Literature DB >> 9359957

Mathematical modeling of pharmacy systems.

B S Dean1, S Gallivan, N D Barber, A Van Ackere.   

Abstract

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.

Mesh:

Year:  1997        PMID: 9359957     DOI: 10.1093/ajhp/54.21.2491

Source DB:  PubMed          Journal:  Am J Health Syst Pharm        ISSN: 1079-2082            Impact factor:   2.637


  5 in total

1.  When should pharmacists visit their wards? An application of simulation to planning hospital pharmacy services.

Authors:  B Dean; A van Ackere; S Gallivan; N Barber
Journal:  Health Care Manag Sci       Date:  1999-01

Review 2.  Modelling methods for pharmacoeconomics and health technology assessment: an overview and guide.

Authors:  James E Stahl
Journal:  Pharmacoeconomics       Date:  2008       Impact factor: 4.981

3.  Virtual epidemic in a virtual city: simulating the spread of influenza in a US metropolitan area.

Authors:  Bruce Y Lee; Virginia L Bedford; Mark S Roberts; Kathleen M Carley
Journal:  Transl Res       Date:  2008-04-03       Impact factor: 7.012

4.  Using discrete event simulation to design a more efficient hospital pharmacy for outpatients.

Authors:  Matthew Reynolds; Christos Vasilakis; Monsey McLeod; Nicholas Barber; Ann Mounsey; Sue Newton; Ann Jacklin; Bryony Dean Franklin
Journal:  Health Care Manag Sci       Date:  2011-02-23

5.  Mathematical modeling to reduce waste of compounded sterile products in hospital pharmacies.

Authors:  Vera Tilson; Gregory Dobson; Curtis E Haas; David Tilson
Journal:  Hosp Pharm       Date:  2014-07
  5 in total

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