Theses and Dissertations - UTB/UTPA

Date of Award


Document Type


Degree Name

Master of Science (MS)


Manufacturing Engineering

First Advisor

Dr. Miguel A. Gonzalez

Second Advisor

Dr. Douglas Timmer

Third Advisor

Dr. Zhixiang Chen


Error reduction in the performance of medical emergency situations is an area of great concern in today's society. This is specially the case when the situation involves a cardiac arrhythmia. These situations are generally categorized as Advanced Cardiac Life Support (ACLS) events. The American Heart Association provides the proper procedures that practitioners of ACLS should follow to provide care to patients presenting heart arrhythmia problems. These situations occur inside and outside the hospital, outside the hospital being the most critical ones considering the limitation of equipment and availability of qualified care. Errors made by the practitioners of ACLS in this type of situations can lead to the death of the patient or permanent disability. As errors are part of human nature, it is necessary to find some tools that can provide a good training to the practitioners to prevent the occurrence of human errors in ACLS practice. The purpose of this thesis is to develop a fuzzy based human reliability model for the performance of ACLS task. The goal of the model is to provide a means for computing performance reliability of a practitioner based on an ACLS practitioner's personal profile. Through this model an effective training and retraining configuration of ACLS can be developed to reduce error in the performance of ACLS tasks. The model also determines the probability of error that practitioners may commit while performing an ACLS task. It enables the practitioner to establish a method of training and re-training with emphasis on the areas with the highest probability of error based on the practitioner's profile.


Copyright 2003 Lucia Veronica Rosas. All Rights Reserved.

Granting Institution

University of Texas-Pan American