A Decision Support Tool for Allocating Hospital Bed Resources and Determining Required Acuity of Care

Steven Walczak; Walter E. Pofahl; Ronald J. Scorpio

doi:10.1016/S0167-9236(02)00071-4

A Decision Support Tool for Allocating Hospital Bed Resources and Determining Required Acuity of Care

Steven Walczak, Walter E. Pofahl, Ronald J. Scorpio

University of South Florida

Research output: Contribution to journal › Article › peer-review

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).

Original language	American English
Journal	Decision Support Systems
Volume	34
DOIs	https://doi.org/10.1016/S0167-9236(02)00071-4
State	Published - Mar 1 2003

Keywords

neural networks
hospitalization
length of stay
trauma
pancreatitis
acuity of care
fuzzy ARTMAP
backpropagation

Disciplines

Business Administration, Management, and Operations
Health and Medical Administration

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10.1016/S0167-9236(02)00071-4License: CC BY

https://doi.org/10.1016/S0167-9236(02)00071-4

Cite this

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title = "A Decision Support Tool for Allocating Hospital Bed Resources and Determining Required Acuity of Care",

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).",

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AU - Pofahl, Walter E.

AU - Scorpio, Ronald J.

PY - 2003/3/1

Y1 - 2003/3/1

N2 - 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).

AB - 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).

KW - neural networks

KW - hospitalization

KW - length of stay

KW - trauma

KW - pancreatitis

KW - acuity of care

KW - fuzzy ARTMAP

KW - backpropagation

UR - https://digitalcommons.usf.edu/si_facpub/191

UR - https://doi.org/10.1016/S0167-9236(02)00071-4

U2 - 10.1016/S0167-9236(02)00071-4

DO - 10.1016/S0167-9236(02)00071-4

M3 - Article

VL - 34

JO - Decision Support Systems

JF - Decision Support Systems

ER -

A Decision Support Tool for Allocating Hospital Bed Resources and Determining Required Acuity of Care

Abstract

Keywords

Disciplines

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