Mining Clinical Data: Selecting Decision Support Algorithm for the MET-AP System

Szymon WilkPoznan University of Technology

Ken FarionChildren’s Hospital of Eastern Ontario

Wojtek MichalowskiUniversity of Ottawa

Jerzy BlaszczynskiPoznan University of TechnologySteven RubinChildren’s Hospital of Eastern OntarioDawid WeissPoznan University of Technology

Emergency Triage Triage ≠ diagnosis

Prioritization(Triage nurse)

Medical assessment and disposition

(Physician)

ConsultObservation/

further investigationDischarge

Canadian Triage Acuity Scale (CTAS)

What clinical algorithm should be used?

Experiment Retrospective study of

the ED patients with abdominal pain (AP)

Data transcribed from the selected records

Considered algorithms Rule-based Naive Bayes Case-based Tree-based

# of records

Triage classLearning

dataTesting

data

Discharge 352 52

Observation 89 15

Consult 165 33

Total 606 100

Results

Algorithm Overall DischargeObservatio

nConsult

Rule-based 59.00% 55.80% 46.70% 69.70%

Naive Bayes 56.00% 65.40% 20.00% 57.60%

Case-based 58.00% 57.70% 20.00% 75.80%

Tree-based 57.00% 59.60% 20.00% 69.70%

Algorithm Overall DischargeObservatio

nConsult

Naive Bayes 56.00% 59.60% 46.70% 54.60%

Case-based 49.00% 42.30% 60.00% 54.60%

Tree-based 55.00% 59.60% 40.00% 54.60%

Classification accuracy

Cost-sensitive classification accuracy

AlgorithmSensitivit

ySpecificity Gain

Rule-based 0.6970 0.8060 0.5030

Naive Bayes 0.5758 0.7612 0.3370

Case-based 0.7576 0.6716 0.4292

Tree-based 0.6970 0.7015 0.3985

AlgorithmSensitivit

ySpecificity Gain

Naive Bayes 0.5455 0.8358 0.3813

Case-based 0.5455 0.8507 0.3962

Tree-based 0.5455 0.8060 0.3515

MET-AP Client-server architecture

with the embedded rule-based clinical algorithm

Verified in a clinical trial

Shell

Local database

MET Client

AP clinical algorithmHIS

Clinical alorithms

Integrator

Temporary database

MET Server

HL7

wired or wireless

communication

Physicians MET-AP

Overall 70.24% 72.21%

Discharge 71.26% 80.17%

Observation 63.93% 29.51%

Consult 70.83% 68.75%

Accuracy in the trial

Thank You

Poster #32 (gallery)

http://www.mobiledss.uottawa.ca