The US spends more money on health care than other industrialized nations. Nevertheless, the US lags behind them in life expectancies, access to care, and other health indicators. This can be attributed to the numerous issues that afflict the US health care sector - the lack of a universal health coverage, increasing medical errors, over and under-treatment of patients, lack of standardization, and so on. It is believed that the structure of health care delivery as it exists in the US is broken, which consequently reduces the quality of provided care and increases costs. There is a growing consensus among the different players in the sector that a complete overhaul of the health care system is required. This study presents an approach to identify patient treatment over a cycle of care. Every medical condition has a care cycle over which treatment is provided. The complete cycle of care of most medical conditions comprise of both inpatient and ambulatory care and start from the onset of the disease to its resolution. There are established guidelines that state what care should be provided during various points of this cycle. It is important to identify and analyze the flow of patients through this cycle of care. Once the flow is identified, various analyses can then be conducted to identify bottlenecks, delays, redundancies and other issues that reduce efficiency and increase costs. Unfortunately, due to the fact that medical data is collected for either medical or billing purposes and not for an operational analysis, it is very difficult to analyze the flow of patients over this cycle of care. This study developed a framework to extract relevant patient medical information from existing administrative databases of health care organizations. This was used to create patient flow paths across a segment of the care cycle to enable the analysis of the care treatment. A case study was conducted at a federal health care provider to identify and map the flow over the care cycle of patients with lung cancer.

Communication and coordination in complex sociotechnical systems require continuous assessment on its artefacts and how they are utilized to improve system performance. Situation Awareness (SA) is considered as a fundamental concept in designing and understanding interactions between human and non-human agents (i.e., information systems) that impact system performance. The interaction efficiency is partly determined by quality of information or SA distributed across agents to ensure the accuracy of decision making and resource allocations. Disrupting SA distribution between agents can significantly affect operations of the system with financial and safety consequences. This research applied the Distributed Situation Awareness (DSA) theory to study and improve patient flow management. The main objective of this research was to advance methodology in the DSA literature for (1) deriving design implications from DSA models, and (2) developing quantitative DSA models to formally compare system designs. This DSA research was situated in the domain of patient flow management. Data were collected using the three-part method of data elicitation, extraction, and representation to investigate DSA at a patient flow command and control center at Carilion Clinic in Roanoke, VA. The data used were elicited from observations and interviews on workers daily activities and available historical database (i.e., TeleTracking). Then, data were represented into a combined network to highlight social, task and knowledge elements in patient flows for studying and assessing patient flow management. The influence of the DSA on complex systems was examined qualitatively and quantitatively. The DSA combined network qualitatively characterized patient flow management and identified deficiencies of the command-and-control center functions. The network characterized admission, clinical (inside-hospital) transportation, discharge, and environmental services functions managed by Carilion Transfer and Communications Center (CTaC). These characterizations led to the identification of design principles on job roles, tasks performed, and SA transactions and distribution adopted by the state-of-the-art patient flow management facility. In addition, the network representing the current operation of CTaC illustrated the connection between functional groups, arbitration of resources, and job roles that could become the bottlenecks in transmitting SA. The network also helped identify inefficient task loops, which resulted in delay due to missing/poor SA, and task orders that could be modified to improve the patient flow and thus reduce the likelihood of delay. The qualitative (i.e., combined network) model was partially translated into a quantitative model based on discrete event simulation (DES) and agent-based modeling (ABM) to simulate patient transportation inside the hospital. The simulation model consisted of 28 patient origins, 29 equipment origins, 12 destinations, and more than 200 entities (i.e., simulation objects). The model was validated by lack of significant difference on various outcome metrics between 100 simulation replications and historical data using one-way t-tests. The simulation model captured the distribution and transactions of knowledge elements between agents within the modeled processes. Further, the model successfully verified the deficiencies in the existing system (i.e., delay and cancelation), attributing various instances of deficiency to be either SA related or non-SA related. The simulation model tested two interventions for eliminating SA deficiencies revealed by the qualitative model: (1) updating the wards