In this thesis, we generalize a set of facility location models within a two-stage robust optimization framework by assuming each demand is only known to lie within a continuous and bounded uncertainty region. Our approach involves discretizing each uncertainty region into a set of finite scenarios, each of which represents a potential location where the demand may be realized. We show that the gap between the optimal values of the theorized continuous uncertainty problem and our discretized model can be bounded by a function of the granularity of the discretization. We then propose a solution technique based on row-and-column generation, and compare its performance with existing solution methods. Lastly, we apply our robust location models to the problem of ambulance positioning using cardiac arrest location data from the City of Toronto, and show that hedging against demand location uncertainty may help decrease EMS response times to cardiac arrest emergencies.

In this thesis, we generalize a set of facility location models within a two-stage robust optimization framework by assuming each demand is only known to lie within a continuous and bounded uncertainty region. Our approach involves discretizing each uncertainty region into a set of finite scenarios, each of which represents a potential location where the demand may be realized. We show that the gap between the optimal values of the theorized continuous uncertainty problem and our discretized model can be bounded by a function of the granularity of the discretization. We then propose a solution technique based on row-and-column generation, and compare its performance with existing solution methods. Lastly, we apply our robust location models to the problem of ambulance positioning using cardiac arrest location data from the City of Toronto, and show that hedging against demand location uncertainty may help decrease EMS response times to cardiac arrest emergencies.

abstract: This dissertation addresses access management problems that occur in both emergency and outpatient clinics with the objective of allocating the available resources to improve performance measures by considering the trade-offs. Two main settings are considered for estimating patient willingness-to-wait (WtW) behavior for outpatient appointments with statistical analyses of data: allocation of the limited booking horizon to patients of different priorities by using time windows in an outpatient setting considering patient behavior, and allocation of hospital beds to admitted Emergency Department (ED) patients. For each chapter, a different approach based on the problem context is developed and the performance is analyzed by implementing analytical and simulation models. Real hospital data is used in the analyses to provide evidence that the methodologies introduced are beneficial in addressing real life problems, and real improvements can be achievable by using the policies that are suggested. This dissertation starts with studying an outpatient clinic context to develop an effective resource allocation mechanism that can improve patient access to clinic appointments. I first start with identifying patient behavior in terms of willingness-to-wait to an outpatient appointment. Two statistical models are developed to estimate patient WtW distribution by using data on booked appointments and appointment requests. Several analyses are conducted on simulated data to observe effectiveness and accuracy of the estimations. Then, this dissertation introduces a time windows based policy that utilizes patient behavior to improve access by using appointment delay as a lever. The policy improves patient access by allocating the available capacity to the patients from different priorities by dividing the booking horizon into time intervals that can be used by each priority group which strategically delay lower priority patients. Finally, the patient routing between ED and inpatient units to improve the patient access to hospital beds is studied. The strategy that captures the trade-off between patient safety and quality of care is characterized as a threshold type. Through the simulation experiments developed by real data collected from a hospital, the achievable improvement of implementing such a strategy that considers the safety-quality of care trade-off is illustrated. / Dissertation/Thesis / Doctoral Dissertation Industrial Engineering 2019

Yes / The role of the pharmacist as we know it has altered substantially over recent years. No longer is the expectation that they are a dispenser of pills and potions and nothing else (Richardson and Pollock, 2010). Skills/competencies mapping and associated performance have been examined from a supply chain perspective e.g. Kauppi et al., 2013; Sohal, 2013; but there is limited evidence of such exploration within the pharmacy profession and healthcare operations management. The aim of this study is to explore the critical management skills needed by pharmacists to effectively perform their role within the National Health Service (UK).

No description available.

Yes / The National Health Service (UK) is wholly accountable and heavily scrutinised for its strategy, activity, performance and spending (Appleby, 2016; NHS Confederation, 2016; Parliament UK, 2010), and much research has been undertaken as to its effectiveness at managing its operations and its competency in doing so (Gov.Uk, 2016; National Audit Office, 1999)). The impact of not performing adequately combined with threats such as funding cuts (King’s Fund, 2016), government intervention and private sector competition; has led to uncertainty and disillusion with the sustainability of the service (Hunter, 2016). Based on current economic concerns, this paper chooses to focus on the area of Medical Equipment Loans Services where products are released to patients to aid therapeutic rehabilitation and physical mobility. The aim of this study is to examine the process of product retrieval in a multi-case study analysis and consider how value-added technologies can be used to improve retrieval success rates.

