuity for young to medium age groups (especially for age 0-9, OR 1.50 [95% CI 1.45-1.55]; age 10-19, OR 1.77 [95% CI 1.71-1.83]; age 20-29, OR 1.64 [95% CI 1.59-1.68] and age 30-39, OR 1.40 [95% CI 1.37-1.44]; p < 0.001, reference group 80-89) and for females (OR 1.12 [95% CI 1.1-1.13], p < 0.001). Odds were slightly higher for calls from a neighbourhood with lower social status (OR 1.01 per index unit increase [95% CI 1.0-1.01], p < 0.05) and at the weekend (OR 1.02 [95% CI 1.0-1.04, p < 0.05]). No significant association of the call volume with population density was detected.

This analysis provides valuable new insights into pre-hospital emergency care. Low-acuity calls were not the primary driver of increased EMS utilisation in Berlin. Younger age is the strongest predictor for low-acuity calls in the model. The association with female gender is significant, while socially deprived neighbourhoods play a minor role. No statistically significant differences in call volume between densely and less densely populated regions were detected. The results can inform the EMS in future resource planning.