nurse before picking up patients from inpatient floor, and (2) updating the X-ray nurse/team before arriving with the patient. Both interventions involved updates from the transporters to nurses, transmitting SA on the estimated time of arrival and patient information for the nurse to become aware of the transport status. The simulation ran for 1500 replications for results on transport time and cancellation rate on these two interventions. One-way t-tests revealed that the intervention to update the wards nurse resulted in significant reductions in mean transport and cancellation rate time compared to historical data (i.e., TeleTracking), yielding 0.42 minutes to 1.24 minutes reduction in transport time and 2% to 5% less cancelations. However, the second intervention resulted in a significant increase in transport time and thus was ineffective. DES and ABM supplemented the qualitative modeling with quantitative evidence on DSA concepts and assessment of potential interventions for improving DSA in patient flow management. Specifically, the DES and ABM enabled comparison and prediction of performance outcome from recommended changes to communication protocols. These findings indicate that DSA is a promising framework for analyzing communication and coordination in complex systems and assessing improvement on SA design quantitatively. / Doctor of Philosophy / Hospitals aim to provide care and treatment to patients in a timely and effective manner but their operations can be hindered by delays and long treatment times, resulting in high operating cost. A potential cause of this problem is the complexity of patient treatment process and the number agents involved. The treatment is provided through nurses, doctors, and technicians who work together to deliver care to patients. They all rely on the information from various medical devices and communicate patient-related information continuously to streamline patient movement towards different locations for different retreatments in the hospital. Thus, studying and improving communication and coordination between the medical staff could improve patient flow that in turn reduce idling resources and patient time in hospital, thereby lowering the healthcare cost without sacrificing quality of care. This dissertation investigated patient movement in the hospital adopting Distributed Situation Awareness (DSA). DSA models communication and coordination by examining the distribution of situation awareness (SA) between human and machine agents for a given task. The primary objective of this dissertation was to investigate how to develop DSA models for studying and improving patient flow management. The dissertation showed how to build a network model that illustrated how SA were generated and distributed amongst hospital staff and information systems to manage admission, discharge, room cleaning, and patient transportation. The network model also helped identified the deficiencies associated with different activities. Further, simulation was used to study the processes and SA communicated quantitively. The simulation model was able to show how one recommended change to the communication protocol could reduce patient transport time and cancellation for one route but another. This dissertation enhanced the methodology DSA for real-world applications and demonstrated the method to quantify SA distribution and transaction in complex system.

The Vrinnevi hospital in Norrköping faces a series of changes in conjunction with “Vision 2020”, the emergency ward is no exception. One of the goals that has been set up is to have 80 % of the arriving patients leave the ER within four hours, while having received the proper care. This study maps out the flow of patients through the ER, from arrival to discharge, as well as the process in between. The study also identifies the areas where bottlenecks in the patient flow are likely to appear and describes countermeasures to remedy such situations. In order to achieve this, a simulation model has been created. Facts used in the study are mainly based on previous studies, interviews with employees at the emergency ward, as well as some assumptions based on a theoretical background. Visits to the ER in question have been made, to gain a better understanding of the system that the simulation will illustrate. The study does not contain any deeper economic analysis. The focus is placed on examining whether the proposed changes to the system will affect the patient flow by measuring number of discharged patients within four hours, number of patients who receive a medical assessment within 30 minutes and the number of patients who get to meet a doctor within an hour. Five different scenarios, changing the work process at the ER, based on previous studies attempting to reduce patient throughput, have been created. The scenarios have been analyzed to form an understanding of how they may affect the different efficiency measurements of the emergency ward. The scenarios that have been simulated are: implementation of doctor-assisted triage, implementation on a “Clinical Initiative Nurse” in the waiting room, a reduction of administrative workload for the employees and adding resources to the emergency ward during specific hours of the day. Lastly, a combination scenario containing experiments with three of the most efficient measures has been created in order to achieve a discharge rate of 80 % within four hours. In conclusion, it is evident that all the scenarios have a positive effect on the efficiency measurements and that they all can be implemented so long as there is a positive attitude towards change and, in some cases, economic support.

