Mathematical modelling of Pharmacy Systems

Détails

ID Serval
serval:BIB_05C1C180561A
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Mathematical modelling of Pharmacy Systems
Périodique
The American Journal of Health-System Pharmacy
Auteur(s)
van Ackere A., Dean B., Barber N., Gallivan S.
ISSN
1079-2082
Statut éditorial
Publié
Date de publication
1997
Peer-reviewed
Oui
Volume
54
Numéro
21
Pages
2491-2499
Langue
anglais
Résumé
Mathematical modeling and its potential applications in pharmacy are discussed.
A model is a simplified representation of the real world. As an experimental approach, modeling minimizes expense, risk, and disruption, but its validity can be hard to ascertain. Mathematical models describe numerically the relationships among elements of a system and are a powerful tool in making decisions affecting that system. There are two types of mathematical models: analytical models, which directly describe the relationships between system inputs and outputs using mathematical equations (such as pharmacokinetic models), and simulation models, which involve the replication, usually with a computer, of events as they occur in the real world. Analytical models are easier to develop but are not appropriate for describing highly complex systems. In continuous-time simulation, the system is represented as an uninterrupted flow of material; in discrete-event simulation, it is assumed that events occur only at distinct times. Various simulation programs are commercially available. The stages of a mathematical modeling study are (1) formulate the problem, (2) determine the model's structure, (3) collect and analyze initial data, (4) develop the model further, (5) validate the model, (6) experiment using the model, and (7) use the results. There have been many applications of modeling in health care, but relatively few have involved the study of pharmacy systems.
Mathematical modeling offers pharmacists a low-risk, low-cost tool for aiding decisions about pharmacy systems by predicting alternative futures.
Mots-clé
administration, computers, decisionmaking, mathematics, methodology, models, pharmacy, institutional, hospital
Pubmed
Création de la notice
02/06/2009 14:07
Dernière modification de la notice
20/08/2019 12:27
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