Using phase-type models to cost stroke patient care across health, social and community services

DOI10.1016/J.EJOR.2014.01.063zbMath1338.90236DBLPjournals/eor/McCleanGGBSF14OpenAlexW1989937980WikidataQ60570233 ScholiaQ60570233MaRDI QIDQ299873

Lalit Garg, Ken Kullerton, Maria Barton, Jennifer Gillespie, Sally McClean, Bryan W. Scotney

Publication date: 23 June 2016

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2014.01.063

zbMATH Keywords

Markov processesdecision analysisapplied probabilitycost benefit analysisOR in health servicesCoxian phase-type models

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Management decision making, including multiple objectives (90B50) Case-oriented studies in operations research (90B90) Medical applications (general) (92C50)

Related Items (3)

Laws of large numbers for non-homogeneous Markov systems with arbitrary transition probability matrices ⋮ Laws of large numbers for non-homogeneous Markov systems ⋮ Understanding dynamic status change of hospital stay and cost accumulation via combining continuous and finitely jumped processes

Cites Work

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• Discrete conditional phase-type models utilising classification trees: application to modelling health service capacities
• On the moments and the distribution of the cost of a semi Markov model for healthcare systems
• Choice of modelling technique for evaluating health care interventions
• Introduction to Matrix Analytic Methods in Stochastic Modeling
• A modeling framework that combines markov models and discrete-event simulation for stroke patient care

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