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.

Rights, Rationality and Reproduction: Balancing Interests in the Abortion Debate

As medical technology has advanced, so too have our attitudes towards the level of control we can or should expect to have over our procreative capacities. This creates a multidimensional problem for the law and family planning services in terms of access to services – whether to avoid conception or terminate a pregnancy – and the negligent provision of these services. These developments go to the heart of our perception of autonomy. Unsurprisingly, these matters also raise a moral dilemma for the law. Distinctively, discourse in this area is dominated by assertions of subjective moral value; in relation to life, to personal choice and to notions of the archetypal family. Against this, I stress that a model of objective morality can answer these challenging questions and resolve the inherent problems of legal regulation. Therefore, I argue that notions of autonomy must be based on a rational, action-based understanding of what it means to be a ‘moral agent’. I claim that from this we might support a legal standard, based on objective rational morality, which can frame our constitutional norms and our conception of justice in these contentious areas. This paper claims that the current regulation of abortion is outdated and requires radical reform. It proposes a scheme that would shift the choice towards the mother (and the father), remove the unnecessarily broad disability ground and involve doctors having a role of counsel (rather than gatekeeper).