Costing hospital resources for stroke patients using phase-type models

Health Care Management Science

Volumn 14, Issue 3, 2011, Pages 279-291

  Gillespie, Jennifer ^a   McClean, Sally ^a   Scotney, Bryan ^a   Garg, Lalit ^a   Barton, Maria ^a   Fullerton, Ken ^b  

^a UNIVERSITY OF ULSTER   (United Kingdom)

^b QUEEN'S UNIVERSITY BELFAST   (United Kingdom)

Author keywords

Healthcare modelling; Patient flow; Phase type models; Stroke disease; Thrombolysis

Indexed keywords

ARTICLE; ECONOMICS; FIBRINOLYTIC THERAPY; HOSPITAL COST; HUMAN; LENGTH OF STAY; ORGANIZATION AND MANAGEMENT; PROBABILITY; STATISTICS; STROKE; THEORETICAL MODEL;

EFFICIENCY, ORGANIZATIONAL; HOSPITAL COSTS; HUMANS; LENGTH OF STAY; MARKOV CHAINS; MODELS, THEORETICAL; STROKE; THROMBOLYTIC THERAPY;

EID: 80051873002     PISSN: 13869620     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10729-011-9170-y     Document Type: Article

References (43)

1. Akaike H (1974) A new look at the statistical model identification. IEEE T Automat Contr 19(6): 716-723.
2. Assmussen S, Nerman O, Olsson M (1006) Fitting phase-type distributions via the EM algorithm. Scand J Stat 23: 419-441.
3. Bebbington A, Darton R, Netton A (2001) Care homes for older people: volume 2 admissions, needs and outcomes, The 1995-96 National Longitudinal Survey of Publicly-funded Admissions Edn, Personal Social Services Research Unit, University of Kent at Canterbury.
4. Caulkins JP, Dietze P, Ritter A (2007) Dynamic Compartmental model of trends in Australian drug use. Health Care Manag Sci 10: 151-162.
5. Christodoulou G, Taylor GJ (2001) Using a continuous time hidden Markov process, with covariates, to model bed occupancy of people aged over 65 years. Health Care Manag Sci 4: 21-24.
6. Cochran JK, Bharti A (2006) Stochastic bed balancing of an obstetrics hospital. Health Care Manag Sci 9: 31-45.
7. Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B 39(1): 1-38.
8. Department of Health (2009) NHS Choices: Your Health, Your Choice: Overview Department of Health, http://www. nhs. uk/NHSEngland/thenhs/about/Pages/overview. aspx. Accessed 24/01/11.
9. Department of Health (2008) NHS Institute for Innovation and Improvement. Department of Health, http://www. institute. nhs. uk/. Accessed 25/01/11.
10. Department of Health (2008) NHS Institute for Innovation and Improvement: Performance Management. Department of Health, http://www. institute. nhs. uk/quality_and_service_improvement_tools/quality_and_service_improvement_tools/performance_management. html. Accessed 25/01/11.
11. Fackrell M (2009) Modelling healthcare systems with phase-type distributions. Health Care Manag Sci 12: 11-26.
12. Faddy MJ, McClean SI (1999) Analysing data on lengths of stay of hospital patients using phase-type distributions. Appl Stoch Model Bus Ind 15: 311-317.
13. Faddy MJ, McClean SI (2005) Markov Chain Modelling for geriatric patient care. Methods Inf Med 44: 369-373.
14. Garg L, McClean SI, Meenan BJ, El-Darzi E, Millard PH (2009) Clustering patient length of stay using mixtures of Gaussian models and phase type distributions. 22nd IEEE Symposium on Computer-Based Medical Systems (CBMS 2009), Albuquerque, New Mexico, USA, August 3-4, 2009, pp 1-7.
15. Garg L, McClean S, Meenan, B and Millard P (2009) A phase type survival tree model for clustering patient Length of Stay. Applied Stochastic Models and Data Analysis. The XIII International Conference, Vilnius, Lithuania, pp 477.
16. Garg L, McClean S, Meenan B, Millard P (2010) A non-homogeneous discrete time Markov model for admission scheduling and resource planning in a cost or capacity constrained healthcare system. Health Care Manag Sci 13: 155-169.
17. Green PJ (1987) Penalized likelihood for general semi-parametric regression models. Int Stat Rev 55: 245-259.
18. Harper PR (2002) A Framework for Operational Modelling of Hospital Resources. Health Care Manag Sci 5: 165-173.
