title: Length of Hospital Stay Prediction at the Admission Stage for Cardiology Patients Using Artificial Neural Network.
abstract: For hospitals' admission management, the ability to predict length of stay (LOS) as early as in the preadmission stage might be helpful to monitor the quality of inpatient care. This study is to develop artificial neural network (ANN) models to predict LOS for inpatients with one of the three primary diagnoses: coronary atherosclerosis (CAS), heart failure (HF), and acute myocardial infarction (AMI) in a cardiovascular unit in a Christian hospital in Taipei, Taiwan. A total of 2,377 cardiology patients discharged between October 1, 2010, and December 31, 2011, were analyzed. Using ANN or linear regression model was able to predict correctly for 88.07% to 89.95% CAS patients at the predischarge stage and for 88.31% to 91.53% at the preadmission stage. For AMI or HF patients, the accuracy ranged from 64.12% to 66.78% at the predischarge stage and 63.69% to 67.47% at the preadmission stage when a tolerance of 2 days was allowed.
authors.affiliation: Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 10608, Taiwan.
authors.forename: Pei-Fang Jennifer
authors.initials: PF
authors.lastname: Tsai
authors.affiliation: Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 10608, Taiwan.
authors.forename: Po-Chia
authors.initials: PC
authors.lastname: Chen
authors.affiliation: Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 10608, Taiwan.
authors.forename: Yen-You
authors.initials: YY
authors.lastname: Chen
authors.affiliation: Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 10608, Taiwan.
authors.forename: Hao-Yuan
authors.initials: HY
authors.lastname: Song
authors.affiliation: Division of Health Insurance, Mackay Memorial Hospital, Taipei 10449, Taiwan.
authors.forename: Hsiu-Mei
authors.initials: HM
authors.lastname: Lin
authors.affiliation: Medical Affairs Department, Mackay Memorial Hospital, Taipei 10449, Taiwan.
authors.forename: Fu-Man
authors.initials: FM
authors.lastname: Lin
authors.affiliation: Registration and Admitting, Mackay Memorial Hospital, Taipei 10449, Taiwan.
authors.forename: Qiou-Pieng
authors.initials: QP
authors.lastname: Huang
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003324:Coronary Artery Disease / Q000175:diagnosis*; D006333:Heart Failure / Q000175:diagnosis*; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000175:diagnosis*; D016571:Neural Networks, Computer; D010343:Patient Admission / Q000706:statistics & numerical data*; D011237:Predictive Value of Tests; D013624:Taiwan; D016896:Treatment Outcome; D055815:Young Adult