The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Gaussian mixture distributions and Coxian phase type distributions have been popular choices model based clustering of patients' length of stay data. This paper compares these models and presents an idea for a mixture distribution comprising of components of both of the above distributions. Also a mixed distribution survival tree is presented. A stroke dataset available from the English Hospital Episode...
In this paper we propose a new approach capable of determining clinically meaningful patient groups from a given dataset of patient spells. We hypothesise that the skewed distribution of length of stay (LOS) observations, often modelled in the past using mixed exponential equations, is composed of several homogeneous groups that together form the overall skewed LOS distribution. We show how the Gaussian...
An effective admission policy is an essential part of successful management of a patient care system. This admission policy should consider the future availability of resources, e.g. number of beds or budgets available. All possible pathways through the whole patient care system need to be identified to better understand the process dynamics of a care system. In the current paper we show how such...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.