Using Big Data to Analyze and Improve Emergency Department Efficiency: New Methods and Techniques

Author:

Ahmed Abatal1,Adil Korchi2

Affiliation:

1. Hassan Premier University

2. Chouaib Doukkali University

Abstract

Abstract Efficiency is crucial, in Emergency Departments (EDs). It can be hindered by the number of patients. In this study we present a solution that utilizes the increasing amount of healthcare data and advancements in data analysis techniques. Our approach involves a combination of LSTM and Decision Tree models to enhance the accuracy of predicting volume, in EDs. The results indicate that our model outperforms existing methods suggesting its potential to improve ED efficiency.

Publisher

Research Square Platform LLC

Reference18 articles.

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2. Elalouf A, Wachtel G (2021) December). Queueing problems in emergency departments: a review of practical approaches and research methodologies. Operations Research Forum, vol 3. Springer International Publishing, Cham, p 2. 1

3. Benefits and challenges of big data in healthcare: an overview of the european initiatives;Pastorino R;Eur J Pub Health,2019

4. Lstm model for prediction of heart failure in big data;Maragatham G;J Med Syst,2019

5. Machine learning approach on healthcare big data: a review;Supriya M;Big Data and Information Analytics,2020

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