Modeling daily patient arrivals at Emergency Department and quantifying the relative importance of contributing variables using artificial neural network

Decision Support Systems

Volumn 54, Issue 3, 2013, Pages 1488-1498

  Xu, M ^a   Wong, T C ^a   Chin, K S ^a  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

Artificial neural network; Emergency Department; Multiple linear regression; Patient arrival; Relative importance

Indexed keywords

COMPLEX SYSTEM MODELING; COMPREHENSIVE COMPARISONS; EMERGENCY DEPARTMENTS; MULTIPLE LINEAR REGRESSIONS; NON-LINEAR LEAST SQUARES; PATIENT ARRIVAL; RELATIVE IMPORTANCE; STRATEGIC DECISION MAKING;

EMERGENCY ROOMS; HEALTH CARE; LINEAR REGRESSION;

NEURAL NETWORKS;

EID: 84875413164     PISSN: 01679236     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.dss.2012.12.019     Document Type: Article

References (60)

1. R.E. Abdel-Aal Univariate modeling and forecasting of monthly energy demand time series using abductive and neural networks Computers and Industrial Engineering 54 2008 903 917 (Pubitemid 351458387)
2. M.A. Ahmed, and T.M. Alkhamis Simulation optimization for an emergency department healthcare unit in Kuwait European Journal of Operational Research 198 2009 936 942
3. S. Aldor-Noiman, P.D. Feigin, and A. Mandelbaum Workload forecasting for a call center: methodology and a case study The Annals of Applied Statistics 3 2009 1403 1447
4. B.R. Asplin, D.J. Magid, K.V. Rhodes, L.I. Solberg, N. Lurie, and C.A. Camargo Jr. A conceptual model of emergency department crowding Annals of Emergency Medicine 42 2003 173 180 (Pubitemid 36899784)
5. B.R. Asplin, T.J. Flottemesch, and B.D. Gordon Developing models for patient flow and daily surge capacity research Academic Emergency Medicine 13 2006 1109 1113 (Pubitemid 44642348)
6. K.F. Au, T.M. Choi, and Y. Yu Fashion retail forecasting by evolutionary neural networks International Journal of Production Economics 114 2008 615 630
7. H. Batal, J. Tench, S. McMillan, J. Adams, and P.S. Mehler Predicting patient visits to an urgent care clinic using calendar variables Academic Emergency Medicine 8 2001 45 53
8. W.G. Baxt, F.S. Shofer, F.D. Sites, and J.E. Hollander A neural network aid for the early diagnosis of cardiac ischemia in patients presenting to the emergency department with chest pain Annals of Emergency Medicine 40 2002 575 583 (Pubitemid 35417479)
9. W.G. Baxt, F.S. Shofer, F.D. Sites, and J.E. Hollander A neural computational aid to the diagnosis of acute myocardial infarction Annals of Emergency Medicine 39 2002 366 373 (Pubitemid 34263489)
10. L. Bianchi, J. Jarrett, and R. Choudary Hanumara Improving forecasting for telemarketing centers by ARIMA modeling with intervention International Journal of Forecasting 14 1998 497 504 (Pubitemid 128340123)
11. C.M. Bishop Neural Networks for Pattern Recognition 1995 Clarendon Press Oxford
12. R. Champion, L.D. Kinsman, G.A. Lee, K.A. Masman, E.A. May, M.D. Taylor, P.R. Thomas, and R.J. Williams Forecasting emergency department presentations Austrian Health Review 31 2007 83 90
13. N. Channouf, P. L'Ecuyer, A. Ingolfsson, and A. Avramidis The application of forecasting techniques to modeling emergency medicine system calls in Calgary, Alberta Health Care Management Science 10 2007 25 45
14. Y.C. Chao, Y. Zhao, L.L. Kupper, and L.A. Nylander-French Quantifying the relative importance of predictors in multiple linear regression analyses for public health studies Journal of Occupational and Environmental Hygiene 5 2008 519 529 (Pubitemid 351882407)
15. K.Y. Chen Combining linear and nonlinear model in forecasting tourism demand Expert Systems with Applications 38 2011 10368 10376
16. M.S. Chen, L.C. Ying, and M.C. Pan Forecasting tourist arrivals by using the adaptive network-based fuzzy inference system Expert Systems with Applications 37 2010 1185 1191
17. C.H. Cheng, J.W. Wang, and C.H. Li Forecasting the number of outpatient visits using a new fuzzy time series based on weighted-transitional matrix Expert Systems with Applications 34 2008 2568 2575
