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Designing the model patient: Data-driven virtual patients in medical education

Babichenko, D and Druzdzel, MJ and Grieve, L and Patel, R and Velez, J and Neal, T and McCray, J and Wallace, RD and Jenkins, S (2016) Designing the model patient: Data-driven virtual patients in medical education. In: UNSPECIFIED.

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Abstract

© 2016 IEEE. In this paper we describe ModelPatient, a software application developed to allow health sciences educators to create and deliver educational cases that are based on and simulate real patient behavior. ModelPatient uses data from Electronic Medical Record Systems (EMRS) or from publically available medical data sets in combination with Bayesian network (BN) models to generate virtual patient (VP) cases. Because the underlying models are based on real data, each decision made by a learner affects outcome probabilities. Therefore the behavior of a VP reflects how a real patient with the same medical condition would have reacted to the learners' actions. We believe that data- and model-driven approaches to creating VPs would allow educators to create higher-fidelity teaching cases and offer richer educational experience to learners.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Babichenko, D
Druzdzel, MJdruzdzel@pitt.eduDRUZDZEL
Grieve, L
Patel, R
Velez, J
Neal, T
McCray, J
Wallace, RD
Jenkins, S
Date: 7 October 2016
Date Type: Publication
Journal or Publication Title: 2016 IEEE International Conference on Serious Games and Applications for Health, SeGAH 2016
Event Type: Conference
DOI or Unique Handle: 10.1109/segah.2016.7586253
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9781509022090
Date Deposited: 19 Jul 2016 12:58
Last Modified: 14 Oct 2017 11:55
URI: http://d-scholarship.pitt.edu/id/eprint/28602

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