Essays On Perioperative Services Problems In Healthcare

One of the critical challenges in healthcare operations management is to efficiently utilize the expensive resources needed while maintaining the quality of care provided. Simulation and optimization methods can be effectively used to provide better healthcare services. This can be achieved by developing models to minimize patient waiting times, minimize healthcare supply chain and logistics costs, and maximize access. In this proposal, we study some of the important problems in healthcare operations management. More specifically, we focus on perioperative services and study scheduling of operating rooms (ORs) and management of necessary resources such as staff, equipment, and surgical instruments. We develop optimization and simulation methods to coordinate material handling decisions, inventory management, and OR scheduling. In Chapter 1 of this dissertation, we investigate material handling services to improve the flow of surgical materials in hospitals. The ORs require timely supply of surgical materials such as surgical instruments, linen, and other additional equipment required to perform the surgeries. The availability of surgical instruments at the right location is crucial to both patient safety and cost reduction in hospitals. Similarly, soiled material must also be disposed of appropriately and quickly. Hospitals use automated material handling systems to perform these daily tasks, minimize workforce requirements, reduce risk of contamination, and reduce workplace injuries. Most of the literature related to AGV systems focuses on improving their performance in manufacturing settings. In the last 20 years, several articles have addressed issues relevant to healthcare systems. This literature mainly focuses on improving the design and management of AGV systems to handle the specific challenges faced in hospitals, such as interactions with patients, staff, and elevators; adhering to safety standards and hygiene, etc. In Chapter 1, we focus on optimizing the delivery of surgical instrument case carts from material departments to ORs through automated guided vehicles (AGV). We propose a framework that integrates data analysis with system simulation and optimization. We test the performance of the proposed framework through a case study developed using data from a partnering hospital, Greenville Memorial Hospital (GMH) in South Carolina. Through an extensive set of simulation experiments, we investigate whether performance measures, such as travel time and task completion time, improve after a redesign of AGV pathways. We also study the impact of fleet size on these performance measures and use simulation-optimization to evaluate the performance of the system for different fleet sizes. A pilot study was conducted at GMH to validate the results of our analysis. We further evaluated different policies for scheduling the material handling activities to assess their impact on delays and the level of inventory required. Reducing the inventory level of an instrument may negatively impact the flexibility in scheduling surgeries, cause delays, and therefore, reduce the service level provided. On the other hand, increasing inventory levels may not necessarily eliminate the delays since some delays occur because of inefficiencies in the material handling processes. Hospitals tend to maintain large inventories to ensure that the required instruments are available for scheduled surgery. Typically, the inventory level of surgical instruments is determined by the total number of surgeries scheduled in a day, the daily schedule of surgeries that use the same instrument, the processing capacity of the central sterile storage division (CSSD), and the schedule of material handling activities. Using simulation-optimization tools, we demonstrate that integrating decisions of material handling activities with inventory management has the potential to reduce the cost of the system. In Chapter 2 we focus on coordinating OR scheduling decisions with efficient management of surgical instruments. Hospitals pay more attention to OR scheduling. This is because a large portion of hospitals\u27 income is due to surgical procedures. Inventory management of decisions follows the OR schedules. Previous work points to the cost savings and benefits of optimizing the OR scheduling process. However, based on our review of the literature, only a few articles discuss the inclusion of instrument inventory-related decisions in OR schedules. Surgical instruments are classified as (1) owned by the hospital and (2) borrowed from other hospitals or vendors. Borrowed instruments incur rental costs that can be up to 12-25\% of the listed price of the surgical instrument. A daily schedule of ORs determines how many rental instruments would be required to perform all surgeries in a timely manner. A simple strategy used in most hospitals is to first schedule the ORs, followed by determining the instrument assignments. However, such a strategy may result in low utilization of surgical instruments owned by hospitals. Furthermore, creating an OR schedule that efficiently uses available surgical instruments is a challenging problem. The problem becomes even more challenging in the presence of material handling delays, stochastic demand, and uncertain surgery duration. In this study, we propose an alternative scheduling strategy in which the OR scheduling and inventory management decisions are coordinated. More specifically, we propose a mixed-integer programming model that integrates instrument assignment decisions with OR scheduling to minimize costs. This model determines how many ORs to open, determines the schedule of ORs, and also identifies the instrument assignments for each surgery. If the level of instrument inventory cannot meet the surgical requirements, our model allows instruments to be rented at a higher cost. We introduce and evaluate the solution methods for this problem. We propose a Lagrangean decomposition-based heuristic, which is an iterative procedure. This heuristic separates the scheduling problem from the inventory assignment problem. These subproblems are computationally easier to solve and provide a lower bound on the optimal cost of the integrated OR scheduling problem. The solution of the scheduling subproblem is used to generate feasible solutions in every iteration. We propose two alternatives to find feasible solutions to our problem. These alternatives provide an upper bound on the cost of the integrated scheduling problem. We conducted a thorough sensitivity analysis to evaluate the impact of different parameters, such as the length of the scheduling horizon, the number of ORs that can be used in parallel, the number of surgeries, and various cost parameters on the running time and quality of the solution. Using a case study developed at GMH, we demonstrate that integrating OR scheduling decisions with inventory management has the potential to reduce the cost of the system. The objective of Chapter 3 is to develop quick and efficient algorithms to solve the integrated OR scheduling and inventory management problem, and generate optimal/near-optimal solutions that increase the efficiency of GMH operations. In Chapter 2, we introduced the integrated OR scheduling problem which is a combinatorial optimization problem. As such, the problem is challenging to solve. We faced these challenges when trying to solve the problem directly using the Gurobi solver. The solutions obtained via construction heuristics were much farther from optimality while the Lagrangean decomposition-based heuristics take several hours to find good solutions for large-sized problems. In addition, those methods are iterative procedures and computationally expensive. These challenges have motivated the development of metaheuristics to solve OR scheduling problems, which have been shown to be very effective in solving other combinatorial problems in general and scheduling problems in particular. In Chapter 3, we adopt a metaheuristic, Tabu search, which is a versatile heuristic that is used to solve many different types of scheduling problems. We propose an improved construction heuristic to generate an initial solution. This heuristic identifies the number if ORs to be used and then the assignment of surgeries to ORs. In the second step, this heuristic identifies instrument-surgery assignments based on a first-come, first-serve basis. The proposed Tabu search method improves upon this initial solution. To explore different areas of the feasible region, we propose three neighborhoods that are searched one after the other. For each neighborhood, we create a preferred attribute candidate list which contains solutions that have attributes of good solutions. The solutions on this list are evaluated first before examining other solutions in the neighborhood. The solutions obtained with Tabu search are compared with the lower and upper bounds obtained in Chapter \ref{Ch2}. Using a case study developed at GMH, we demonstrate that high-quality solutions can be obtained by using very little computational time

