In health care, it is crucial to organize patient care and resources based on the urgency level so that patients whose lives are in danger are treated as a priority. This study introduces a new algorithm, created in C# using new technologies such as ChatGPT, to improve the sorting and prioritizing of patients based on the National Urgency Level. The algorithm aims to demonstrate the possibility of real-time reporting of the occupancy level of all hospitals. This way, patients can head to the nearest and most available hospital based on both proximity and urgency level. To identify the urgency level, the algorithm utilizes a widely used external service, ChatGPT. Additionally, the algorithm calculates the average waiting time based on the number of patients, their urgency level, and the number of on-duty doctors. To achieve these goals, the algorithm's implementation has been carried out using modern technologies, such as C# programming language, ranging from the artificial intelligence service ChatGPT to entity framework for managing data in the Microsoft database. The article addresses two major issues, namely text-based classification into a specific category based on common characteristics, such as a patient's symptoms concerning a specific urgency level. The second issue is represented by the proposed calculation formula for real-time estimation of waiting time, based on the identified urgency level.