Le travail de recherche présenté dans cette thèse est l’un des premiers dans le domaine de la gestion optimisée des services d’aide médicale urgente en France. Il est conduit dans le cadre d’un projet ANR qui vise à proposer de nouveaux scénarios d’organisation pour le SAMU du département du Val-de-Marne pour offrir aux patients l’accès adapté aux soins, tout en disposant de ressources limitées. Pour cela, nous développons un modèle de simulation à évènements discrets qui modélise et évalue la performance actuelle de ce système complexe et identifie des pistes d’amélioration susceptibles de réduire la durée entre la réception de l’appel et l’arrivée d’une équipe sur le lieu de l’accident, appelé temps de réponse, qui est un aspect critique dans les systèmes d’urgence pré-hospitaliers. Ce modèle de simulation est utilisé pour quantifier l’impact de divers scénarii se rapportant aux nombres de ressources humaines et matérielles, à la localisation de ces ressources à travers le territoire du Val-de-Marne de manière statique et à l’affectation de ces ressources aux interventions. En outre, nous avons effectué des analyses de sensibilité sur différents paramètres du modèle comme le nombre d’appels reçus, les temps de trajet et les temps de service. Finalement, nous avons utilisé deux approches d’optimisation par simulation afin d’étudier l’impact de la relocalisation des équipes dans différentes bases du département plusieurs fois dans une journée afin de tenir compte des fluctuations des temps de trajet et du nombre de ressources. Les résultats de ces deux approches ont été analysés puis comparés au regard des temps de calcul et de la distribution du temps de réponse. / The research addressed in this thesis is one of the first studies to address the Emergency Medical Service in France, known as SAMU (which stands for the French acronym of Urgent Medical Aid Services). It is funded by the French National Research Agency and aims at improving the organizational processes of the Val-de-Marne department SAMU system in order to meet the population’s needs under limited resources. For this purpose, we develop a discrete event simulation model in order to assess the current performance of this complex system, as well as to investigate the effects of potential process changes that would lead to enhanced operational efficiency, in terms of response time performance (i.e. the period between the receipt of a call and the first arrival of a rescue team at the scene), which is a critical aspect for SAMU providers. This model was used as a decision-support tool for comparing the relative benefits of several scenarios mainly related to the needed resource levels and static location of rescue teams throughout the Val-de-Marne area and their assignment to incoming calls. Sensivity analyses were also performed by changing values of some input parameters such as arrival rates of calls, travel times and service times. Finally, we used two simulation optimization approaches to analyze the impact of rescue teams assignment to bases by considering temporal fluctuations of travel times and number of resources during a day. Experimental results of the two approaches were analyzed and compared regarding computational times and response time distribution.

Delivering health care services in an efficient and effective way has become a great challenge for many countries due to the aging population worldwide, rising health expenses, and increasingly complex healthcare delivery systems. It is widely recognized that models and analytical tools can aid decision-making at various levels of the healthcare delivery process, especially when decisions have to be made under uncertainty. This thesis employs stochastic models to improve decision-making under uncertainty in two specific healthcare settings: inpatient flow management and infectious disease modeling. In Part I of this thesis, we study patient flow from the emergency department (ED) to hospital inpatient wards. This line of research aims to develop insights into effective inpatient flow management to reduce the waiting time for admission to inpatient wards from the ED. Delayed admission to inpatient wards, also known as ED boarding, has been identified as a key contributor to ED overcrowding and is a big challenge for many hospitals. Part I consists of three main chapters. In Chapter 2 we present an extensive empirical study of the inpatient department at our collaborating hospital. Motivated by this empirical study, in Chapter 3 we develop a high fidelity stochastic processing network model to capture inpatient flow with a focus on the transfer process from the ED to the wards. In Chapter 4 we devise a new analytical framework, two-time-scale analysis, to predict time-dependent performance measures for some simplified versions of our proposed model. We explore both exact Markov chain analysis and diffusion approximations. Part I of the thesis makes contributions in three dimensions. First, we identify several novel features that need to be built into our proposed stochastic network model. With these features, our model is able to capture inpatient flow dynamics at hourly resolution and reproduce the empirical time-dependent performance measures, whereas traditional time-varying queueing models fail to do so. These features include unconventional non-i.i.d. (independently and identically distributed) service times, an overflow mechanism, and allocation delays. Second, our two-time-scale framework overcomes a number of challenges faced by existing analytical methods in analyzing models with these novel features. These challenges include time-varying arrivals and extremely long service times. Third, analyzing the developed stochastic network model generates a set of useful managerial insights, which allow hospital managers to (i) identify strategies to reduce the waiting time and (ii) evaluate the trade-off between the benefit of reducing ED congestion and the cost from implementing certain policies. In particular, we identify early discharge policies that can eliminate the excessively long waiting times for patients requesting beds in the morning. In Part II of the thesis, we model the spread of influenza pandemics with a focus on identifying factors that may lead to multiple waves of outbreak. This line of research aims to provide insights and guidelines to public health officials in pandemic preparedness and response. In Chapter 6 we evaluate the impact of seasonality and viral mutation on the course of an influenza pandemic. In Chapter 7 we evaluate the impact of changes in social mixing patterns, particularly mass gatherings and holiday traveling, on the disease spread. In Chapters 6 and 7 we develop agent-based simulation models to capture disease spread across both time and space, where each agent represents an individual with certain socio-demographic characteristics and mixing patterns. The important contribution of our models is that the viral transmission characteristics and social contact patterns, which determine the scale and velocity of the disease spread, are no longer static. Simulating the developed models, we study the effect of the starting season of a pandemic, timing and degree of viral mutation, and duration and scale of mass gatherings and holiday traveling on the disease spread. We identify possible scenarios under which multiple outbreaks can occur during an influenza pandemic. Our study can help public health officials and other decision-makers predict the entire course of an influenza pandemic based on emerging viral characteristics at the initial stage, determine what data to collect, foresee potential multiple waves of attack, and better prepare response plans and intervention strategies, such as postponing or cancelling public gathering events.

