Application of data mining to the identification of critical factors in patient falls using a web-based reporting system.
OBJECTIVE
The implementation of an information system has become a trend in healthcare institutions. How to identify variables related to patient safety among accumulated data has been viewed as a main issue. The purpose of this study was to identify critical factors related to patient falls through the application of data mining to available data through a hospital information system.


METHODS
Data on a total of 725 patient falls were obtained from a web-based nursing incident reporting system at a medical center in Taiwan. In the process of data mining, feature selection was applied as the first step, after which 10 critical factors were selected to predict the dependent variables (injury versus non-injury). An artificial neural network (ANN) analysis was applied to develop a predictive model and a multivariate stepwise logistic regression was performed for comparison purposes.


RESULTS
The ANN model produced the following results: a Receiver-Operating-Character (ROC) curve indicated 77% accuracy, the positive predictive value (PPV) was 68%, and the negative predictive value (NPV) was 72%; while the multivariate stepwise logistic regression only identified 3 variables (fall assessment, anti-psychosis medication and diuretics) as significant predictors with ROC curve of 42%, PPV of 26.24%, and NPV of 87.12%.


CONCLUSIONS
In addition to medication use such as anti-psychotic and diuretics, nursing intervention where a fall assessment is conducted could represent a critical factor related to outcomes of fall incidence.
National Taipei University of Nursing and Health Sciences, Taipei 11219, Taiwan. tingting@ntunhs.edu.tw
Ting-Ting
TT
Lee
Chieh-Yu
CY
Liu
Ya-Hui
YH
Kuo
Mary Etta
ME
Mills
Jian-Guo
JG
Fong
Cheyu
C
Hung
D000058:Accidental Falls; D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D002675:Child, Preschool; D057225:Data Mining; D005260:Female; D006801:Humans; D007223:Infant; D016247:Information Storage and Retrieval; D020407:Internet; D008875:Middle Aged; D012308:Risk Management; D012449:Safety; D055815:Young Adult