Modelling changes in healthcare demand through geographic data extrapolation.

Stay Well Plans are a new programme of care offered to frail and elderly people in Newport. In 2016 a roll out the programme to be offered in all five counties serviced by Aneurin Bevan University Health Board was planned. This paper presents the data analysis and modelling used to determine the programme's effects on the demand of the wider system, and the effects of a Gwent-wide roll out. We extrapolate information from data from a geographical subset of the model domain to a larger geographical area, adjusting for population sizes, deprivation, and distances to healthcare facilities. These parametrise a Markov model and Monte Carlo simulation to predict changes in demand due to different levels of roll out. We conclude that a programme roll out may result in a large reduction on demand at residential care, however at the expense of an increase in demand at community care services.

Emergency services utilization in Jakarta (Indonesia): a cross-sectional study of patients attending hospital emergency departments.

BACKGROUND: Pre-hospital and emergency services in Indonesia are still developing. Despite recent improvements in the Indonesian healthcare system, issues with the provision of pre-hospital and emergency services persist. The demand for pre-hospital and emergency services has not been the subject of previous research and, therefore, has not been fully understood. Our research explored the utilization of emergency medical services by patients attending hospital emergency departments in Jakarta, Indonesia. METHODS: The study used a cross-sectional survey design involving five general hospitals (four government-funded and one private). Each patient's demographic profile, medical conditions, time to treatment, and mode of transport to reach the hospital were analysed using descriptive statistics. RESULTS: A total of 1964 (62%) patients were surveyed. The median age of patients was 44 years with an interquartile range (IQR) of 26 to 58 years. Life-threatening conditions such as trauma and cardiovascular disease were found in 8.6 and 6.6% of patients, respectively. The majority of patients with trauma travelled to the hospital using a motorcycle or car (59.8%). An ambulance was used by only 9.3% of all patients and 38% of patients reported that they were not aware of the availability of ambulances. Ambulance response time was longer as compared to other modes of transportation (median: 24 minutes and IQR: 12 to 54 minutes). The longest time to treatment was experienced by patients with neurological disease, with a median time of 120 minutes (IQR: 78 to 270 minutes). Patients who used ambulances incurred higher costs as compared to those patients who did not use ambulances. CONCLUSION: The low utilization of emergency ambulances in Jakarta could be contributed to patients' lack of awareness of medical symptoms and the existence of ambulance services, and patients' disinclination to use ambulances due to high costs and long response times. The emergency ambulance services can be improved by increasing population awareness on symptoms that warrant the use of ambulances and reducing the cost burden related to ambulance use.

Using a theory of mind to find best responses to memory-one strategies.

Memory-one strategies are a set of Iterated Prisoner's Dilemma strategies that have been praised for their mathematical tractability and performance against single opponents. This manuscript investigates best response memory-one strategies with a theory of mind for their opponents. The results add to the literature that has shown that extortionate play is not always optimal by showing that optimal play is often not extortionate. They also provide evidence that memory-one strategies suffer from their limited memory in multi agent interactions and can be out performed by optimised strategies with longer memory. We have developed a theory that has allowed to explore the entire space of memory-one strategies. The framework presented is suitable to study memory-one strategies in the Prisoner's Dilemma, but also in evolutionary processes such as the Moran process. Furthermore, results on the stability of defection in populations of memory-one strategies are also obtained.

Evolution reinforces cooperation with the emergence of self-recognition mechanisms: An empirical study of strategies in the Moran process for the iterated prisoner's dilemma.

We present insights and empirical results from an extensive numerical study of the evolutionary dynamics of the iterated prisoner's dilemma. Fixation probabilities for Moran processes are obtained for all pairs of 164 different strategies including classics such as TitForTat, zero determinant strategies, and many more sophisticated strategies. Players with long memories and sophisticated behaviours outperform many strategies that perform well in a two player setting. Moreover we introduce several strategies trained with evolutionary algorithms to excel at the Moran process. These strategies are excellent invaders and resistors of invasion and in some cases naturally evolve handshaking mechanisms to resist invasion. The best invaders were those trained to maximize total payoff while the best resistors invoke handshake mechanisms. This suggests that while maximizing individual payoff can lead to the evolution of cooperation through invasion, the relatively weak invasion resistance of payoff maximizing strategies are not as evolutionarily stable as strategies employing handshake mechanisms.

Reinforcement learning produces dominant strategies for the Iterated Prisoner's Dilemma.

We present tournament results and several powerful strategies for the Iterated Prisoner's Dilemma created using reinforcement learning techniques (evolutionary and particle swarm algorithms). These strategies are trained to perform well against a corpus of over 170 distinct opponents, including many well-known and classic strategies. All the trained strategies win standard tournaments against the total collection of other opponents. The trained strategies and one particular human made designed strategy are the top performers in noisy tournaments also.

How efficient can an emergency unit be? A perfect world model.

Various approaches have been used to identify possible routes for improvement of patient flow within an emergency unit (EU). One such approach is to use simulation to create a 'real world' model of an EU and carry out various tests to gauge ways of improvement. This paper proposes a novel approach in which simulation is used to create a 'perfect world model'. The EU at a major UK hospital is modelled not as it is, but as it could be. The 'efficiency gap' between the 'perfect world' and the 'real world' demonstrates how operational research can be used effectively to identify the location of bottlenecks in the current 'whole hospital' patient pathway and can be used in the planning and managing of hospital resources to ensure the most effective use of those resources.