Queue Recommendation System for Hospital Application using Parallel Patient Treatment Time Prediction Algorithm in Big Data

Abstract

The major problems faced by hospital is patients wait delay and patient overcrowding. various examinations,
inspection or tests must be done by patient usually according to his medical conditions. Similarly, there are various
reasons for a patient to wind up his visit in hospital as soon as possible. For this an effective queue management must be
maintained which gives an ease to fast track treatment process. But, patient queue management and wait time prediction
brings challenges and complications because each patient requires different phases of treatmentand operations such as
check-up. Therefore, a Random Forest Algorithm(RFA) is used to categorize the patients on big data platform.
Furthermore, this implementation is applied to Time Prediction for each patient. This is where technology comes into
scenario developing system to overcome the queue management and providing effective patient waiting time for each
treatment using Apache Spark for real time data analysis using Spark Streaming parallel to RFA with integration of
Scala. Hospital Queueing Recommendation System (HQR) is developed for Patient Treatment Time Prediction (PTTP)