A Decision Support Tool for Allocating Hospital Bed Resources and Determining Required Acuity of Care
Document Type
Article
Publication Date
3-2003
Keywords
neural networks, hospitalization, length of stay, trauma, pancreatitis, acuity of care, fuzzy ARTMAP, backpropagation
Digital Object Identifier (DOI)
https://doi.org/10.1016/S0167-9236(02)00071-4
Abstract
Limitations in health care funding require physicians and hospitals to find effective ways to utilize resources. Neural networks provide a method for predicting resource utilization of costly resources used for prolonged periods of time. Injury severity knowledge is used to determine the acuity of care required for each patient and length of stay is used to determine duration of inpatient hospitalization. Neural networks perform well on these medical domain problems, predicting total length of stay within 3 days for pediatric trauma (population mean and S.D. 4.37±45.12) and within 4 days for acute pancreatitis patients (7.75±79.19).
Was this content written or created while at USF?
No
Citation / Publisher Attribution
Decision Support Systems, v. 34, issue 4, p. 445-456
Scholar Commons Citation
Walczak, Steven; Pofahl, Walter E.; and Scorpio, Ronald J., "A Decision Support Tool for Allocating Hospital Bed Resources and Determining Required Acuity of Care" (2003). School of Information Faculty Publications. 191.
https://digitalcommons.usf.edu/si_facpub/191
