|
KMID : 0926620030080010081
|
|
Korean Journal of Hospital Management
2003 Volume.8 No. 1 p.81 ~ p.94
|
|
|
A Neural Network for Prediction and Sensitivity of Outpatients` Satisfaction
|
|
Lee Kyun-Jick
Chung Young-Chul
Kim Mi-Ra
|
|
|
Abstract
|
|
|
|
This paper aims at developing a prediction model and analyzing a sensitivity for the outpatient’s overall satisfaction on utilizing hospital services by using data mining techniques within the context of customer satisfaction. From a total of 900 outpatient cases, 80 percent were randomly selected as the training group and the other 20 percent as the validation group. Cases in the training group were used in the development of the CHAID and Neural Networks. The validation group was used to test the performance of these models. The major findings may be summarized as follows: the CHAID provided six useful predictors - satisfaction with treatment level, satisfaction with healthcare facilities and equipments, satisfaction with registration service, awareness of hospital reputation, satisfaction with staffs courtesy and responsiveness, and satisfaction with nurses kindness. The prediction accuracy rates based on MLP (77.90%) is superior to RBF (76.80%).
|
|
|
KEYWORD
|
|
|
neural network, patient satisfaction, sensitivity analysis, CHAID
|
|
|
FullTexts / Linksout information
|
|
|
|
|
|
Listed journal information
|
|
 
|