Journal article
Building a hospital referral expert system with a Prediction and Optimization-Based Decision Support System algorithm
Journal of biomedical informatics, Vol.41(2), pp.371-386
04/2008
DOI: 10.1016/j.jbi.2007.10.002
PMID: 18054523
Abstract
This study presents a new method for constructing an expert system using a hospital referral problem as an example. Many factors, such as institutional characteristics, patient risks, traveling distance, and chances of survival and complications should be included in the hospital-selection decision. Ideally, each patient should be treated individually, with the decision process including not only their condition but also their beliefs about trade-offs among the desired hospital features. An expert system can help with this complex decision, especially when numerous factors are to be considered. We propose a new method, called the Prediction and Optimization-Based Decision Support System (PODSS) algorithm, which constructs an expert system without an explicit knowledge base. The algorithm obtains knowledge on its own by building machine learning classifiers from a collection of labeled cases. In response to a query, the algorithm gives a customized recommendation, using an optimization step to help the patient maximize the probability of achieving a desired outcome. In this case, the recommended hospital is the optimal solution that maximizes the probability of the desired outcome. With proper formulation, this expert system can combine multiple factors to give hospital-selection decision support at the individual level.
Details
- Title: Subtitle
- Building a hospital referral expert system with a Prediction and Optimization-Based Decision Support System algorithm
- Creators
- Chih-Lin Chi - Health Informatics Program, 3087 Main Library, The University of Iowa, Iowa City, IA 52242, USA. chih-lin-chi@uiowa.eduW Nick StreetMarcia M Ward
- Resource Type
- Journal article
- Publication Details
- Journal of biomedical informatics, Vol.41(2), pp.371-386
- DOI
- 10.1016/j.jbi.2007.10.002
- PMID
- 18054523
- NLM abbreviation
- J Biomed Inform
- ISSN
- 1532-0464
- eISSN
- 1532-0480
- Grant note
- R01 HS015009 / AHRQ HHS
- Language
- English
- Date published
- 04/2008
- Academic Unit
- Bus Admin College; Health Management and Policy; Nursing; Computer Science; Business Analytics
- Record Identifier
- 9984221745302771
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