Abnormal diagnosis of Emergency Abnormal diagnosis of Emergency Department triage explored with Department triage explored with data mining technologydata mining technology : An : An EmergencyEmergency Department at a Department at a Medical Center in Taiwan taken as Medical Center in Taiwan taken as an examplean 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 emergencies, as a system to sort the injured so that the greatest the injured so that the greatest number of patients can be helped. number of patients can be helped. In medical emergency situations In medical emergency situations where there are more injured where there are more injured people than there are medical people than there are medical resources to care for them, triage resources to care for them, triage allows doctors or other health care allows doctors or other health care professionals to decide which professionals to decide which people can be helped the most, 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 Level 1 : Requiring immediate treatmenttreatment

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 knowledge of the administrative head at the Emergency Department head at the Emergency Department ,in the hope to effectively improve ,in the 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 :1.1. Base on information management ,the Base on information management ,the

information system is applied in triage of the information system is applied in triage of the Emergency Department to generate patients’ Emergency Department to generate patients’ datadata

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

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

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

Fig.1.Number of service person times in past Fig.1.Number of service person times in past years.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. TemperatureTemperature

2.2. Systolic pressureSystolic pressure

3.3. Diastolic pressureDiastolic pressure

4.4. RespirationRespiration

5.5. PulsePulse

6.6. SpO2SpO2

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

Data mining Process ModelData mining Process Model

Include:Include:

1.1. ClassificationClassification

2.2. EstimationEstimation

3.3. PredictionPrediction

4.4. Affinity groupingAffinity grouping

5.5. ClusteringClustering

6.6. DescriptionDescription

7.7. ProfilingProfiling

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

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