Grey relational and partial least squares regression analysis on the hospitalization expenses * / 重庆医学

ABSTRACT

Objective To combine grey relation analysis and partial least squares regression model to establish the forecasting model of per-patient hospitalization expenses .Methods Gray relational analysis was used to filter out the main factors affecting per-patient hospitalization expenses ,and then collinearity was examined between these factors .Partial least squares regression was used to establish prediction model of per-patient hospitalization expenses ,and the prediction accuracy was proved .Results After filtered by gray relational analysis ,the order of the importance of factors affecting per-patient hospitalization expenses was the west-ern medicine fee ,traditional Chinese medicine fees ,diagnosis and treat fees ,other fees ,inspection fees ,bed fees and operation fees . The established partial least squares regression model had a higher accuracy on fitting and prediction ,with low average relative er-ror ,respectively ,-0 .000 2% and 0 .349 3% .Conclusion The gray relational analysis and partial least squares regression are suit-able for the influencing factors and prediction analysis of hospitalization costs .It provides a reference for data with the small sample size and high collinearity between the variables .