Diversos serviços de saúde no Brasil vem apresentado episódios de superlotação, em um contexto onde os recursos são limitados. A redução do tempo de permanência em internações hospitalares tem como consequência direta a disponibilização de mais leitos-dia. O gerenciamento e melhoria do fluxo de pacientes ao longo das internações hospitalares é importante, sendo que o uso eficiente dos leitos pode acontecer devido a uma série de fatores. Estudos demonstram que equipes multidisciplinares podem realizar uma assistência de qualidade, reduzindo custos e o tempo em que os pacientes permanecem internados, sem impacto na reinternação ou mortalidade. Também há trabalhos que apontam a eficácia de unidades dedicadas ao atendimento de doenças específicas. A admissão de pacientes dentro de critérios bem definidos aumenta o giro de leitos. Com o objetivo de analisar se a equipe multidisciplinar Medicina Interna – Emergência (MIE) poderia contribuir para a redução do tempo de permanência hospitalar dos pacientes portadores de doenças prevalentes, sem alterar os indicadores de reinternação e mortalidade, o presente estudo experimental, controlado, não-randomizado, comparou o período pré e pós-intervenção, ou seja, a criação de uma Unidade de Curta Permanência no Serviço de Medicina Interna, do Hospital de Clínicas de Porto Alegre (HCPA). Foram analisadas internações ocorridas através da Emergência do HCPA, de pacientes com 14 anos ou mais, com as doenças prevalentes classificadas conforme grupos do CID-10 (J09-J018; J40-J47; N30-N39; I30-I52; I60-I69; B20-B24; C15-C26; A30-A49; e E10-E14), no período compreendido entre 01 de dezembro de 2008 a 30 de novembro de 2010 (n = 11040). Os resultados do estudo demonstram que após a criação da equipe E-MEI e a sua unidade de curta permanência, houve uma redução do tempo de permanência dos pacientes internados pelas causas selecionadas (antes: 10,89 ± 13,17 dias, após: 9,47 ± 11,24 dias, p = 0,006), e uma diminuição mais acentuada nas internações do Serviço de Medicina Interna [antes (n = 680): 14,33 ± 14,57 dias, após (n = 1243): 9,77 ± 10,62 dias, p = 0,000]. Não ocorreu alteração na taxa de mortalidade de todos os pacientes admitidos para as causas selecionadas [antes (n = 3800): 11,3%, após (n = 3958): 11,8% p = 0,123]. Também não houve alteração na taxa de reinternação de 7 dias na amostra estudada [antes (n = 3369): 7,2%, depois de (n = 3491): 6,7%, p = 0,407]. / Several health services in Brazil has shown episodes of overcrowding, in a context where resources are limited. Reducing the length of stay in hospital has as a direct consequence the provision of more beds-day. Managing and improving the flow of patients throughout the hospital is important, and the efficient use of beds can happen due to a number of factors. Studies have shown that multidisciplinary teams can perform quality care, reducing costs and the time patients remain hospitalized, with no impact on mortality or rehospitalization. There are also studies that show the effectiveness of units dedicated to the treatment of specific diseases. The admission of patients into well-defined criteria increases the turnover of beds. With the objective of analyzing the multidisciplinary team Internal Medicine – Emergency, could help to reduce the length of hospital stay of patients with diseases prevalent, without changing the indicators of rehospitalization and mortality, the present study experimental, controlled, not -randomized study compared the pre-and post-intervention, ie the creation of a Short Stay Unit in the Department of Internal Medicine, Hospital de Clinicas de Porto Alegre (HCPA). We analyzed hospital admissions through the Emergency HCPA, for patients aged 14 years or older with prevalent disease groups classified according to the ICD-10 (J09-J018, J40-J47, N30-N39, I30-I52, I60-I69; B20-B24, C15-C26, A30-A49, and E10-E14), during the period from December 1, 2008 to November 30, 2010 (n = 11,040). The study results show that after the creation of the multidisciplinary team, and its Short Stay Unit, there was a reduction in the length of stay of inpatients by selected causes (before: 10.89 ± 13.17 days after: 9 47 ± 11.24 days, p = 0.006) and a greater reduction in hospitalizations Service of Internal Medicine [before (n = 680): 14.33 ± 14.57 days after (n = 1243): 9, 77 ± 10.62 days, p = 0.000]. No change in the mortality rate of all patients admitted to selected causes [before (n = 3800): 11.3% after (n = 3958): 11.8% p = 0.123]. There was also no change in the rate of readmission than 7 days in our sample [before (n = 3369): 7.2% after (n = 3491): 6.7%, p = 0.407].

