Patient Experience Management

Abstract

Patient Experience Monitoring focuses on designing and reacting to patient experience to determine the best possible ways to provide the optimal patient satisfaction, loyalty and advocacy. The proposed research presents the idea of using RFID technology along with the patient feedback to effectively monitor and improve the patient experience at the hospital. The RFID technology help us measure the queue time and process time taken by each patient at every station and the feedback form provides us an insight about the patient’s journey at the hospital. IoTs along with machine learning algorithms are also used to capture different factors like no. of people to find out the peak hours, the voice of staff at reception desk to determine the behavior of staff with patients and to check the camera footage can be used find out if the hospital environment is clean or not. The results of these machine learning algorithms show that which department needs more attention in which aspects in providing better services to the patient. All these results are then displayed using a dashboard that operates in real-time and highlights the performance of the individual departments as well as all the doctors and staff working in those departments, which helps the hospital management easily monitor the performance and make improvements where needed. We’ve also sufficiently reduced the process and queue time by automating the conventional hospital processes like registration, appointments and payment using our apps and self-service kiosk. The application provided to patients can be used to register patients online, take appointments beforehand, find a suitable doctor, find respective department according to common symptoms and look for hospital indoor maps etc. Additional features like self-service kiosk, automated tokens and a people counter also help make patient experience better