A decision support tool for allocating hospital bed resources and determining required acuity of care

Decision Support Systems

Volumn 34, Issue 4, 2002, Pages 445-456

  Walczak, Steven ^a   Pofahl, Walter E ^b   Scorpio, Ronald J ^c  

^a UNIVERSITY OF COLORADO   (United States)

^b EAST CAROLINA UNIVERSITY   (United States)

^c Gibbs Cancer Center and Research Institute   (United States)

Author keywords

Acuity of care; Backpropagation; Fuzzy ARTMAP; Hospitalization; Length of stay; Neural networks; Pancreatitis; Trauma

Indexed keywords

FUZZY SETS; HEALTH CARE; NEURAL NETWORKS; RESOURCE ALLOCATION;

DECISION SUPPORT TOOLS;

DECISION SUPPORT SYSTEMS;

EID: 0037208450     PISSN: 01679236     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9236(02)00071-4     Document Type: Article

References (24)

1. Alpsan D., Towsey M., Ozdamar O., Tsoi A.C., Ghista D.N. Efficacy of modified backpropagation and optimization methods on a real-world medical problem. Neural Networks. 8(6):1995;945-962.
2. Barnard E., Wessels L. Extrapolation and interpolation in neural network classifiers. IEEE Control Systems. 12:1992;50-53.
3. Buchman T.G., Kubos K.L., Seidler A.J., Siegforth M.J. A comparison of statistical and connectionist models for the prediction of chronicity in a surgical intensive care unit. Critical Care Medicine. 22(5):1994;750-762.
4. Carpenter G.A., Grossberg S., Reynolds J.H. A fuzzy ARTMAP nonparametric probability estimator for nonstationary pattern recognition problems. IEEE Transactions on Neural Networks. 6:1995;1330-1336.
5. Dombi G.W., Nandi P., Saxe J.M., Ledgerwood A.M., Lucas C.E. Prediction of rib fracture injury outcome by an artificial neural network. Journal of Trauma: Injury, Infection, and Critical Care. 39(5):1995;915-921.
6. Dybowski R., Gant V. Artificial neural networks in pathology and medical laboratories. Lancet. 346:November 4, 1995;1203-1207.
7. Frye K.E., Izenberg S.D., Williams M.D., Luterman A. Simulated biologic intelligence used to predict length of stay and survival of burns. Journal of Burn Care and Rehabilitation. 17(6):1996;540-546.
8. Hornik K., Stinchcombe M., White H. Multilayer feedforward networks are universal approximators. Neural Networks. 2(5):1989;359-366.
9. Iezzoni L.I., Schwartz M., Ash A.S., Mackiernan Y.D. Does severity explain differences in hospital length of stay for pneumonia patients? Journal of Health Services Research and Policy. 1(2):1996;65-76.
10. Izenberg S.D., Williams M.D., Luterman A. Prediction of trauma mortality using a neural network. American Surgeon. 63(3):1997;275-281.
11. Lowell W.E., Davis G.E. Predicting length of stay for psychiatric diagnosis-related groups using neural networks. Journal of the American Medical Informatics Association. 1(6):1994;459-466.
12. Medsker L., Liebowitz J. Design and Development of Expert Systems and Neural Networks. 1994;Macmillan, New York.
13. Mobley B.A., Leasure R., Davidson L. Artificial neural network predictions of lengths of stay on a post-coronary care unit. Heart and Lung. 24(3):1995;251-256.
14. Montague G., Morris J. Neural-network contributions in biotechnology. Trends in Biotechnology. 12(8):1994;312-324.
15. Ranson J.H.C., Rifkind K.M., Roses D.F., Fink S.D., Eng K., Spencer F.C. Prognostic signs and the role of operative management in acute pancreatitis. Surgery, Gynecology and Obstetrics. 139:1974;69-81.
16. Ranson J.H.C. Etiological and prognostic factors in human acute pancreatitis: a review. American Journal of Gastroenterology. 77:1982;633-638.
17. Smith M. Neural Networks for Statistical Modeling. 1993;Van Nostrand-Reinhold, New York.
18. Tu J.V., Guerriere M. Use of a neural network as a predictive instrument for length of stay in the intensive care unit following cardiac surgery. Computers and Biomedical Research. 26:1993;220-229.
19. Walczak S. Neural network models for a resource allocation problem. IEEE Transactions on Systems Man and Cybernetics. 28B(2):1998;276-284.
20. Walczak S., Cerpa N. Heuristic principles for the design of artificial neural networks. Information and Software Technology. 41(2):1999;109-119.
21. Weissman C. Analyzing intensive care unit length of stay data: problems and possible solutions. Critical Care Medicine. 25(9):1997;1594-1599.
22. White H. Connectionist nonparametric regression: multilayer feedforward networks can learn arbitrary mappings. Neural Networks. 3:1990;535-549.
23. Wilson R.L., Sharda R. Bankruptcy prediction using neural networks. Decision Support Systems. 11(5):1994;545-557.
24. available at http://members.aol.com/badice98/icestromDiary/icestormtext.html, available through October 2000. (alternate page available at: http://www.usatoday.com/weather/wice98.htm).