Modelling Patient Duration of Stay to Facilitate Resource Management of Geriatric Hospitals

A fundamental aspect of health care management is the effective allocation of resources. This is of particular importance in geriatric hospitals where elderly patients tend to have more complex needs. Hospital managers would benefit immensely if they had advance knowledge of patient duration of stay in hospital. Managers could assess the costs of patient care and make allowances for these in their budget. In this paper, we tackle this important problem via a model which predicts the duration of stay distribution of patients in hospital. The approach uses phase-type distributions conditioned on a Bayesian belief network.

Using Coxian Phase-Type Distributions to Identify Patient Characteristics for Duration of Stay in Hospital

Coxian phase-type distributions are a special type of Markov model that describes duration until an event occurs in terms of a process consisting of a sequence of latent phases. This paper considers the use of Coxian phase-type distributions for modelling patient duration of stay for the elderly in hospital and investigates the potential for using the resulting distribution as a classifying variable to identify common characteristics between different groups of patients according to their (anticipated) length of stay in hospital. The identification of common characteristics for patient length of stay groups would offer hospital managers and clinicians possible insights into the overall management and bed allocation of the hospital wards.

Length of Stay-Based Patient Flow Models: Recent Developments and Future Directions

Modelling patient flow in health care systems is vital in understanding the system activity and may therefore prove to be useful in improving their functionality. An extensively used measure is the average length of stay which, although easy to calculate and quantify, is not considered appropriate when the distribution is very long-tailed. In fact, simple deterministic models are generally considered inadequate because of the necessity for models to reflect the complex, variable, dynamic and multidimensional nature of the systems. This paper focuses on modelling length of stay and flow of patients. An overview of such modelling techniques is provided, with particular attention to their impact and suitability in managing a hospital service.

Simulating Coxian Phase-type Distributions for Patient Survival

Coxian phase-type distributions are a special type of Markov model that can be used to represent survival times in terms of phases through which an individual may progress until they eventually leave the system completely. Previous research has considered the Coxian phase-type distribution to be ideal in representing patient survival in hospital. However, problems exist in fitting the distributions. This paper investigates the problems that arise with the fitting process by simulating various Coxian phase-type models for the representation of patient survival and examining the estimated parameter values and eigenvalues obtained. The results indicate that numerical methods previously used for fitting the model parameters do not always converge. An alternative technique is therefore considered. All methods are influenced by the choice of initial parameter values. The investigation uses a data set of 1439 elderly patients and models their survival time, the length of time they spend in a UK hospital.

Simultaneous remote haptic collaboration for assembling tasks

Stand-alone virtual environments (VEs) using haptic devices have proved useful for assembly/disassembly simulation of mechanical components. Nowadays, collaborative haptic virtual environments (CHVEs) are also emerging. A new peer-to-peer collaborative haptic assembly simulator (CHAS) has been developed whereby two users can simultaneously carry out assembly tasks using haptic devices. Two major challenges have been addressed: virtual scene synchronization (consistency) and the provision of a reliable and effective haptic feedback. A consistency-maintenance scheme has been designed to solve the challenge of achieving consistency. Results show that consistency is guaranteed. Furthermore, a force-smoothing algorithm has been developed which is shown to improve the quality of force feedback under adverse network conditions. A range of laboratory experiments and several real trials between Labein (Spain) and Queen’s University Belfast (Northern Ireland) have verified that CHAS can provide an adequate haptic interaction when both users perform remote assemblies (assembly of one user’s object with an object grasped by the other user). Moreover, when collisions between grasped objects occur (dependent collisions), the haptic feedback usually provides satisfactory haptic perception. Based on a qualitative study, it is shown that the haptic feedback obtained during remote assemblies with dependent collisions can continue to improve the sense of co-presence between users with regard to only visual feedback.

A programmable architecture for layered multimedia streams in IPv6 networks

A new configurable architecture is presented that offers multiple levels of video playback by accommodating variable levels of network utilization and bandwidth. By utilizing scalable MPEG-4 encoding at the network edge and using specific video delivery protocols, media streaming components are merged to fully optimize video playback for IPv6 networks, thus improving QoS. This is achieved by introducing “programmable network functionality” (PNF) which splits layered video transmission and distributes it evenly over available bandwidth, reducing packet loss and delay caused by out-of-profile DiffServ classes. An FPGA design is given which gives improved performance, e.g. link utilization, end-to-end delay, and that during congestion, improves on-time delivery of video frames by up to 80% when compared to current “static” DiffServ.