Improving efficiency in the emergency department Monte Carlo simulation for determining the optimal number of staff

Abstract

This paper examines the application of Monte Carlo simulation to determine optimal staffing levels at reception desks in the Emergency Department. The study utilizes data collected from a hospital in Bogotá, with all data anonymized to maintain the confidentiality of both the institution and its patients. By leveraging programming tools, the study randomizes the data and models various scenarios to assess the staffing requirements accurately. The primary goal is to enhance the efficiency and quality of service by aligning staffing levels with patient demand. The use of historical data, combined with the simulation of hypothetical scenarios, provides a robust basis for predicting future needs and making informed staffing decisions. The study's findings offer valuable insights into human resources management, enabling the Emergency Department to strategically allocate personnel, minimize wait times, and improve overall patient care. This approach demonstrates the potential for simulation-based models to optimize resource allocation in critical healthcare environments.