DYNAMIC BIOPSYCHOSOCIAL PRIORITIZATION STRATEGY FOR ELECTIVE SURGERIES IN HIGH-COMPLEXITY PUBLIC HOSPITALS: A SIMULATION-BASED STUDY(STEPS TO STRENGTHEN REGIONAL COOPERATION IN AN EMERGENCY SITUATION)

Research Background: Long waiting lists for elective surgeries in public health systems represent a critical challenge. In Chile, there are high-complexity hospitals (HCPH) that provide coverage to the entire population. Patients on waiting lists for surgeries not covered by explicit health guarantees (GES) are particularly affected due to the lack of prioritization frameworks that consider factors beyond time or urgency. Purpose of the article: The aim of this article is to develop a hybrid prioritization model for elective surgery patients without GES in the Otorhinolaryngology (ENT) Department of a high-complexity public hospital (HCPH) in Chile. Methods: The model consists of 13 clinical and 7 psychosocial variables, weighted using expert judgment (ENT specialists) to construct a total prioritization score. Furthermore, using a stochastic simulation of 1,000 patients, we observed a concrete result: a 6.6% reduction in the number of patients who exceeded their maximum safe wait time, compared with the FIFO strategy currently implemented. Findings and added value: Our study adds value by proposing a hybrid prioritization strategy. Unlike traditional approaches based solely on time or urgency, our model integrates biopsychosocial variables and, more importantly, incorporates a dynamic vulnerability factor that adjusts prioritization based on changes in wait time and cumulative urgency. All of this has been validated by a team of medical experts. Although not yet implemented in practice, our model has great potential by providing a prioritization score for each patient, enabling the ward's medical team to make decisions about surgical scheduling, improving equity, and reducing preventable harm.