The Effects of Computer Simulation on Reducing the Incidence of Medical Errors Associated with Mass Distribution of Chemoprophylaxis as a Result of a Bioterrorism Event

Patrick Glass, Purdue University

Abstract

The objective of research is to develop a computer simulation model to provide a means to effectively and efficiently reduce medication errors associated with points of distribution sites by identifying and manipulating screeners with a high probability of generating errors. Points of distribution sites are used to rapidly distribute chemoprophylaxis to a large population in response to a pandemic event or a bioterrorism attack. Because of the nature of the rapid response, points of distribution sites require the use of peer-trained helpers who volunteer their services. The implications are that peer-trained helpers could have a variety of experience or education levels. These factors increase the risk of medical errors. Reducing medical errors is accomplished through changing the means in which healthcare providers are trained and focusing on a team approach to healthcare delivery. Computer simulations have been used in the past to identify sources of inefficiency and potential of error. Data for the model were collected over the course of two semesters. Of the 349 data points collected from the first semester, only 137 data points were usable for the purposes of model building. When the experiment was conducted again for the second semester, similar results were found. The control simulation was run 20 times with each screener generating errors with a probability of 0.101 following a Bernoulli distribution. The variable simulation was run 30 times with each screener generating the same probability of errors; however, the researcher identified the screeners generating the errors and immediately stopped them from processing additional agents once they reached five errors. An ANOVA was conducted on the percent errors generated from each simulation run. The results of the ANOVA showed significant difference between individuals within the groups. A simulation model was built to reflect the differences in medical error rates between screeners. By comparing the results of the simulation as the screeners are manipulated in the system, the model can be used to show how medical errors can be reduced in points of distribution sites.

Degree

Ph.D.

Advisors

Dietz, Purdue University.

Subject Area

Public health|Medicine|Medical personnel|Communication|Education|Health care management|Management|Pharmaceutical sciences|Public administration

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