Diversos serviços de saúde no Brasil vem apresentado episódios de superlotação, em um contexto onde os recursos são limitados. A redução do tempo de permanência em internações hospitalares tem como consequência direta a disponibilização de mais leitos-dia. O gerenciamento e melhoria do fluxo de pacientes ao longo das internações hospitalares é importante, sendo que o uso eficiente dos leitos pode acontecer devido a uma série de fatores. Estudos demonstram que equipes multidisciplinares podem realizar uma assistência de qualidade, reduzindo custos e o tempo em que os pacientes permanecem internados, sem impacto na reinternação ou mortalidade. Também há trabalhos que apontam a eficácia de unidades dedicadas ao atendimento de doenças específicas. A admissão de pacientes dentro de critérios bem definidos aumenta o giro de leitos. Com o objetivo de analisar se a equipe multidisciplinar Medicina Interna – Emergência (MIE) poderia contribuir para a redução do tempo de permanência hospitalar dos pacientes portadores de doenças prevalentes, sem alterar os indicadores de reinternação e mortalidade, o presente estudo experimental, controlado, não-randomizado, comparou o período pré e pós-intervenção, ou seja, a criação de uma Unidade de Curta Permanência no Serviço de Medicina Interna, do Hospital de Clínicas de Porto Alegre (HCPA). Foram analisadas internações ocorridas através da Emergência do HCPA, de pacientes com 14 anos ou mais, com as doenças prevalentes classificadas conforme grupos do CID-10 (J09-J018; J40-J47; N30-N39; I30-I52; I60-I69; B20-B24; C15-C26; A30-A49; e E10-E14), no período compreendido entre 01 de dezembro de 2008 a 30 de novembro de 2010 (n = 11040). Os resultados do estudo demonstram que após a criação da equipe E-MEI e a sua unidade de curta permanência, houve uma redução do tempo de permanência dos pacientes internados pelas causas selecionadas (antes: 10,89 ± 13,17 dias, após: 9,47 ± 11,24 dias, p = 0,006), e uma diminuição mais acentuada nas internações do Serviço de Medicina Interna [antes (n = 680): 14,33 ± 14,57 dias, após (n = 1243): 9,77 ± 10,62 dias, p = 0,000]. Não ocorreu alteração na taxa de mortalidade de todos os pacientes admitidos para as causas selecionadas [antes (n = 3800): 11,3%, após (n = 3958): 11,8% p = 0,123]. Também não houve alteração na taxa de reinternação de 7 dias na amostra estudada [antes (n = 3369): 7,2%, depois de (n = 3491): 6,7%, p = 0,407]. / Several health services in Brazil has shown episodes of overcrowding, in a context where resources are limited. Reducing the length of stay in hospital has as a direct consequence the provision of more beds-day. Managing and improving the flow of patients throughout the hospital is important, and the efficient use of beds can happen due to a number of factors. Studies have shown that multidisciplinary teams can perform quality care, reducing costs and the time patients remain hospitalized, with no impact on mortality or rehospitalization. There are also studies that show the effectiveness of units dedicated to the treatment of specific diseases. The admission of patients into well-defined criteria increases the turnover of beds. With the objective of analyzing the multidisciplinary team Internal Medicine – Emergency, could help to reduce the length of hospital stay of patients with diseases prevalent, without changing the indicators of rehospitalization and mortality, the present study experimental, controlled, not -randomized study compared the pre-and post-intervention, ie the creation of a Short Stay Unit in the Department of Internal Medicine, Hospital de Clinicas de Porto Alegre (HCPA). We analyzed hospital admissions through the Emergency HCPA, for patients aged 14 years or older with prevalent disease groups classified according to the ICD-10 (J09-J018, J40-J47, N30-N39, I30-I52, I60-I69; B20-B24, C15-C26, A30-A49, and E10-E14), during the period from December 1, 2008 to November 30, 2010 (n = 11,040). The study results show that after the creation of the multidisciplinary team, and its Short Stay Unit, there was a reduction in the length of stay of inpatients by selected causes (before: 10.89 ± 13.17 days after: 9 47 ± 11.24 days, p = 0.006) and a greater reduction in hospitalizations Service of Internal Medicine [before (n = 680): 14.33 ± 14.57 days after (n = 1243): 9, 77 ± 10.62 days, p = 0.000]. No change in the mortality rate of all patients admitted to selected causes [before (n = 3800): 11.3% after (n = 3958): 11.8% p = 0.123]. There was also no change in the rate of readmission than 7 days in our sample [before (n = 3369): 7.2% after (n = 3491): 6.7%, p = 0.407].

