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The Effective Implications On The Time Of Discharge in Modares Hospital With Data Mining Techniques. payavard. 2017; 11 (5)
URL: http://payavard.tums.ac.ir/article-1-6326-en.html

Abstract:   (117 Views)
Introduction and Purpose: Over the recent years, patient discharge process time has been an important issue focused by so many officials. Being so, the present study is aimed at identifying the main factors with regard to the discharge process and selecting the best data-mining algorithm.
Method: The population in question is all the patients discharged from Modarres Hospital during the first three months in the year 2014. Sampling wasn’t carried out but the number of observations has reached over 1060. Data was gathered via the researcher’s checklist while the relation between dependent and independent variants is examined and identified through T-test, Pearson Correlation Test and one-way analysis of variance. Employing Data Mining Algorithms, In this study, were as following: Neural Network, Support Vector Machine, Tree Decision, Simple Linear Regression.
Findings: The average discharging process in the present study is 246.76 +- 3.254 , which shows that among main factors concerned with discharging process, Admission Ward is considered as the most crucial . Also, according to the algorithms employed in this study, Tree Decision, Correlation Value=0.301, Root-Mean Square Error= 103.2927, was taken as the most useful.
Conclusion: Results show that Data-Mining Algorithms can be employed to identify crucial factors regarding the whole discharging process  and The most important factor during discharge process variable is hospitalized.
     
Type of Study: Research | Subject: Hospital Managment
Received: 2017/12/5 | Accepted: 2017/12/5 | Published: 2017/12/5

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