18. C.W. Chu, and G.P. Zhang A comparative study of linear and nonlinear models for aggregate retail sales forecasting International Journal of Production Economics 86 2003 217 231
19. H.C. Co, and R. Boosarawongse Forecasting Thailand's rice export: statistical techniques vs. artificial neural networks Computers and Industrial Engineering 53 2007 610 627 (Pubitemid 47588647)
20. T.J. Flottemesch, B.D. Gordon, and S.S. Jones Advanced statistics: developing a formal model of emergency department census and defining operational efficiency Academic Emergency Medicine 14 2007 799 809 (Pubitemid 47277430)
21. G.D. Garson Interpreting neural-network connection weights AI Expert 6 1991 47 51
22. M. Gevrey, I. Dimopoulos, and S. Lek Review and comparison of methods to study the contribution of variables in artificial neural network models Ecological Modelling 160 2003 249 264 (Pubitemid 36251040)
23. E. González-Romera, M.A. Jaramillo-Morán, and D. Carmona-Fernández Forecasting of the electric energy demand trend and monthly fluctuation with neural networks Computers and Industrial Engineering 52 2007 336 343 (Pubitemid 46412646)
24. L.V. Green, P.J. Kolesar, and W. Whitt Coping with time-varying demand when setting staffing requirements for a service system Production and Operations Management 16 2007 13 39
25. U. Grömping Relative importance for linear regression in R: the package relaimpo Journal of Statistical Software 17 2006
26. R.F. Harrison, and R.L. Kennedy Artificial neural network models for prediction of acute coronary syndromes using clinical data from the time of presentation Annals of Emergency Medicine 46 2005 431 439 (Pubitemid 41552393)
27. J.E. Hollander, K.L. Sease, D.M. Sparano, F.D. Sites, F.S. Shofer, and W.G. Baxt Effects of neural network feedback to physicians on admit/discharge decision for emergency department patients with chest pain Annals of Emergency Medicine 44 2004 199 205 (Pubitemid 39140517)
28. L.I. Horwitz, J. Green, and E.H. Bradley US emergency department performance on waiting time and length of visit Annals of Emergency Medicine 55 2010 133 141
29. R. Howes, and N. Crook Using input parameter influences to support the decisions of feedforward neural networks Neurocomputing 24 1999 191 206 (Pubitemid 29098854)
30. S.S. Jones, A. Thomas, R.S. Evans, S.J. Welch, P.J. Haug, and G.L. Snow Forecasting daily patient volumes in the emergency department Academic Emergency Medicine 15 2008 159 170
31. S.S. Jones, R.S. Evans, T.L. Allen, A. Thomas, P.J. Haug, S.J. Welch, and G.L. Snow A multivariate time series approach to modeling and forecasting demand in the emergency department Journal of Biomedical Informatics 42 2009 123 139
32. C.T. Lin, and I.F. Lee Artificial intelligence diagnosis algorithm for expanding a precision expert forecasting system Expert Systems with Applications 36 2009 8385 8390
33. R.H. Lindeman, P.F. Merenda, and R.Z. Gold Introduction to Bivariate and Multivariate analysis 1980 Scott, Foresman Glenview, IL
34. C.J. Lu, and Y.W. Wang Combining independent component analysis and growing hierarchical self-organizing maps with support vector regression in product demand forecasting International Journal of Production Economics 128 2010 603 613
35. M.L. McCarthy, S.L. Zeger, R. Ding, D. Aronsky, N.R. Hoot, and G.D. Kelen The challenge of predicting demand for emergency department services Academic Emergency Medicine 15 2008 337 346
36. Y. Ni, and F. Fan A two-stage dynamic sales forecasting model for the fashion retail Expert Systems with Applications 38 2011 1529 1536
37. J.D. Olden, and D.A. Jackson Illuminating the "black box": a randomization approach for understanding variable contributions in artificial neural networks Ecological Modelling 154 2002 135 150 (Pubitemid 34793582)
