Using discrete-event simulation to increase the efficiency of point of distribution sites
DOI:
https://doi.org/10.5055/jem.2018.0378Keywords:
point of distribution site, computer simulation modeling, discrete-event simulationAbstract
Objective: The objective of this research was to develop a computer simulation model that will provide the most optimal allocation of resources for a point of distribution (POD) site.
Design: A baseline assessment was conducted by participants establishing POD sections with no guidance from the investigator. A computer model was built with four stations: triage, registration, screening, and dispensing. The information from the computer simulation was used to design the allocation of volunteers for the experimental group. Once the data were collected, a two-sample t test was used to determine the significance of the difference between the average times of the two groups to complete the POD.
Setting: The POD site was conducted indoors with volunteers acting as patients, and volunteer nursing students, and pharmacy students acting as POD workers. Volunteers were divided into two groups, group B, experimental and group A, control. Time was recorded using a digital time-stamp at the beginning and at the end of the POD.
Interventions: The researcher inputted the total number of volunteers into the model, and the model generated the most applicable ratio for distribution of human capital: a one-to-one ratio of screeners to dispensers.
Main outcome measures: The mean time for Group A was 4.55 minutes (95% CI: 4.27, 4.83). The mean time for group B was 3.05 minutes (95% CI: 2.79, 3.31). A two-sample t test and Analysis of Variance of these data show that the difference is meaningful (p < 0.001).
Results: The results show that a discrete-event computer simulation can be used to identify the most efficient use of resources in order to decrease the amount of time that patients are required to participate.
Conclusions: The discrete-event computer simulation model was found to be effective at identifying ways to increase efficiency and reduce the overall time required by patients to complete the POD.
References
Landesman LY: Public Health Management of Disasters: The Practice Guide. 3rd ed. Washington, DC: American Public Health Association, 2012.
Ablah E, Scanlon E, Konda K, et al.: A large-scale points-of-dispensing exercise for first responders and first receivers in Nassau County, New York. Biosecur Bioterror. 2010; 8: 25-35.
Glass P, Dietz JE , Aaltonen P, et al.: Using Discrete-Event Simulation to Reduce the Incidence of Medical Errors from a Point of Distribution Site [MS thesis]. West Lafayette, IN: Purdue University, 2017.
Robinson S: Simulation. New York: Wiley, 2004.
Hupert N, Mushlin AI, Callahan MA: Modeling the public health response to bioterrorism: Using discrete event simulation to design antibiotic distribution centers. Med Decis Making. 2002; 22(s5): S17-S25. doi:10.1177/027298902237709.
Vesna B, Bec´irevic´-Lac´an M, Bozikov V, et al.: Prescribing medication errors in hospitalised patients: A prospective study. Acta Pharm. 2005; 55(2): 157-167. Available at http://www.scopus.com/inward/record.url?eid=2-s2.0-22244456752&partnerID=40&md5=05dd3299f15d4fb0d574eded2e3c5a5b. Accessed September 15, 2016.
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