@inproceedings{ea5b5d14ce56495495422c7f2d4fbf43,
title = "MetSim: A simulation decision support tool using meteorological information for short-term planning of hospital services",
abstract = "Improved short-term predictions of hospital admissions and bed occupancy offer the potential to plan resource needs more accurately and effectively. The MetSim project explores the relationship between weather and health, building novel Bayesian models that are more sensitive to fluctuations in weather. Short-term forecasts of the numbers of admissions, categorised by age, gender and medical condition, are produced. In turn, coupled with predictions on length of stay and information on current occupancy, MetSim uses hazard ratios embedded within a simulation framework to provide forecasts of short-term bed needs. MetSim is a collaboration between Cardiff University, the University of Southampton, and the Met Office. Cardiff and Vale University Health Board and Southampton University Hospitals NHS Trust have guided the development of MetSim, provided data and piloted the tool.",
keywords = "Forecasting demand, Hospital capacity management, Simulation, Weather",
author = "Paul Harper and John Minty and Sujit Sahu and Bernard Baffour and Christophe Sarran",
year = "2012",
language = "English",
isbn = "9789898565204",
series = "SIMULTECH 2012 - Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications",
pages = "543--547",
booktitle = "SIMULTECH 2012 - Proceedings of the 2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications",
note = "2nd International Conference on Simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2012 ; Conference date: 28-07-2012 Through 31-07-2012",
}