IMPACT: a generic tool for modelling and simulating public health policy

Ainsworth, J. D. and Carruthers, E. and Crouch, P. and Green, N. and O'Flaherty, M. and Sperrin, M. and Williams, R. and Asghar, Zahid and Capewell, S. and Buchan, I. E. (2011) IMPACT: a generic tool for modelling and simulating public health policy. Methods of Information in Medicine, 50 (5). pp. 454-463. ISSN 0026-1270

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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.

Item Type: Article
Keywords: Mathematical Modelling, public health policy, population based intervention, discrete event simulation, decision support, policy modelling, computer simulation, ref03, refdoi
Subjects: G Mathematical and Computer Sciences > G330 Stochastic Processes
G Mathematical and Computer Sciences > G150 Mathematical Modelling
G Mathematical and Computer Sciences > G200 Operational Research
A Medicine and Dentistry > A300 Clinical Medicine
G Mathematical and Computer Sciences > G300 Statistics
G Mathematical and Computer Sciences > G340 Statistical Modelling
G Mathematical and Computer Sciences > G320 Probability
G Mathematical and Computer Sciences > G350 Mathematical Statistics
G Mathematical and Computer Sciences > G311 Medical Statistics
B Subjects allied to Medicine > B810 Cardiography
Divisions: College of Social Sciences > Faculty of Health & Social Sciences > Lincoln School of Health & Social Care
Depositing User: Zahid Asghar
Date Deposited: 23 Mar 2012 17:38
Last Modified: 08 May 2013 13:58
URI: http://eprints.lincoln.ac.uk/id/eprint/4962

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