38. J.D. Olden, M.K. Joy, and R.G. Death An accurate comparison of methods for quantifying variable importance in artificial neural networks using simulated data Ecological Modelling 178 2004 389 397 (Pubitemid 38946674)
39. S.L. Özesmi, and U. Özesmi An artificial neural network approach to spatial habitat modeling with interspecific interaction Ecological Modelling 116 1999 15 31 (Pubitemid 29114522)
40. J. Puente, A. Gómez, I. Fernández, and P. Priore Medical doctor rostering problem in a hospital emergency department by means of genetic algorithms Computers and Industrial Engineering 56 2009 1232 1242
41. M. Qualls, D.J. Pallin, and J.D. Schuur Parametric versus nonparametric statistical tests: the length of stay example Academic Emergency Medicine 17 2010 1113 1121
42. W.R. Rising, J.A. O'Daniel, and C.S. Roberts Correlating weather and trauma admissions at a level I trauma center The Journal of Trauma 60 2006 1096 1100
43. L.M. Schweigler, J.S. Desmond, M.L. McCarthy, K.J. Bukowski, E.L. Ionides, and J.G. Younger Forecasting models of emergency department crowding Academic Emergency Medicine 16 2009 301 308
44. H. Setzler, C. Saydam, and S. Park EMS call volume predictions: a comparative study Computers and Operations Research 36 2009 1843 1851
45. H. Shen, and J.Z. Huang Interday forecasting and intraday updating of call center arrivals Manufacturing & Service Operations Management 10 2008 391 410
46. A.H. Sung Ranking importance of input parameters of neural networks Expert Systems with Applications 15 1998 405 411 (Pubitemid 128422961)
47. J.W. Taylor A comparison of univariate time series methods for forecasting intraday arrivals at a call center Management Science 54 2008 253 265 (Pubitemid 351463142)
48. J.W. Taylor Triple seasonal methods for short-term electricity demand forecasting European Journal of Operational Research 204 2010 139 152
49. S.H. Tsaur, Y.C. Chiu, and C.H. Huang Determinants of guest loyalty to international tourist hotels - a neural network approach Tourism Management 23 2002 397 405
50. W. Tych, D.J. Pedregal, P.C. Young, and J. Davies An unobserved component model for multi-rate forecasting of telephone call demand: the design of a forecasting support system International Journal of Forecasting 18 2002 673 695
51. M. Wargon, E. Casalino, and B. Guidet From model to forecasting: a multicenter study in emergency departments Academic Emergency Medicine 17 2010 970 978
52. J. Weinberg, L.D. Brown, and J.R. Stroud Bayesian forecasting of an inhomogeneous Poisson process with applications to call center data Journal of the American Statistical Association 102 2007 1185 1198
53. P. Williams, G. Tai, and Y. Lei Simulation based analysis of patient arrival to health care systems and evaluation of an operations improvement scheme Annals of Operations Research 178 2010 263 279
54. T.C. Wong, K.M.Y. Law, H.K. Yau, and S.C. Ngan Analyzing supply chain operation models with the PC-algorithm and the neural network Expert Systems with Applications 38 2011 7526 7534
55. T.C. Wong, S.Y. Wong, and K.S. Chin A neural network-based approach of quantifying relative importance among various determinants toward organizational innovation Expert Systems with Applications 38 2011 13064 13072
56. T.C. Wong, S.C. Ngan, F.T.S. Chan, and A.Y.L. Chong A two-stage analysis of the influences of employee alignment on effecting business-IT alignment Decision Support Systems 53 2012 490 498
57. W. Xu Long range planning for call centers at Fedex The Journal of Business Forecasting Methods and Systems 18 2000 7 11
58. J.Y. Yeh, and W.S. Lin Using simulation technique and genetic algorithm to improve the quality of a hospital emergency department Expert Systems with Applications 32 2007 1073 1083
59. Y. Yoon, T. Guimaraes, and G. Swales Integrating artificial neural networks with rule-based expert systems Decision Support Systems 11 1994 497 507
60. L.M. Zibners, B.K. Bonsu, J.R. Hayes, and D.M. Cohen Local weather effects on emergency department visits Pediatric Emergency Care 22 2006 104 106