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A fuzzy inference system for prevent...

Beechner, Paul Martin.

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A fuzzy inference system for preventing ambulance diversion in emergency departments.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	A fuzzy inference system for preventing ambulance diversion in emergency departments./
Author:	Beechner, Paul Martin.
Description:	145 p.
Notes:	Source: Masters Abstracts International, Volume: 52-02.
Contained By:	Masters Abstracts International52-02(E).
Subject:	Engineering, Industrial. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1543602
ISBN:	9781303309748

A fuzzy inference system for preventing ambulance diversion in emergency departments.
Beechner, Paul Martin.

A fuzzy inference system for preventing ambulance diversion in emergency departments. - 145 p.

Source: Masters Abstracts International, Volume: 52-02.

Thesis (M.S.)--State University of New York at Binghamton, 2013.

The hospital emergency department (ED) is an extremely important area of the hospital and serves a diverse patient population. The population that utilizes the ED is of varying acuity levels, varying illnesses, different demographics, and different ages. The objective of this research is to construct a fuzzy inference system that performs as a decision support system to eliminate ambulance diversion in the ED. This system takes information or input factors from the ED and recommends a certain percentage of lower acuity patients to divert from the ED to outpatient clinics or primary care physicians. The systems were validated against the baseline values for need for diversion and the error was calculated. The queue network performed much better than the simulation model fuzzy inference system when MSE was compared. The error for the queue network FIS was relatively low and it performed well across most of the data range.

ISBN: 9781303309748Subjects--Topical Terms:

626639
Engineering, Industrial.

A fuzzy inference system for preventing ambulance diversion in emergency departments.
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005 20140624205951.5
008 150210s2013 ||||||||||||||||| ||eng d
020 $a 9781303309748
035 $a (MiAaPQ)AAI1543602
035 $a AAI1543602
040 $a MiAaPQ $c MiAaPQ
100 1 $a Beechner, Paul Martin. $3 2096395
245 1 2 $a A fuzzy inference system for preventing ambulance diversion in emergency departments.
300 $a 145 p.
500 $a Source: Masters Abstracts International, Volume: 52-02.
500 $a Adviser: Mohammad T. Khasawneh.
502 $a Thesis (M.S.)--State University of New York at Binghamton, 2013.
520 $a The hospital emergency department (ED) is an extremely important area of the hospital and serves a diverse patient population. The population that utilizes the ED is of varying acuity levels, varying illnesses, different demographics, and different ages. The objective of this research is to construct a fuzzy inference system that performs as a decision support system to eliminate ambulance diversion in the ED. This system takes information or input factors from the ED and recommends a certain percentage of lower acuity patients to divert from the ED to outpatient clinics or primary care physicians. The systems were validated against the baseline values for need for diversion and the error was calculated. The queue network performed much better than the simulation model fuzzy inference system when MSE was compared. The error for the queue network FIS was relatively low and it performed well across most of the data range.
590 $a School code: 0792.
650 4 $a Engineering, Industrial. $3 626639
650 4 $a Health Sciences, Health Care Management. $3 1017922
650 4 $a Engineering, System Science. $3 1018128
690 $a 0546
690 $a 0769
690 $a 0790
710 2 $a State University of New York at Binghamton. $b Industrial and Systems Engineering. $3 2096396
773 0 $t Masters Abstracts International $g 52-02(E).
790 $a 0792
791 $a M.S.
792 $a 2013
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1543602