Patient Queue Systems in Hospital Using Patient Treatment Time Prediction Algorithm

Abstract

Patient Treatment Time Prediction Algorithm was very important to build an outpatient queue system at the hospital. This study aims to build a system of outpatient queues to predict the waiting time of outpatients in the eye clinic at one of Cirebon hospitals. Patient Treatment Time Prediction algorithm was calculated based on historical data or medical records of patients in the hospital with 120 patient data. The Patient Treatment Time Prediction algorithm was trained by improved Random Forest algorithm for each service and a waiting time for each service. Prediction of waiting time for each patient service was obtained by calculating the consumption of patient care time based on patient characteristics. The waiting time for each service predicted by the trained Patient Treatment Time Prediction algorithm is the total waiting time of patients in the queue for each service. This research resulted in a system that can show the time taken by patients in every service available in the eye clinic. Patient time consumption in each service produced varies according to the patient's condition, in this case based on the patient's gender and age. This research provides benefits in terms of improving performance in each department involved, optimizing human resources, and increasing patient satisfaction. This research can be developed for each department in the hospital.