Handheld-Based Decision Support in Trauma Medicine

Handheld-Based Decision Support

in Trauma Medicine

Blaž Zupan

Faculty of Computer Science, University of LjubljanaBaylor College of Medicine, Houston

Examples ofMedical Decision Support• Probability of recurrence after radical

prostatectomy

• Predicting patient’s long term clinical status after hip arthroplasty

• Wrist injuries: should we operate?

Why?

• Second opinion• Systematic approach• Decision analysis

– which factors are important– how do they influence the decision

• Prognosis,• Treatment planning,• Diagnosis, ...

Why handhelds?

• Handhelds are practical• Decision support tool should be

available wherever decision takes place• They provide enough computing power

Decision Support Models

background (expert) knowledge

data(EPR, clinical data bases, ...)

statistical analysisdata mining

decisionsupportmodel

patient’s data

decision(prognosis, diagnosis, treatment plan, ...)

Sucess Story: Prostogram

• MW Kattan, P Fern: From 1999 in regular use at Memorial Sloan-Kettering Hospital and BCM

Decision Support Shellon Palm(TM)

statistical analysisdata mining

decision support modelsin XML

(synchronization)

decision support

An example ...

Aoki N. et al: Mathematical Analysis of Data from the Hanshin-Awaji Earthquake.

... An example

Current Status• Applications

– BCM & Ben Taub Hospital, Houston: traumatology

– Smrke (Clinical Center in Ljubljana, Slovenia): hip, wrist injury

– Kattan (Sloan-Kettering, NY): prostate cancer

• Methodology– Logistic regression, other methods (table

lookup, naive Bayes, survival models) coming soon

– Integration with data mining tools coming soon