Patient Treatment Time Prediction in Hospital Queuing Management

Abstract

Hospitals patient queue and its management to lower patient waits delays daily is considered as challenging tasks. Time wasting waits for long period results in to poor service and also lowers the hospitals reputation. Patient waiting for the treatment task to be completed need to wait for all the other patients who are appointed before him. This all the factors can be avoided if patient receive the updates about the queue, required time he need to wait for on his mobile phone. Understanding these problems faced by the hospitals, I proposed an individual Parallel Treatment Time Prediction (PTTP) system which will be responsible for analyzing the waiting period for every treatment activity for a patient. Here the realistic patient data from hospitals will be analyzed to calculate estimated patient treatment time for every task. The system will be responsible for getting the updates regarding huge and realtime data-set, the treatments time taken by each and patient among the list of present queue of every task is analyzed. With the successful recognition about the time taken by patient and waiting time, the Hospital Queuing Recommendation (HQR) system is implemented. HQR responsible for the suggestion about the time efficient treatment tasks for the individual. The models thus helps us to overcome the problems faced by hospitals with the help of HQRs time efficiency.