Survey on Hospital Queue Management using A Parallel Patient Treatment Time Prediction Algorithm


Authors : Ankita Turuk , Himanshu Bhardwaj , Vikas Kumar , Mrigakshi Devikar , Sarika Kadam

Volume/Issue : Volume 3 - 2018, Issue 1 - January

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/YnF5R7

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

A cross-sectional descriptive survey was done. Questionnaires were administered to patients United Nations agency attended the final patient department. Observations were conjointly created on the queuing model and therefore the service discipline at the clinic. Queries were meant to get demographic characteristics and therefore the time spent on the queue by patients before being seen by a doctor, time spent with the doctor, and helpful suggestions on a way to scale back the time spent on the queue. Inessential and annoying waits for long periods cause substantial human resource and time wastage and increase the frustration endured by patients. For each patient among the queue, the whole treatment time of all the patients before him is that the time that he need to wait. Queuing theory is that the mathematical approach to the analysis of waiting lines in any setting wherever arrival rate of subjects is quicker than the system will handle. It’s applicable to health care settings wherever the systems have excess capability to accommodate random variations. Therefore, we’ve a bent to propose a Patient Treatment Time Prediction (PTTP) algorithmic to predict the waiting time for every treatment task for a patient. We’ve got associate degree inclination to use realistic patient information from varied hospitals to induce a patient treatment time model for each task. Supported this large-scale, realistic data-set, the treatment time for every patient among this queue of each task is anticipated. Supported the expected waiting time, a Hospital Queuing Recommendation (HQR) system is developed. HQR calculates Associate in Nursing predicts a cheap and convenient treatment recognized taught for the patient. As results of the large-scale, realistic data-set and put together the demand for measure response, the PTTP algorithmic and HQR system mandate potency and low-latency response. Our planned model to counsel associate degree economical treatment established for patients to scale back their wait times in hospitals.

Keywords : Computer System Organization, Embedded and Cyber Secure System, Real Time System, HQR (Hospital Queue Recommendation), PTTP (Patient Treatment Time Prediction)

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