Abnormal diagnosis of Emergency Abnormal diagnosis of Emergency Department triage explored with data Department triage explored with data mining technologymining technology : An Emergency : An Emergency Department at a Medical Center in Department at a Medical Center in Taiwan taken as an exampleTaiwan taken as an example

Wen -Tsann Lin ,Shen – Tsu Wang ,Ta-Cheng ,Yu-Xin Wen -Tsann Lin ,Shen – Tsu Wang ,Ta-Cheng ,Yu-Xin Shi , Wei-yu Chen , Huei-min ChenShi , Wei-yu Chen , Huei-min Chen

Present by : Umagorn Khaosumain ;KM 6 Present by : Umagorn Khaosumain ;KM 6

TRIAGETRIAGE

Triage is used in medical Triage is used in medical emergencies, as a system to sort the emergencies, as a system to sort the injured so that the greatest number injured so that the greatest number of patients can be helped. In medical of patients can be helped. In medical emergency situations where there emergency situations where there are more injured people than there are more injured people than there are medical resources to care for are medical resources to care for them, triage allows doctors or other them, triage allows doctors or other health care professionals to decide health care professionals to decide which people can be helped the most, which people can be helped the most, and how to help them efficiently.and how to help them efficiently.

Emergency Department assessmentEmergency Department assessment Standard(1995) Standard(1995)4 Level4 Level

Level 1 : Requiring immediate treatmentLevel 1 : Requiring immediate treatment

Level 2 : To be treated in 10 minutesLevel 2 : To be treated in 10 minutes

Level 3 : To be treated in 30 minutesLevel 3 : To be treated in 30 minutes

Level 4 : Treatment can be delayedLevel 4 : Treatment can be delayed

The study is made on medical The study is made on medical management and nursing, with the management and nursing, with the knowledge of the administrative head knowledge of the administrative head at the Emergency Department ,in the at the Emergency Department ,in the hope to effectively improve hope to effectively improve consistency of triage with the consistency of triage with the combination of data mining theories combination of data mining theories and practiceand practice

The purposes are as follows :The purposes are as follows : Base on information management ,the information Base on information management ,the information

system is applied in triage of the Emergency system is applied in triage of the Emergency Department to generate patients’ dataDepartment to generate patients’ data

Exploration of correlation between triage and Exploration of correlation between triage and abnormal diagnosis ;abnormal diagnosis ;cluster analysiscluster analysis conducted on conducted on variables with clinical meaningsvariables with clinical meanings

Establishing triage abnormal diagnosis clusters with Establishing triage abnormal diagnosis clusters with hierarchical clustering (Ward ’method)hierarchical clustering (Ward ’method) and and partitioning clustering (K-means algorithm);partitioning clustering (K-means algorithm); obtaining obtaining correlation law of abnormal diagnosis with correlation law of abnormal diagnosis with decision decision treestrees

Improving consistency of triage with data mining Improving consistency of triage with data mining ;offering quantified and scientific rules for triage ;offering quantified and scientific rules for triage decision -making in the hope of serving as a decision -making in the hope of serving as a foundation for future researchers and clinical foundation for future researchers and clinical examinationexamination

Fig.1.Number of service person times in past years.Fig.1.Number of service person times in past years.source:Department of Health,2004.source:Department of Health,2004.

Fig.2.Major component factors of triageFig.2.Major component factors of triage

Parameter measurementParameter measurement

1.1. TemperatureTemperature2.2. Systolic pressureSystolic pressure3.3. Diastolic pressureDiastolic pressure4.4. RespirationRespiration5.5. PulsePulse6.6. SpO2SpO2

Fig.3.Data mining processFig.3.Data mining process

Data mining Process ModelData mining Process ModelInclude:Include:

2.2. ClassificationClassification

3.3. EstimationEstimation

4.4. PredictionPrediction

5.5. Affinity groupingAffinity grouping

6.6. ClusteringClustering

7.7. DescriptionDescription

8.8. ProfilingProfiling

Fig.4.Tendency after clusteringFig.4.Tendency after clustering

Fig.5.Triage expert system (IDEFO-AO)Fig.5.Triage expert system (IDEFO-AO)