19. Harrison GW (2001) Implications of mixed exponential occupancy distributions and patient flow models for health care planning. Health Care Manag Sci 4: 35-45.
20. Jones PW, Smith P (2001) Stochastic processes: an introduction. Arnold, London.
21. Latouche G, Ramaswami V (1999) Introduction to matrix analytic methods in stochastic modelling. SIAM, Philadelphia.
22. McClean SI, McAlea B, Millard PH (1998) Using a Markov reward model to estimate spend down costs for a geriatric department. J Oper Res 49: 1021-1025.
23. McClean SI, Millard P (2007) Where to treat the older patient? Can Markov models help us better understand the relationship between hospital and community care? J Oper Res Soc 58: 255-261.
24. McClean SI, Millard PH (1998) A Three compartment model of the patient flows in a geriatric department: a decision support approach. Health Care Manag Sci 1: 159-163.
25. McClean S, Barton M, Garg L, Fullerton K (2011) Combining markov models and discrete events simulation to plan stroke patient care. Transactions on Modeling and Computer Science (TOMACS) 21(4).
26. McClean S, Faddy M, Millard P (2005) Markov model-based clustering for efficient patient care. Proceedings of the 18th IEEE symposium on computer-based medical systems IEEE, Piscataway, pp 467.
27. Marshall AH, McClean SI (2004) Using Coxian Phase-type distributions to identify patient characteristics for duration of stay in hospital. Health Care Manag Sci 7: 285-289.
28. Marshall AH, McClean SI (2003) Conditional phase-type distributions for modelling patient length of stay in hospital. Int Trans Oper Res 10: 565-576.
29. Marshall AH, McClean SI, Millard PH (2004) Addressing bed costs for the elderly: a new methodology for modelling patient outcomes and length of stay. Health Care Manag Sci 7: 27-33.
30. Marshall A, Vasilakis C, El-Darzi E (2005) Length of stay-based patient flow models: recent developments and future directions. Health Care Manag Sci 8: 213-220.
31. Marshall AH, Zenga M (2009) Recent developments in fitting coxian phase-type distributions in healthcare. Applied stochastic models and data analysis. The XIII International Conference, Vilnius, Lithuania, pp 482.
32. Millard PH (1989) Geriatric medicine: a new method of measuring bed usage and a theory for planning, MD thesis, University of London.
33. Neuts MF (1981) Matrix-geometric solutions in stochastic models: an algorithmic approach. John Hopkins University Press, Baltimore.
34. Norris JR (1998) Markov chains. Cambridge Series in Statistical and Probabilistic Mathematics. Cambridge University Press, Cambridge, England.
35. Olsson M (1996) Estimation of phase-type distributions from censored data. Scand J Stat 23: 443-460.
36. Royal College of Physicians National Sentinel Stroke Audit Report (2008) Audit of stroke, prepared for on behalf of the Intercollegiate Stroke Working Party, London, RCP.
37. Saka O, McGuire A, Wolfe C (2009) Cost of stroke in the United Kingdom. Age Ageing 38: 27-32.
38. Sandercock P, Berge E, Dennis M, Forbes J, Hand P, Kwan J, Lewis S, Lindley R, Neilson A, Wardlaw J (2004) Cost-effectiveness of Thrombolysis with Recombinant Tissue Plasminogen Activator for Acute Ischemic Stroke Assessed by a Model Based on UK NHS Costs 1490-1497.
39. Sundburg G, Bagust A, Terent A (2003) A model for costs of stroke service. Health Policy 63: 81-94.
40. Taylor G, McClean S, Millard P (1998) Continuous time Markov model for geriatric patient behaviour. Appl Stoch Model Data Anal 13: 315-323.
41. The National Institute of Neurological Disorders and Stroke rt-PA Stroke Study Group (NINDS) (1995) New Engl J Med 33: 1581-1588.
42. The NHS Confederation (2010) On the Day Briefing- 2010 Budget Report, The NHS Conderation, http://www. nhsconfed. org/Documents/budget_2010_briefingmarch10. pdf.
43. Xie H, Chaussalet TJ, Millard PH (2006) A Model based approach to the analysis of patterns of length of stay in institutional long-term care. IEEE Trans Inf Tech Biosci 10: 512-551.