Building a hospital referral expert system with a Prediction and Optimization-Based Decision Support System algorithm

Chih Lin Chi, W. Nick Street, Marcia M. Ward

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)371-386
Number of pages16
JournalJournal of Biomedical Informatics
Issue number2
StatePublished - Apr 2008

Bibliographical note

Funding Information:
Analysis for this paper was partially supported by grant R01 HS015009 from the Agency for Healthcare Research and Quality.


  • Artificial intelligence
  • Data mining
  • Decision support systems
  • Expert systems
  • Hospital quality
  • Hospital referral
  • Machine learning
  • Optimization
  • Support vector machines


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