0096

DATA MINING THE CAPFSA RED CROSS CHILDREN’S HOSPITAL DATABASE 1991-2000 AS PART OFF INJURY PREVENTION PLANNING

AB van As, G Dragosavac#, N du Toit *,AJW Millar, H Rode

Trauma Unit, Department of Paediatric Surgery, Institute of Child Health, Red Cross War Memorial Children’s Hospital, University of Cape Town, South Africa,

*Child Accident Prevention Foundation of Southern Africa

#Mine-Max Limited

Introduction

Trauma is the leading cause of morbidity and mortality in children across the globe and a huge public health problem in South Africa. The aim of the Child Accident Prevention Foundation of Southern Africa (CAPFSA) is to reduce all intentional and un-intentional injuries of all severity through research, education, environmental change and to produce recommendations for legislation. Since 1991 we have been capturing data from all injured children treated at the Red Cross Children’s Hospital for trauma in our database. There are currently 88822 patients entered in the database.

Aims/Objectives

To study patterns and trends from all trauma patients presenting to Red Cross Children’s Hospital with the ultimate goal of accident prevention.

Materials/Methods

We explored our database with novel advanced data-mining methods (visualisation, decision trees and case-based reasoning, supplied by Mine-Max Ltd)

Results

The most common injuries were falls (n = 32766). 21,2% (n = 6953) fell from the bed, while 11.1% (n = 3.638) fell from playground equipment. From all seriously injured children 39,4% fell from the bed, while only 2.8% fell from playground equipment.

The second most common cause was traffic accidents (n = 11915). Motor vehicle accidents involving a pedestrian were the most common with 64.2% (n = 7645). Bicycle accidents were second with 15.3% (n = 1819), passenger motor vehicle accidents third with 13,7% (n = 1630).

Passenger-minibus accidents and motorcycle accidents were relatively rare (4,45 respectively 0,5%).

7241 patients presented with burns, of which 72,1% were fluid burns, 11,7% were due to flame burns. From the 54 patients presenting unconscious, 44,4% were due to flame burns.

3.302 patients presented after assault. 51,7% (n = 1709) after blunt assault, 22,3% (n = 735) were raped, 13,1% (n = 433) presented after sharp assault, while 1,2% (n = 40) were attacked with human bites. Detailed data-mining results will be discussed during the presentation.

A brief overview will be given on the various active and passive prevention strategies, that are used by CAPFSA in an attempt to prevent childhood injuries.

Conclusions

Data-mining is a powerful and promising tool in the third millennium. Close co-operation between information technologists, data-collecting clinicians and injury prevention workers could prove to be an exciting pathway in the future of injury control.