TY - JOUR
T1 - The use of discrete-event simulation modeling to compare handwritten and electronic prescribing systems
AU - Ghany, Ahmad
AU - Vassanji, Karim
AU - Kuziemsky, Craig
AU - Keshavjee, Karim
PY - 2013
Y1 - 2013
N2 - Electronic prescribing (e-prescribing) is expected to bring many benefits to Canadian healthcare, such as a reduction in errors and adverse drug reactions. As there currently is no functioning e-prescribing system in Canada that is completely electronic, we are unable to evaluate the performance of a live system. An alternative approach is to use simulation modeling for evaluation. We developed two discrete-event simulation models, one of the current handwritten prescribing system and one of a proposed e-prescribing system, to compare the performance of these two systems. We were able to compare the number of processes in each model, workflow efficiency, and the distribution of patients or prescriptions. Although we were able to compare these models to each other, using discrete-event simulation software was challenging. We were limited in the number of variables we could measure. We discovered non-linear processes and feedback loops in both models that could not be adequately represented using discrete-event simulation software. Finally, interactions between entities in both models could not be modeled using this type of software. We have come to the conclusion that a more appropriate approach to modeling both the handwritten and electronic prescribing systems would be to use a complex adaptive systems approach using agent-based modeling or systems-based modeling.
AB - Electronic prescribing (e-prescribing) is expected to bring many benefits to Canadian healthcare, such as a reduction in errors and adverse drug reactions. As there currently is no functioning e-prescribing system in Canada that is completely electronic, we are unable to evaluate the performance of a live system. An alternative approach is to use simulation modeling for evaluation. We developed two discrete-event simulation models, one of the current handwritten prescribing system and one of a proposed e-prescribing system, to compare the performance of these two systems. We were able to compare the number of processes in each model, workflow efficiency, and the distribution of patients or prescriptions. Although we were able to compare these models to each other, using discrete-event simulation software was challenging. We were limited in the number of variables we could measure. We discovered non-linear processes and feedback loops in both models that could not be adequately represented using discrete-event simulation software. Finally, interactions between entities in both models could not be modeled using this type of software. We have come to the conclusion that a more appropriate approach to modeling both the handwritten and electronic prescribing systems would be to use a complex adaptive systems approach using agent-based modeling or systems-based modeling.
KW - Agent-based Model
KW - Complex Adaptive Systems
KW - Discrete-event simulation model
KW - Electronic Prescribing
KW - Handwritten Prescribing
UR - http://www.scopus.com/inward/record.url?scp=84880159489&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-203-5-383
DO - 10.3233/978-1-61499-203-5-383
M3 - Article
C2 - 23388319
AN - SCOPUS:84880159489
SN - 0926-9630
VL - 183
SP - 383
EP - 387
JO - Studies in Health Technology and Informatics
JF - Studies in Health Technology and Informatics
ER -