[pt] As doenças do rim e trato urinário contribuem com cerca de 850 mil mortes a cada ano, sendo a décima segunda causa de morte do mundo. No Brasil, a diálise ainda é o procedimento mais utilizado, apesar de o transplante ser a modalidade mais recomendada, por oferecer melhor qualidade de vida ao paciente, uma possível redução do risco de mortalidade e menor custo que a diálise. Uma vez na fila, o paciente ainda se depara um conjunto de ineficiências do Sistema Nacional de Transplante. A presente pesquisa identifica que uma delas é o desalinhamento entre os atores do transplante (doador, receptor e unidade transplantadora) e que há um gap no que tange às atividades do ator unidades transplantadoras. Dessa forma, o objetivo da presente pesquisa é investigar, à luz da gestão de operações, o modelo de uma unidade transplantadora de referência, inserida na rede de transplante renal do estado do Rio de Janeiro. A partir do levantamento da literatura e de campo, são realizadas modelagens do processo de transplante renal, descrição e diagnóstico do modelo de operação da unidade transplantadora e proposições acerca do projeto de operação da unidade estudada / [en] Diseases of the kidney and urinary tract contribute about 850,000 deaths each year, being the 12th leading cause of death in the world. In Brazil, dialysis is still the most used procedure, although transplantation is the most recommended modality, because it offers a better quality of life for the patient, a possible reduction of mortality risk and lower cost than dialysis. Once in the queue, the patient still faces a set of inefficiencies of the National Transplant System. The present research identifies that one of them is the misalignment between the actors of the transplant (donor, receiver and transplantation unit) and that there is a gap with respect to the activities of the transplantation unit actors. Thus, the objective of this research is to investigate, in the light of operations management, the model of a reference transplantation unit, inserted in the kidney transplant network of the state of Rio de Janeiro. From the literature and field survey, modeling of the renal transplantation process, description and diagnosis of the operation model of the transplantation unit and propositions about the operation project of the studied unit are performed.

La tesi vuole porre l’attenzione su uno dei dilemmi dei moderni sistemi sanitari: garantire buoni servizi di cura a costi contenuti. La tesi affronta tale questione attraverso l’implementazione del modello value-based (cfr. medicina basata sul valore), dove per “valore” si intende il risultato di salute conseguito per risorse impiegate. L’obiettivo della tesi è quello di dedurre, attraverso tre differenti punti di analisi, le condizioni e i fattori che stanno inducendo le aziende sanitarie a migliorare i loro modelli di erogazione di cura al fine di incrementare il valore per i pazienti. Nello specifico, la tesi focalizza l’attenzione sui processi sanitari (cfr. operations management) mettendo in risalto le modalità con cui le aziende sanitarie tendono a ridisegnare i processi sanitari per rispondere meglio ai bisogni dei pazienti.La tesi tocca diverse prospettive del modello teorico del value-based. I primi due capitoli analizzano la creazione di valore e le condizioni di implementazione analizzando il fenomeno dalla prospettiva aziendale. Al contrario, l’ultimo capitolo punta ad analizzare tale questione dalla prospettiva del paziente. La tesi da spunti su come le aziende sanitarie debbano intraprendere tali cambiamenti operativi e supportare l’implementazione del modello value-based attraverso tre differenti prospettive: percorsi clinici, efficienza operativa, prospettiva del paziente. / The current thesis tries to shed a light on one of the dilemmas concerning healthcare systems: delivering good care at affordable costs. Therefore, this thesis addresses the issues related to the implementation of the value-based healthcare theory, where “value” is the clinical outcome achieved per resources used. The scope of the thesis is to deduce, through three different viewpoints of analysis, the conditions and drivers that are leading healthcare organizations to enhance their healthcare delivery system in order to create more value for patients. In particular, the thesis stresses the perspective of healthcare operations highlighting how providers tend to redesign healthcare processes to better meet patients’ needs. The thesis touches on different perspectives with regard to the value-based theoretical model. The first two chapters analyze value creation and the conditions of its implementation, looking at these phenomena from the provider’s point of view. In contrast, the last chapter aims to analyze this issue from the patient’s perspective. The thesis makes suggestions on how healthcare organizations should undertake operational changes and deals with value-based healthcare implementation through three different fronts: clinical pathways, operational efficiency, patient’s perspective.