Prediction of Patient Visit Levels Based on Type of Service at Patar Asih General Hospital Using the Monte Carlo Method

Abstract

This study aims to predict the level of patient visits at RSU Patar Asih based on the type of service provided using the Monte Carlo method. The Monte Carlo method was chosen because of its ability to handle data variability and uncertainty that often arises in the context of patient hospital visits. The data used in this study includes the number of patient visits based on the type of service at RSU Patar Asih, such as health services for pregnant women, health services for postpartum mothers, health services for newborns, health services for toddlers, health services at primary education age, health services at productive age. , health services for the elderly, health services for people with hypertension, health services for people with diabetes mellitus, health services for people with serious mental disorders (ODGJ), health services for people suspected of having tuberculosis, health services for people at risk of being infected with the human immune system (HIV)during the period 2021, 2022, 2023.The prediction results from this simulation obtained an accuracy of 81.75%, providing a fairly accurate estimate of the level of patient visits in the future. These predictions can be used by hospital management for resource planning, such as medical staff allocation, drug and medical equipment inventory management, and operational scheduling. Thus, the results of this research have the potential to improve operational efficiency and overall quality of hospital services. It is hoped that this research can contribute to more effective and efficient hospital management through data-based predictions, thereby increasing patient satisfaction and optimizing hospital resources.