A review of dynamic Bayesian network techniques with applications in healthcare risk modelling

Coping with an ageing population is a major concern for healthcare organisations around the world. The average cost of hospital care is higher than social care for older and terminally ill patients. Moreover, the average cost of social care increases with the age of the patient. Therefore, it is important to make efficient and fair capacity planning which also incorporates patient centred outcomes. Predictive models can provide predictions which their accuracy can be understood and quantified. Predictive modelling can help patients and carers to get the appropriate support services, and allow clinical decision-makers to improve care quality and reduce the cost of inappropriate hospital and Accident and Emergency admissions. The aim of this study is to provide a review of modelling techniques and frameworks for predictive risk modelling of patients in hospital, based on routinely collected data such as the Hospital Episode Statistics database. A number of sub-problems can be considered such as Length-of-Stay and End-of-Life predictive modelling. The methodologies in the literature are mainly focused on addressing the problems using regression methods and Markov models, and the majority lack generalisability. In some cases, the robustness, accuracy and re-usability of predictive risk models have been shown to be improved using Machine Learning methods. Dynamic Bayesian Network techniques can represent complex correlations models and include small probabilities into the solution. The main focus of this study is to provide a review of major time-varying Dynamic Bayesian Network techniques with applications in healthcare predictive risk modelling.

Supporting interoperability frameworks in the UK public sector

This paper describes the design and implementation of a component based software application, which alleviates the problem of software interoperability in the UK public sector. We analyze the current interoperability frameworks across the United Kingdom (UK) and European Union (EU) and propose a software solution that enhances such interoperability initiatives. Our example scenario is placed within a UK local authority, which shares data stored within the Police databases, for making efficient and more accurate operational decisions. The prototype, implemented as a J2EE application and built upon existing databases, proves our concept that it is possible to achieve data and application interoperability without integrating data sources and without using XML formats for data sharing.