Diversos serviços de saúde no Brasil vem apresentado episódios de superlotação, em um contexto onde os recursos são limitados. A redução do tempo de permanência em internações hospitalares tem como consequência direta a disponibilização de mais leitos-dia. O gerenciamento e melhoria do fluxo de pacientes ao longo das internações hospitalares é importante, sendo que o uso eficiente dos leitos pode acontecer devido a uma série de fatores. Estudos demonstram que equipes multidisciplinares podem realizar uma assistência de qualidade, reduzindo custos e o tempo em que os pacientes permanecem internados, sem impacto na reinternação ou mortalidade. Também há trabalhos que apontam a eficácia de unidades dedicadas ao atendimento de doenças específicas. A admissão de pacientes dentro de critérios bem definidos aumenta o giro de leitos. Com o objetivo de analisar se a equipe multidisciplinar Medicina Interna – Emergência (MIE) poderia contribuir para a redução do tempo de permanência hospitalar dos pacientes portadores de doenças prevalentes, sem alterar os indicadores de reinternação e mortalidade, o presente estudo experimental, controlado, não-randomizado, comparou o período pré e pós-intervenção, ou seja, a criação de uma Unidade de Curta Permanência no Serviço de Medicina Interna, do Hospital de Clínicas de Porto Alegre (HCPA). Foram analisadas internações ocorridas através da Emergência do HCPA, de pacientes com 14 anos ou mais, com as doenças prevalentes classificadas conforme grupos do CID-10 (J09-J018; J40-J47; N30-N39; I30-I52; I60-I69; B20-B24; C15-C26; A30-A49; e E10-E14), no período compreendido entre 01 de dezembro de 2008 a 30 de novembro de 2010 (n = 11040). Os resultados do estudo demonstram que após a criação da equipe E-MEI e a sua unidade de curta permanência, houve uma redução do tempo de permanência dos pacientes internados pelas causas selecionadas (antes: 10,89 ± 13,17 dias, após: 9,47 ± 11,24 dias, p = 0,006), e uma diminuição mais acentuada nas internações do Serviço de Medicina Interna [antes (n = 680): 14,33 ± 14,57 dias, após (n = 1243): 9,77 ± 10,62 dias, p = 0,000]. Não ocorreu alteração na taxa de mortalidade de todos os pacientes admitidos para as causas selecionadas [antes (n = 3800): 11,3%, após (n = 3958): 11,8% p = 0,123]. Também não houve alteração na taxa de reinternação de 7 dias na amostra estudada [antes (n = 3369): 7,2%, depois de (n = 3491): 6,7%, p = 0,407]. / Several health services in Brazil has shown episodes of overcrowding, in a context where resources are limited. Reducing the length of stay in hospital has as a direct consequence the provision of more beds-day. Managing and improving the flow of patients throughout the hospital is important, and the efficient use of beds can happen due to a number of factors. Studies have shown that multidisciplinary teams can perform quality care, reducing costs and the time patients remain hospitalized, with no impact on mortality or rehospitalization. There are also studies that show the effectiveness of units dedicated to the treatment of specific diseases. The admission of patients into well-defined criteria increases the turnover of beds. With the objective of analyzing the multidisciplinary team Internal Medicine – Emergency, could help to reduce the length of hospital stay of patients with diseases prevalent, without changing the indicators of rehospitalization and mortality, the present study experimental, controlled, not -randomized study compared the pre-and post-intervention, ie the creation of a Short Stay Unit in the Department of Internal Medicine, Hospital de Clinicas de Porto Alegre (HCPA). We analyzed hospital admissions through the Emergency HCPA, for patients aged 14 years or older with prevalent disease groups classified according to the ICD-10 (J09-J018, J40-J47, N30-N39, I30-I52, I60-I69; B20-B24, C15-C26, A30-A49, and E10-E14), during the period from December 1, 2008 to November 30, 2010 (n = 11,040). The study results show that after the creation of the multidisciplinary team, and its Short Stay Unit, there was a reduction in the length of stay of inpatients by selected causes (before: 10.89 ± 13.17 days after: 9 47 ± 11.24 days, p = 0.006) and a greater reduction in hospitalizations Service of Internal Medicine [before (n = 680): 14.33 ± 14.57 days after (n = 1243): 9, 77 ± 10.62 days, p = 0.000]. No change in the mortality rate of all patients admitted to selected causes [before (n = 3800): 11.3% after (n = 3958): 11.8% p = 0.123]. There was also no change in the rate of readmission than 7 days in our sample [before (n = 3369): 7.2% after (n = 3491): 6.7%, p = 0.407].

