
doi: 10.1002/sim.6953
pmid: 27059988
The number of elderly patients requiring hospitalisation in Europe is rising. With a greater proportion of elderly people in the population comes a greater demand for health services and, in particular, hospital care. Thus, with a growing number of elderly patients requiring hospitalisation competing with non‐elderly patients for a fixed (and in some cases, decreasing) number of hospital beds, this results in much longer waiting times for patients, often with a less satisfactory hospital experience. However, if a better understanding of the recurring nature of elderly patient movements between the community and hospital can be developed, then it may be possible for alternative provisions of care in the community to be put in place and thus prevent readmission to hospital. The research in this paper aims to model the multiple patient transitions between hospital and community by utilising a mixture of conditional Coxian phase‐type distributions that incorporates Bayes' theorem. For the purpose of demonstration, the results of a simulation study are presented and the model is applied to hospital readmission data from the Lombardy region of Italy. Copyright © 2016 John Wiley & Sons, Ltd.
330, readmission, Bayes Theorem, Patient Readmission, 004, Applications of statistics to biology and medical sciences; meta analysis, survival analysis, Europe, Hospitalization, Bayes' theorem, length of stay, Italy, Coxian phase-type distribution, Humans, Computer Simulation, Aged
330, readmission, Bayes Theorem, Patient Readmission, 004, Applications of statistics to biology and medical sciences; meta analysis, survival analysis, Europe, Hospitalization, Bayes' theorem, length of stay, Italy, Coxian phase-type distribution, Humans, Computer Simulation, Aged
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