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IMPACT: A Generic Tool for Modelling and Simulating Public Health Policy

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

Standard

IMPACT: A Generic Tool for Modelling and Simulating Public Health Policy. / Ainsworth, J. D.; Carruthers, E.; Couch, P. et al.
In: Methods of Information in Medicine, Vol. 50, No. 5, 2011, p. 454-463.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Ainsworth, JD, Carruthers, E, Couch, P, Green, N, O'Flaherty, M, Sperrin, M, Williams, R, Asghar, Z, Capewell, S & Buchan, IE 2011, 'IMPACT: A Generic Tool for Modelling and Simulating Public Health Policy', Methods of Information in Medicine, vol. 50, no. 5, pp. 454-463. https://doi.org/10.3414/ME11-02-0006

APA

Ainsworth, J. D., Carruthers, E., Couch, P., Green, N., O'Flaherty, M., Sperrin, M., Williams, R., Asghar, Z., Capewell, S., & Buchan, I. E. (2011). IMPACT: A Generic Tool for Modelling and Simulating Public Health Policy. Methods of Information in Medicine, 50(5), 454-463. https://doi.org/10.3414/ME11-02-0006

Vancouver

Ainsworth JD, Carruthers E, Couch P, Green N, O'Flaherty M, Sperrin M et al. IMPACT: A Generic Tool for Modelling and Simulating Public Health Policy. Methods of Information in Medicine. 2011;50(5):454-463. doi: 10.3414/ME11-02-0006

Author

Ainsworth, J. D. ; Carruthers, E. ; Couch, P. et al. / IMPACT: A Generic Tool for Modelling and Simulating Public Health Policy. In: Methods of Information in Medicine. 2011 ; Vol. 50, No. 5. pp. 454-463.

Bibtex

@article{438350dc8a0445d28004898709bd275a,
title = "IMPACT: A Generic Tool for Modelling and Simulating Public Health Policy",
abstract = "Background: Populations are under-served by local health policies and management of resources. This partly reflects a lack of realistically complex models to enable appraisal of a wide range of potential options. Rising computing power coupled with advances in machine learning and healthcare information now enables such models to be constructed and executed. However, such models are not generally accessible to public health practitioners who often lack the requisite technical knowledge or skills.Objectives: To design and develop a system for creating, executing and analysing the results of simulated public health and healthcare policy interventions, in ways that are accessible and usable by modellers and policy-makers.Methods: The system requirements were captured and analysed in parallel with the statistical method development for the simulation engine. From the resulting software requirement specification the system architecture was designed, implemented and tested. A model for Coronary Heart Disease (CHD) was created and validated against empirical data.Results: The system was successfully used to create and validate the CHD model. The initial validation results show concordance between the simulation results and the empirical data.Conclusions: We have demonstrated the ability to connect health policy-modellers and policy-makers in a unified system, thereby making population health models easier to share, maintain, reuse and deploy.",
keywords = "Decision Support, Public Health, Computer Simulation , Discrete Event Simulation , policy modelling",
author = "Ainsworth, {J. D.} and E. Carruthers and P. Couch and N. Green and M. O'Flaherty and M. Sperrin and R. Williams and Z. Asghar and S. Capewell and Buchan, {I. E.}",
year = "2011",
doi = "10.3414/ME11-02-0006",
language = "English",
volume = "50",
pages = "454--463",
journal = "Methods of Information in Medicine",
issn = "0026-1270",
publisher = "Schattauer GmbH",
number = "5",

}

RIS

TY - JOUR

T1 - IMPACT: A Generic Tool for Modelling and Simulating Public Health Policy

AU - Ainsworth, J. D.

AU - Carruthers, E.

AU - Couch, P.

AU - Green, N.

AU - O'Flaherty, M.

AU - Sperrin, M.

AU - Williams, R.

AU - Asghar, Z.

AU - Capewell, S.

AU - Buchan, I. E.

PY - 2011

Y1 - 2011

N2 - Background: Populations are under-served by local health policies and management of resources. This partly reflects a lack of realistically complex models to enable appraisal of a wide range of potential options. Rising computing power coupled with advances in machine learning and healthcare information now enables such models to be constructed and executed. However, such models are not generally accessible to public health practitioners who often lack the requisite technical knowledge or skills.Objectives: To design and develop a system for creating, executing and analysing the results of simulated public health and healthcare policy interventions, in ways that are accessible and usable by modellers and policy-makers.Methods: The system requirements were captured and analysed in parallel with the statistical method development for the simulation engine. From the resulting software requirement specification the system architecture was designed, implemented and tested. A model for Coronary Heart Disease (CHD) was created and validated against empirical data.Results: The system was successfully used to create and validate the CHD model. The initial validation results show concordance between the simulation results and the empirical data.Conclusions: We have demonstrated the ability to connect health policy-modellers and policy-makers in a unified system, thereby making population health models easier to share, maintain, reuse and deploy.

AB - Background: Populations are under-served by local health policies and management of resources. This partly reflects a lack of realistically complex models to enable appraisal of a wide range of potential options. Rising computing power coupled with advances in machine learning and healthcare information now enables such models to be constructed and executed. However, such models are not generally accessible to public health practitioners who often lack the requisite technical knowledge or skills.Objectives: To design and develop a system for creating, executing and analysing the results of simulated public health and healthcare policy interventions, in ways that are accessible and usable by modellers and policy-makers.Methods: The system requirements were captured and analysed in parallel with the statistical method development for the simulation engine. From the resulting software requirement specification the system architecture was designed, implemented and tested. A model for Coronary Heart Disease (CHD) was created and validated against empirical data.Results: The system was successfully used to create and validate the CHD model. The initial validation results show concordance between the simulation results and the empirical data.Conclusions: We have demonstrated the ability to connect health policy-modellers and policy-makers in a unified system, thereby making population health models easier to share, maintain, reuse and deploy.

KW - Decision Support

KW - Public Health

KW - Computer Simulation

KW - Discrete Event Simulation

KW - policy modelling

U2 - 10.3414/ME11-02-0006

DO - 10.3414/ME11-02-0006

M3 - Journal article

VL - 50

SP - 454

EP - 463

JO - Methods of Information in Medicine

JF - Methods of Information in Medicine

SN - 0026-1270

IS - 5

ER -