U.S. Army Medical Command’s Medical Treatment Facilities’ Response to SARS-CoV-2 (COVID-19)

Starting in December 2019 to the current time in May 2022, COVID-19 was a devastating pandemic with approximately 440 million cases and 6 million deaths worldwide (Centers for Disease Control and Prevention [CDC], 2021). The United States (US) with roughly 90 million cases and 1 million deaths (CDC, 2021) was one of the epicenters of the outbreak since the beginning. The pandemic has significantly impacted the health systems across the US with unpredictable surges of highly infectious patients with uncertain symptomology and acuity levels, requiring isolation and critical level of care (Brambilla et al., 2021). Based on the findings from the available literature and case reports of the pandemic impacts and responses, it is clear that the pandemic has put unprecedented pressure on US healthcare facilities, which are not intentionally designed to respond to a pandemic of this scale. Hospitals have struggled to adapt to the increased care complexity, infection control requirements, and the sheer volume of patients (Cohen et al., 2021). The need for such adaptability in the healthcare system has never been clearer as we have observed major deficiencies in how facilities have responded to the pandemic and how the buildings have failed to facilitate and support the required changes in spaces and operations

Agent-based simulation patient model for colon and colorectal cancer care trajectory

ABSTRACT: Colon and Colorectal cancer are a diagnosis of particular concern for older Canadians. They are the second cancer in terms of rate of incidence and mortality among Canadians after lung cancer. Treatment of colon and colorectal cancer requires a complex decision-making process of treatment. These treatments may involve surgery and either pre- or post-operative radiation or chemotherapy, which can have a great impact on the quality of life of patients due to the rigorous requirements of treatment and the inconvenient side effects. This paper is the first developmental step of an agent-based simulation platform aiming at simulating colon and colorectal cancer patient care trajectories in a hospital. In this study, we describe a virtual patient agent, which includes a cancer evolution model, capable of replicating cancer behavior in response to treatment. Simulation results show promising interpolation results with respect to chemotherapy dosage and radiotherapy dosage. However, the model ability to interpolate different administration protocols is still limited, and therefore require calibration for each protocol

Empirical review of NHS Estates ergonomic drawings

In the late 1970s and the early 1980s the Department of Health developed an ergonomic database, in the form of ergonomic drawings, to act as guidance for the design of new hospitals and the adaptation of old buildings. But there is very little peer-reviewed empirical evidence published to support the recommended drawings. The project used ergonomic methodologies to review the ergonomic drawings of single bed spaces and toilet / shower facilities on adult acute wards and intensive care units (ICUs) in terms of nursing staff carrying out specific clinical tasks. The objectives were to (1) review the complex interfaces using ergonomic task analysis methods from other industries, (2) to provide up-to-date ergonomic information to designers (architects) and planners on spatial requirements for the above units, and (3) provide recommendations for the development of future guidance on functional space requirements. Five PFI hospitals were visited to capture a range of `actual' space dimensions in the forms of coded AutoCAD drawings and relevant photos for the application of building the mock-ups for the Functional Space Experiments (FSEs). The field observations were conducted over 5 weeks at two local hospitals. A total of 100 nursing tasks with 74 nurses were recorded and analysed by using Hierarchical Task Analysis (HTA) and Link Analysis (LA). FSEs were conducted with 36 nurses for the ICU, adult acute ward and toilet/shower mock-ups resulting in 190 composite link analysis diagrams. The results from the FSEs were described as an `ergonomic envelope', the incompressible functional, space required for clinical tasks in these areas. The average spatial requirement of ward bed space envelope was 11.14m2 (average width of 3.21 m, length of 3.47m). The average spatial requirement of toilet / shower envelope was 5.43mz (average width 2.08m, length of 2.61m). The average spatial requirement of ICU bed space envelope was 23.47m2 (average width of 4.96m, length of 4.80m). It was recommended that both the width and the length should be given together with the area for an envelope, and hospital planners and architects should regard ergonomic envelope as a "core space" in the hospital development. Finally a 4-step protocol for future development, revision and testing of ergonomic drawings were presented, and the potential further study areas were suggested

