Pre-triage decision support improvement in maternity care by means of data mining

A triage system aims to make a correct characterization of the condition of patients. Because conventional triage systems like Manchester Triage System (MTS) are not suitable for maternity care, a decision model for pre-triaging patients in emergency (URG) and consultation (ARGO) classes was built a...

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Bibliographic Details
Main Author: Pereira, Eliane (author)
Other Authors: Brandão, Andreia (author), Salazar, Maria (author), Portela, Filipe (author), Santos, Manuel (author), Machado, José Manuel (author), Abelha, António (author)
Format: bookPart
Language:eng
Published: 2015
Subjects:
Triage
Decision support
Maternity care
Data mining
Social Sciences
Online Access:http://hdl.handle.net/1822/31201
Country:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/31201
Description
Summary:A triage system aims to make a correct characterization of the condition of patients. Because conventional triage systems like Manchester Triage System (MTS) are not suitable for maternity care, a decision model for pre-triaging patients in emergency (URG) and consultation (ARGO) classes was built and incorporated into a Decision Support System (DSS) implemented in Centro Materno Infantil do Norte (CMIN). Complementarily, DSS produces several indicators to support clinical and management decisions. A recent data analysis revealed a bias in the classification of URG cases. Frequently, cases classified as URG correspond to ARGO. This misclassification has been studied by means of Data Mining (DM) techniques in order to improve the pre-triage model and to discover knowledge for developing a new triage system based on waiting times and on a 5-scale of classes. This chapter presents a kind of sensitivity analysis combining input variables in six scenarios and considering four different DM techniques. CRISP-DM methodology was used to conduct the project.

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