Hospital systems in the United States are facing a dilemma regarding capacity management in the emergency department (ED) and the inpatient care setting. The average wait time in EDs across the United States exceeds 98 minutes, which is also the point at which patients begin to abandon healthcare treatment. The purpose of this quantitative study was to examine the use of queueing theory in capacity management on length-of-stay (LOS) rates, left-without-being-seen (LWBS) rates, and boarding rates in the ED and inpatient setting. The boarding rates represent the rate in which patients were roomed in the ED but required inpatient care. This study assessed the relationships between capacity management using queueing theory and a reduction in the aforementioned rates compared to traditional processes across systems within the continental United States. A linear regression analysis with a confidence interval 95% paired with an independent sample t test was used to analyze the secondary datasets. A sample size of approximately 33,000 patients was tested in the areas of LOS, LWBS, and boarding. The results of the analysis determined that access was improved in the ED and inpatient setting when queueing theory was deployed within the hospital system compared to traditional processes for managing capacity within the system. Queuing theory used for capacity management resulted in lower LOS, LWBS, and boarding rates. The implications of this study for positive social change include the opportunity to provide greater access to care for the population as a whole, and better health outcomes for the promotion of population health.

This dissertation employs management systems engineering principles, data science, and industrial systems engineering techniques to address pressing challenges in emergency department (ED) efficiency, infectious disease management at mass gatherings, and student self-efficacy. It is structured into three essays, each contributing to a distinct domain of research, and utilizes industrial and systems engineering approaches to provide data-driven insights and recommend solutions. The first essay used data analytics and regression analysis to understand how patient length of stay (LOS) in EDs could be influenced by multi-level variables integrating patient, service, and organizational factors. The findings suggested that specific demographic variables, the complexity of service provided, and staff-related variables significantly impacted LOS, offering guidance for operational improvements and better resource allocation. The second essay utilized system dynamics simulations to develop a modified SEIR model for modeling infectious diseases during mass gatherings and assessing the effectiveness of commonly implemented policies. The results demonstrated the significant collective impact of interventions such as visitor limits, vaccination mandates, and mask wearing, emphasizing their role in preventing health crises. The third essay applied machine learning methods to predict student self-efficacy in Muslim societies, revealing the importance of socio-emotional traits, cognitive abilities, and regulatory competencies. It provided a basis for identifying students with varying levels of self-efficacy and developing tailored strategies to enhance their academic and personal success. Collectively, these essays underscore the value of data-driven and evidence-based decision- making. The dissertation's broader impact lies in its contribution to optimizing healthcare operations, informing public health policy, and shaping educational strategies to be more culturally sensitive and psychologically informed. It provides a roadmap for future research and practical applications across the healthcare, public health, and education sectors, fostering advancements that could significantly benefit society. / Doctor of Philosophy / Divided into three essays, this dissertation uses industrial and systems engineering and data science to help make emergency departments more efficient, manage the spread of diseases at large events, and predict students' belief in their abilities. The first essay investigates factors that influence how long patients stay in emergency departments, including patient demographics, triage level, the complexity of care they receive, and number of emergency department staff when patient arrived. The essay offers suggestions to improve these services and better manage resources. The second essay models the spread of COVID-19 during the Hajj, a religious mass gathering, and evaluates the effectiveness of three safety measures: limiting the number of attendees, vaccinations, and wearing masks. This essay shows how different strategies can work together to prevent outbreaks. The third essay uses artificial intelligence and machine learning to understand what affects Muslim students' confidence in their abilities, focusing on emotional intelligence, thinking skills, and self-discipline. The findings could help to identify students who need extra support and to create more personalized programs that will help them succeed. Overall, this dissertation contributes to advancing industrial and systems engineering and data science knowledge by addressing complex issues in healthcare, public health, and education, leading to more informed decisions and better strategies. Its broader impact includes improving hospital operations, guiding public health decisions, and helping develop educational programs and interventions that consider cultural and psychological factors.

