Palmer, Ryan; (2018) Use of network analysis, and fluid and diffusion approximations for stochastic queueing networks to understand flows of referrals and outcomes in community health care. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Community services are fundamental in the delivery of health care, providing local care close to or in patient homes. However, planning, managing and evaluating these services can be difficult. One stand out challenge is how these services may be organised to provide coordinated care given their physical distribution, patients using multiple services, and the increasing use of these services by patients with differing needs. This is complicated by a lack of comparable measures for evaluating quality across differing community services. Presented in this thesis is work that I conducted, alongside the North East London Foundation Trust, to understand referrals and the use of outcome data within community services through data visualisation and mathematical modelling. Firstly, I applied several data visualisations, building from a network analysis, to aid the design of a single point of access for referrals into community services - helping to understand patterns of referrals and patient use. Of interest were concurrent uses of services, whether common patterns existed and how multiple referrals occurred over time. This highlighted important dynamics to consider in modelling these services. Secondly, I developed a patient flow model, extending fluid and diffusion approximations of stochastic queueing systems to include complex flow dynamics such as re-entrant patients and the use of multiple services in sequence. Patient health is also incorporated into the model by using states that patients may move between throughout their care, which are used to model the differential impact of care. I also produced novel methods for allocating servers across parallel queues and patient groups. Finally, I developed the concept of ``the flow of outcomes'' - a measure of how individual services contribute to the output of patients in certain health states over time - to provide operational and clinical insight into the performance of a network of services.

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