Objective To explore an economical and effective screening method of diabetes suitable for application in community.
Methods Based on an epidemiological survey of diabetes mellitus in the community populalion aged above 40 who have no diabetes history in Minhang District of Shanghai in 2007, risk factors scoring model and BP artificial neural network model were established to evaluate the efficiency and economic benefits of the screening method.The original data was divided into training group(1 970 cases)and testing group(1 977 cases). The two models were developed based on training group and the validity and reliability of the models were validated and compared based on the testing group.
Results Taking the risk factors score 27 as the threshold value, the sensitivity and specificity of risk factors scoring model were 63.64% and 72.28% respectively. Taking the network output value 0.16 as the threshold value, the sensitivity and specificity of BP artificial neural network model were 63.64% and 63.60% respectively. The direct medical cost per case of risk factors scoring model was 24.29 yuan, whereas the cost of BP artificial neural network model was 27.04 yuan.
Conclusion The screening effect between risk factors scoring model and BP artificial neural network model was not significantly different. Compared with risk factors scoring model, the cost of BP artificial neural network model was 11.32% higher. Risk factors scoring model was easier to operate and might become a routine diabetes screening method for practice in community.
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