Accident and Emergency (A&E) departments deal with emergency patients in NHS acute hospitals in England. They have access to diagnostics facilities and inpatient beds. A previous government target was that 98% of A&E patients should be completed within four hours. The author was the analytical lead for emergency care in the Department of Health (DH) in 2003 and 2004, responsible for analytical support to ministers on issues faced by the NHS in managing A&E patient flow. A so-called 'generic' discrete event simulation model of A&E services was developed at this time. It described a 'typical' A&E de~artment and enabled detailed investigation and facilitated workshop discussions of potential interventions. It helped advise whether the target was achievable. The development and use of this model at national level is described. An opportunity is also described to use the model in hospital trusts where it was also found to be useful. The experiences with this model provided the motivation to investigate this area further. Simulation is widely used to model A&E services, but very few models are 'generic'- they are usually designed for specific trusts. Three particular research questions are investigated: 1 What are generic hospital simulation models? 2 How can generic hospital simulation models be built? 3 Can they be useful? This research uses a literature review and an informal survey of health OR academics and experienced DH modellers to generate two answers to question 1: a broad four level classification of model types, and a more detailed framework of typical characteristics of generic hospital simulation models. An improved 'generic' A&E patient flow simulation model was then developed to address the shortcomings of the first model, particularly through increased scope and detail. Experiences with,both the original DH model and this improved model provide answers to the second question in identifying different build techniques and important issues to consider when developing generic models. The improved model was used with DH on two case studies: possible NHS responses to a potential swine flu pandemic, and the impact of patient mix and resuscitation patients on A&E performance. This experience, and that with the first model, provide answers to the third question by examining the successes and failures of the use of the models at national and hospital trust level. Possible reasons for the relative levels of success are discussed

This thesis examines the application of operations management (OM) theory to the management of NHS hospital inpatient bed resources (also known as bed management). The study was initiated by management's desire for improvement in bed management at North Management General Hospital (NMGH), a medium-sized acute hospital which is now part of the Pennine Acute Hospitals NBS Trust (the Trust) in the North West of England. The study made use of published research into the practical application of OM theory in various organisations - particularly the still small number of published studies conducted in the health sector - in order to analyse data collected relating to bed management at NMGH over two periods: April 2002 through to April 2004, and also for the month of May 2005. For the data collection, the study deployed various qualitative and quantitative techniques including, process mapping, interviews, observation and statistical analysis. The purpose of the second, shorter, field-study in May 2005 was to measure the outcomes arising from recommendations made to the Trust following the analysis of data collected between April 2002 and April 2004. This allowed for the re-appraisal of the original recommendations to be incorporated into the results and conclusions of this study. This thesis argues that the benefits of applying OM theory in an English NHS hospital are demonstrated by measurable improvements in the management of throughput and queues when OM theory is used in designing layouts and in augmenting capacity coping systems. However, currently, certain cultural and political conditions within the NHS effectively constrain the usefulness of OM approaches. The thesis argues that cultural and political contingencies in OM theory require further consideration if the benefits of OM theory are to be fully exploited in the English NHS hospital environment. 9

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The thesis compares the founding and development of two sectarian hospitals in the East End of London - the London German Hospital in the nineteenth and the London Jewish Hospital in the early twentieth century. They were established to serve the needs of the German and Jewish immigrant communities living in London at these periods. It was the intention to satisfy their religious and cultural requirements, but especially the language problems they faced, as the majority of migrants had little comprehension of the English language and communication with the medical profession was frustrated at the existing voluntary hospitals because diagnostic aids had not yet been fully implemented and a dependence on verbal communication remained of primary importance. It will be shown that although both groups of migrants faced poverty, the supporters of the German Hospital represented the wealthy and the elite in England and on the Continent. It was a time when an affinity existed between British and German cultures, with German philosophy and science celebrated in this country and the founders received virtually no opposition to their venture. The thesis demonstrates how this contrasted with resistance to the founding of the Jewish Hospital eighty years later. The Jewish immigrants struggled to establish their hospital because of the hostility of the indigenous population exemplified by passage of the Aliens Act of 1905 and the opposition of the Jewish elite led by Lord Rothschild who argued that the immigrant Jews should integrate rather than separate. The thesis argues there was a need for the two hospitals, and contrasts their attainment of success despite their social and economic differences. It will show how the arguments have been assembled using information obtained from literature on immigration studies, ethnic and social issues as well as medical history. Research using the newspaper and hospital archives supplemented the study.

This thesis consists of three essays on hospital quality of inpatient care for patients with acute myocardial infarction (AMI) in the United States. First, it explores issues in the measurement of quality, particularly through the estimation of risk-adjusted mortality rates (RAMRs) for hospitals. This work then examines the relationship between hospital quality for AMI patients and the volume of AMI patients. Chapter 2 proposes using machine-learning techniques, particularly random forests, for risk adjustment of patient severity to predict patient mortality. This work shows that these methods greatly outperform other commonly-used methods in precision of patient risk estimates and also that a facility’s estimated RAMR is sensitive to the underlying patient risk-adjustment model. Chapter 3 asks whether a model which aggregates patient mortality risk for AMI patients matters when estimating RAMRs. To do this, it creates a simulation based on realistic assumptions about how patient case mix can vary by hospital quality and how hospital quality can vary by hospital volume. Because different methods of estimating patient mortality risk have different degrees of precision, the simulation considers variation in this precision and further allows precision to vary by hospital. Again, the ranking of hospitals is sensitive to the method used and this paper finds that common methods are not preferred in many important contexts. Both of the first two chapters pay particular importance to applications of their results to pay-for-performance schemes. Chapter 4 examines the relationship between quality, measured by RAMR, and volume in hospital health provision for AMI inpatients. The main contribution of the paper is estimate the causal effect of volume on quality. To do this, it uses a novel instrument, the volume of shock and of trauma patients. Previous work has found mixed results and has primarily used the volume of patients with the same condition within a certain radius of the hospital as an instrument for volume within the hospital. This paper argues that this instrument has a number of shortcomings that its instrument does not. This paper tests various specifications used in other work and finds robust results for its conclusion.

