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.

Accessibility instruments for planning practice: A review of European experiences

Although a large body of literature has been produced on the theoretical definitions and measurements of accessibility, the extent to which such indicators are used in planning practice is less clear. This research explores the gap between theory and application by seeking to understand what the new wave of accessibility instruments (AIs) prepared for spatial and transport planning practice purports to offer the users of AIs. Starting from the question of how urban and transport planners are designing AIs, the article analyzes and describes the AIs developed over the last decade (mainly in Europe), offering a structured overview and a clear categorization of how accessibility measures can be applied. The paper identifies AI characteristics, and considers their usability, based on AI developer perceptions.

Success or failure in knowledge management systems: a universal issue

This paper takes a sociotechnical viewpoint of knowledge management system (KMS) implementation in organizations considering issues such as stakeholder disenfranchisement, lack of communication, and the low involvement of key personnel in system design asking whether KMS designers could learn from applying sociotechnical principles to their systems. The paper discusses design elements drawn from the sociotechnical principles essential for the success of IS and makes recommendations to increase the success of KMS in organizations. It also provides guidelines derived from Clegg’s Principles (2000) for KMS designers to enhance their designs. Our data comes from the application of a plurality of analysis methods on a large comprehensive global survey conducted from 2007 to 2011 of 1034 participants from 76 countries. The survey covers a variety of organizations of all types and sizes from a comprehensive selection of economic sectors and industries. Our results showed that users were not satisfied with the information and knowledge systems that they were being offered. In addition to multiple technology and usability issues, there were human and organisational barriers that prevented the systems from being used to their full potential. We recommend that users of KMS are integrated into the design team so that these usability and other barriers can be addressed during the feasibility stage as well as the actual design and implementation phases.