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Prioritization of congenital cardiac surgical patients using fuzzy reasoning – a solution to the problem of the waiting list?

Published online by Cambridge University Press:  26 May 2006

Ralf Holzer ,
Ed Ladusans ,
Denise Kitchiner ,
Ian Peart ,
Gordon Gladman  and
Gail Miles
Ralf Holzer
Affiliation:
Department of Cardiology and Cardiac Surgery, Royal Liverpool Children's NHS Trust, Liverpool, United Kingdom
Ed Ladusans
Affiliation:
Department of Cardiology and Cardiac Surgery, Royal Liverpool Children's NHS Trust, Liverpool, United Kingdom
Denise Kitchiner
Affiliation:
Department of Cardiology and Cardiac Surgery, Royal Liverpool Children's NHS Trust, Liverpool, United Kingdom
Ian Peart
Affiliation:
Department of Cardiology and Cardiac Surgery, Royal Liverpool Children's NHS Trust, Liverpool, United Kingdom
Gordon Gladman
Affiliation:
Department of Cardiology and Cardiac Surgery, Royal Liverpool Children's NHS Trust, Liverpool, United Kingdom
Gail Miles
Affiliation:
Department of Computer Science, Lenoir-Rhyne College, North Carolina, United States of America and University of Liverpool, United Kingdom
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Abstract

Surgical waiting lists are of high importance in countries, where the national health system is unable to deliver surgical services at a rate that would allow patients to avoid unnecessary periods of waiting. Prioritization of these lists, however, is frequently arbitrary and inconsistent.

The objective of our research was to analyze the medical decision-making process when prioritizing patients with congenital cardiac malformations for cardiac surgical procedures, identifying an appropriate representation of knowledge, and transferring this knowledge onto the design and implementation of an expert system (“PrioHeart”).

The medical decision-making process was stratified into three stages. The first was to analyze the details of the procedure and patient to define important impact factors on clinical priority, such as the risk of adverse events. The second step was to evaluate these impact factors to define an appropriate “timing category” within which a procedure should be performed. The third, and final, step was to re-evaluate the characteristics of individual patients to differentiate between those in the same timing category.

We implemented this decision-making process using a rule-based production system with support for fuzzy sets, using the FuzzyCLIPS inference engine and expert system shell as a suitable development environment for the knowledge base.

The “PrioHeart” expert system was developed to give paediatric cardiologists a tool to allow and facilitate the prioritization of patients on the cardiosurgical waiting list. Evaluation of “PrioHeart” on limited sets of patients documented appropriate results of prioritization, with a significant correlation between the prioritization made using “PrioHeart” and those results obtained by the individual consultant specialist.

We conclude that our study has demonstrated the feasibility of using an expert system approach with a fuzzy, rule-based production system to implement the prioritization of cardiac surgical patients. The approach may potentially be transferable to other medical subspecialities.

Keywords

Heart defectscongenitalexpert systemsmanagement
Type
Original Article
Information
Cardiology in the Young , Volume 16 , Issue 3 , June 2006 , pp. 289 - 299
Copyright
© 2006 Cambridge University Press

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