Johnson, OA, Hall, PS and Hulme, C orcid.org/0000-0003-2077-0419 (2016) NETIMIS: Dynamic Simulation of Health Economics Outcomes Using Big Data. PharmacoEconomics, 34 (2). pp. 107-114. ISSN 1170-7690
Abstract
Many healthcare organizations are now making good use of electronic health record (EHR) systems to record clinical information about their patients and the details of their healthcare. Electronic data in EHRs is generated by people engaged in complex processes within complex environments, and their human input, albeit shaped by computer systems, is compromised by many human factors. These data are potentially valuable to health economists and outcomes researchers but are sufficiently large and complex enough to be considered part of the new frontier of ‘big data’. This paper describes emerging methods that draw together data mining, process modelling, activity-based costing and dynamic simulation models. Our research infrastructure includes safe links to Leeds hospital’s EHRs with 3 million secondary and tertiary care patients. We created a multidisciplinary team of health economists, clinical specialists, and data and computer scientists, and developed a dynamic simulation tool called NETIMIS (Network Tools for Intervention Modelling with Intelligent Simulation; http://www.netimis.com) suitable for visualization of both human-designed and data-mined processes which can then be used for ‘what-if’ analysis by stakeholders interested in costing, designing and evaluating healthcare interventions. We present two examples of model development to illustrate how dynamic simulation can be informed by big data from an EHR. We found the tool provided a focal point for multidisciplinary team work to help them iteratively and collaboratively ‘deep dive’ into big data.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016, Adis &Springer. This is an author produced version of a paper published in PharmacoEconomics. Uploaded in accordance with the publisher's self-archiving policy The final publication is available at Springer via http://dx.doi.org/10.1007/s40273-016-0384-1 |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Health Sciences (Leeds) > Academic Unit of Health Economics (Leeds) |
Funding Information: | Funder Grant number National Inst for Health Research (NIHR) NIHR DEC Proj cc: 802097 |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Jun 2016 12:53 |
Last Modified: | 14 Apr 2017 03:36 |
Published Version: | http://dx.doi.org/10.1007/s40273-016-0384-1 |
Status: | Published |
Publisher: | Adis & Springer Verlag |
Identification Number: | 10.1007/s40273-016-0384-1 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:101101 |