Este trabalho apresenta conceitos relacionados ao pensamento enxuto, e mais especificamente, ao mapeamento de fluxo de valor (MFV), inseridos no contexto hospitalar, destacando exemplos encontrados na literatura e a análise de um caso prático conduzido pelo autor. Com a elaboração do trabalho, foi possível concluir que não existe um modelo de mapeamento de fluxo de valor padronizado para aplicações de lean em ambientes hospitalares. De maneira geral, a utilização do MFV em hospitais se dá através de adaptações da manufatura que não levam em conta todas as atividades que interferem no fluxo dos pacientes, como o fluxo de informações e de materiais. Para contornar esse problema, esta dissertação visa propor um novo modelo de MFV, voltado para ambientes hospitalares, que consiga contemplar em um único mapa todos os fluxos que interferem diretamente na duração do tratamento do paciente e sirva como modelo padrão para aplicações de lean em hospitais. Para isso, foi realizado um levantamento bibliográfico, que buscou identificar, no período de 2000 a 2013, os principais modelos de MFV atualmente empregados em implantações de lean healthcare e identificar as principais características e pontos positivos de cada um. Estes pontos positivos serviram como requisitos para a elaboração do novo modelo, passando a integrar um único mapa. Com a aplicação prática desse novo MFV, foi possível identificar os gargalos operacionais e inúmeros desperdícios que interferem no tratamento do paciente e que não poderiam ser identificados pelos outros modelos de mapeamento estudados. É possível concluir, com os resultados alcançados, que o modelo proposto atendeu aos objetivos definidos e demonstrou ser uma ferramenta valiosa para identificação de desperdícios em ambientes hospitalares. / This thesis presents lean thinking concepts focused on healthcare environments and more specifically on the value stream mapping (VSM). The research could concluded that there is no value stream map standardized for lean healthcare applications. In general, the use of VSM in hospitals are made by manufacturing adaptations that do not take into account all activities that interfere in the patient flow, such as information and material flow. To solve this problem, this research aims to propose a new VSM model for healthcare, which could contemplate all activities that directly affects the treatment time and also be a template for lean healthcare applications. Therefore, the focus in the literature review was to identify the main healthcare VSM models published between 2000 and 2013 and the key characteristics and strengths of each. These strengths were used as requirements for the new mapping model elaboration and were integrated in a single map. The practical application, conducted by the author, identified operational bottlenecks and numerous wastes that interfere in the patient\'s treatment that could not be identified by the other mapping models studied. In conclusion, the new VSM model proposed has achieve the defined goals and proved to be a valuable tool for identifying waste in hospital environments.

Nos travaux de recherches sont des travaux supports pour les gestionnaires de l’hôpital Robert Pax de Sarreguemines, et plus généralement de tout centre hospitalier pour développer des approches centrées sur le patient. Nous nous sommes inspirés des approches centrées sur le produit issues du domaine industriel qui ont été proposées pour répondre aux exigences croissantes de gestion des produits dans un environnement de plus en plus incertain. Par analogie, les systèmes de production de soins centrés patient peuvent être assimilés aux systèmes de production de biens centrés produit. Cependant, il ne faut pas perdre de vue la spécificité des systèmes de production de soins : le facteur humain. Cette spécificité est à l’origine de leur caractère complexe, aléatoire et imprévisible. Par ailleurs, les approches de pilotage, que ce soit dans le milieu industriel ou hospitalier, sont majoritairement des modèles mathématiques et des modèles de simulation utilisant une approche de gestion centrée sur une ou plusieurs ressources considérées comme critiques. C’est pourquoi il nous a paru judicieux d’opter pour une approche centrée patient basée sur le paradigme multi-agents. Nous proposons alors, un système multi-agents de pilotage réactif dynamique et distribué centré patient du parcours patient au sein des systèmes hospitaliers. L’alternative que nous proposons consiste à utiliser une approche centrée patient et basée sur les agents permettant de minimiser les délais d’attente, ainsi que la durée de séjour, et par conséquent les coûts des soins, tout en assurant un soin de qualité pour l’ensemble des patients et une meilleure gestion des ressources hospitalières / Through our research, we offer a support tool for the managers in Robert Pax hospital in Sarreguemine (France), and more generally any hospital center wishing to develop a patient centered approach. We were inspired by « product centered » approaches emerging from industrial domain which were proposed to answer the increasing requirements of products management. By analogy, health care systems patient centered can be assimilated to production systems product centered. However, it is important not to lose sight of the specificities of health care systems which is the human factor. This specificity makes this system complex, random and unpredictable. Besides, the approaches used in industrial or hospital environment, are mainly mathematical models and simulation approaches centered on one ore several resources categorized as critical. In that sense, it seemed judicious to choose a patient centered approach based on a multi-agent paradigm. We proposed a Reactive multi-agent control system of the patient flow in healthcare system. The proposed alternative is a patient centered approach allowing to minimize the patients waiting time and the length of their stay and consequently the care costs. The proposed approach also ensures the care quality and an optimal use of the hospital resources