Paper Details

Effective patient queue management to reduce patient wait delays and patient overcrowding is one in all themost challenges featured by hospitals. Inessential and annoying waits for long periods result in substantial humanresource and time wastage and increase the frustration endured by patients. for every patient among the queue, thewhole treatment time of all the patients before him is that the time that he should wait. it would be convenient anddesirable if the patients might receive the foremost efficient treatment organize and understand the expected waiting timethrough a mobile application that updates in real time. Therefore, we've a bent to propose a Patient Treatment TimePrediction (PTTP) algorithmic to predict the waiting time for each treatment task for a patient. We've a tendency to userealistic patient data from varied hospitals to induce a patient treatment time model for every task. Supported this largescale, realistic data-set, the treatment time for each patient among the present queue of every task is predicted.Supported the expected waiting time, a Hospital Queuing Recommendation (HQR) system is developed. HQR calculatesAssociate in Nursing predicts an economical and convenient treatment started suggested for the patient. As a result of thelarge-scale, realistic data-set and also the demand for time period response, the PTTP algorithmic and HQR systemmandate efficiency and low-latency response. Our proposed model to recommend an efficient treatment set up forpatients to reduce their wait times in hospitals.

Poonam Dumbre, Trushali Sandbhor, Priya Dhumal, Satyabhama Mane, Prof. Anuja Bharate, “PARALLEL PATIENT TREATMENT TIME PREDICTION USING EFFECTIVE HOSPITAL QUEUING-RECOMMENDATION SYSTEM”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 5, Issue 5, pp. 535-539, May 2018.