Healthcare systems are tasked with balancing a variety of conflicting priorities such as increasing patient demand, minimising waiting times and a limited budget. With an ageing population the pressure on hospitals to maintain the quality of patient care is only going to rise as demand increases. Improving the management of these systems is important for avoiding potential dangers such as patient overcrowding and bed blockages which can result in or exacerbate problems such as increased risk to patient care, excessive patient lengths of stay, and staff burnout. This thesis develops and applies an analytical model, which uses queueing theory to approximate healthcare systems in order to provide a means of analysing these systems mathematically. In particular we consolidate, simplify and extend the theory underpinning both single node and networks of infinite server queues, using ideas and concepts developed in Gallivan and Utley (2005) and Massey and Whitt (1993) in order to derive explicit and easy to use formulae for the mean and variance of bed demand. We demonstrate the use of the analytical model by using the model outputs to produce model-based performance indicators to measure hospital performance and hence identify hospitals deserving further investigation. A difficulty in evaluating hospitals is determining how to measure their performance and produce fair and meaningful results while accounting for factors beyond their control, for example hospital size impacts on the relative variability of patient demand and needs to be incorporated into any analysis. We analyse the elective and emergency work of 30 hospitals using model-based performance indicators as a point of comparison for the observed results, allowing for hospital size. For the emergency work we focused on a single length of stay distribution but a key difference arose in the elective case, where we incorporated day-of-week dependent patient lengths of stay. In cases where day-of-week dependent length of stay data is not available, we also devise and evaluate a statistical approach for model calibration.

the growth in size, complexity and the number of chronic diseases in the NHS. In addition, there is an increase in demand for high quality care, processes and planning. Effective Discharge Planning (DP) requires practitioners to have appropriate, patient personalised and updated knowledge in order to be able to make informed and holistic decisions about a patients’ discharge. This research examines the role Knowledge Management (KM) plays in planning an effective discharge plan and examines existing ways in which DP is currently carried out, identifies the stakeholders who are involved in the DP process and highlights problem areas requiring further improvement. The research also examines KM models and KM models in healthcare and integrates KM with DP in the form of a KM-based DP model. The development of the model is based on primary research, using the Grounded Theory method on a sample of stakeholders in the DP process in typical NHS hospitals. Through a process of thematic coding to the point of theoretical saturation the primary research builds on the thorough secondary research, applying problem analysis techniques in an innovative way. The model is intended to highlight the problem areas that require focus and provides a seamless overview allowing healthcare personnel to thoroughly plan the discharge of a patient with the involvement of both patients and carers. By following the guidelines in the model, healthcare personnel, patients and carers will be prompted to identify and implement the relevant factors that make up an effective discharge plan. The KM-based DP model is validated by the actors involved in planning the discharge (i.e. a sample of healthcare personnel). The doctoral challenge of the research is in the development and validation of an original discharge planning model using an innovative application of the Grounded Theory method. The model has implications for further academic research and for a controlled implementation in practice.

In 2003, Mexico conducted a major health reform that transformed its health system to gradually extend health care insurance coverage to more than 50 million uninsured. The expansion of insurance coverage increased the demand for health care and the amount of resources allocated to health. However, little is known about the efficiency with which these resources have been used and about the quality of the services provided. This thesis contributes to this literature by analysing the extent to which primary and hospital care providers are making an efficient use of the resources in the system. The first part of the thesis uses ambulatory care sensitive hospitalisations (ACSHs) to analyse the effectiveness of primary care services within and between the 32 states of Mexico during 2001-2011. Additionally, the burden of ACSHs is defined and a methodology to estimate it proposed. The second part of the thesis details the incentive structure faced by Mexican public hospitals and predicts that hospitals will adjust their performance level to meet their external demand. The model is tested by extending previous work that estimates hospital effects on the length of stay of its patients purged of patient and treatment characteristics. Each hospital effect is interpreted as a measure of performance and then used to construct a panel to examine whether variation across hospitals and over time is related to hospital and state characteristics in estimated dependent variable models for 2005-2013. The findings suggest a high heterogeneity in both primary and hospital care performance with well identified groups of best and worst performers. The empirical model on hospital performance supports the theoretical prediction and additionally found that hospital performance is persistent over time and consistent across type of care.

This report is a record and analysis of the introduction and development of a philosophy now known as Utilisation Management (UM), to a group of North West Health Communities between 2001 and the present day. The study began as an investigation into the use of one service "Rapid Response"; a local South Manchester initiative to provide an alternative for some patients to admission to hospital. As new learning very quickly emerged the learning journey developed into a wider review of the existing evidence, existing services and the new evidence that this programme developed. This evidence indicated how commissioning and provider organisations could transform services and processes in hospitals and communities to reduce "inappropriate admission" to hospital. Ultimately this work culminates in a new national programme "Utilisation Management" now embedded in all NHS Acute Hospital Contracts and is the core business of the North West Utilisation Management Team at Salford PCT. I developed the philosophy described in this dissertation and now established and described nationally, in "Ensuring Appropriateness of Care", (DH, 2006) through an Action Learning and Research approach supported by the Revans Institute for Action Learning and Research at Salford University.