A healthcare space planning simulation model for Accident and Emergency (A&E)

The National Health Service (NHS) in the United Kingdom provides a range service for its population including primary care and hospital services. The impact of the 2008 economic and financial crises prompted a tightening of public budgets including health. Over the next few years, and most likely beyond, the NHS is planning for unprecedented levels of efficiency saving in the order of £ billions. With little doubt, the NHS will need to review its way of working will need to do more with less. Simulation is an established technique with applications in many industries including healthcare. Potentially, there are huge opportunities for simulation use to make further inroads in the field of healthcare. Despite the potential, arguably, simulation has failed to make a significant impact in health. Some evidence has tended to suggest that within health there has been poor adaption along with poor linkage to real-world problems, as perceived by healthcare stakeholders. The aim of this thesis is to develop a model to help address real-world healthcare issues as recognised by healthcare stakeholders. In doing so, this thesis will focus on a couple of real-world problems, namely: What space is needed to meet service demand, when is it needed and what will it cost? What space do we have, how can it be used to meet service demand and at what cost? The developed simulation space demand model will demonstrate its value modelling dynamic systems over static models. The developed models will also show its value highlighting space demand issues by groups of patients, by time of day. Real, readily available data (arrival and length of stay, by patient group) would drive the model inputs, supporting ease of use and clarity for healthcare stakeholders. The model was modular by design to support rapid reconfiguration. Dynamically modelled space information allows service managers and Healthcare Planners to better manage and organise their space in a flexible way to meet service requirements. This work will also describe how space demand can linked with building notes to determine Schedules of Accommodation which can be used to cost floor space and consequent building or refurbishment costs. Furthermore, this information could be used to drive business plans and to develop operational cost pertaining to the floor area. This body of work debates using function-to-space ratios and attaching facilities management cost. Our findings suggest great variance in function-to-space ratios. Our findings also suggest that moving to median or lower quartile function-to-space ratios could potentially save hospitals £ millions in facilities management costs. This thesis will reflect on the level of modelling taking place in the healthcare industry by non-academic healthcare modellers, sometimes collectively known as Healthcare Planners, the Healthcare Planning role in space planning and their links with healthcare stakeholders. This reflection will also consider whether healthcare stakeholders perceive a great need for academic healthcare modelling, if they believe their modelling needs are met by Healthcare Planners. A central theme of this thesis is that academic modelling and Healthcare Planning have great synergy and that bringing together Healthcare Planners’ industry knowledge and stakeholder relationships with academic know-how, can make a significant contribution to the healthcare simulation modelling arena

Patient model for colon and colorectal cancer care trajectory simulation

Almost half Canadians (41% women and 46% men) will develop cancer during their lifetime and 88% of them are older than fifty [1]. Lung, breast, colon, colorectal and prostate cancers represent more than half of all new cancer cases (52%). Breast cancer is the leading type of cancer among women, while colon and colorectal cancer are the third most common cancer among men and women. Cancer is the leading cause of death in Canada and in the world with 29.8% of the population affected, compared to 26.6% for cardiovascular diseases [2]. Furthermore, in 2000, cancer was the fourth most expensive disease in Canada with $17.4 billion spent. Colon and Colorectal cancer are considered the second leading cause of cancer death among men and the third among women. Cancer treatment is characterized by the convergence of many services including ambulatory, hospitals, clinical, nutritional, psychological, and sports medicine, which coordination and integration condition treatment success and patient quality of life. In order to reduce the impact of this disease and increase the cure rate and the patient quality of life, it is necessary to develop and evaluate new therapeutic and organizational approaches. This study deals with this goal and is the first methodological step toward creating a simulation platform of care trajectories of colorectal cancer patients. This simulation platform aims at simulating many elements of the hospital environment, from care resources to patient physiology and psychology profiles, in order to evaluate the many impacts of organizational changes of care trajectories. First, this paper describes the general scope of this simulation project and presents a state of the art of agentbased simulation. Next, the general conceptual model of the simulation is described. Then, we present our cancer evolution, which is then tested and validated using two separate experiments

Patient Experience Informs Health Care Strategies in Irish Hospitals

Patients are central to health care facilities and institutions; therefore, a dire need arises to include feedback of their experience in the decision-making process. Patient experience is increasingly recognised as one of the three pillars of quality in healthcare alongside clinical effectiveness and patient safety. A comprehensive literature review (more than 2500 peer-reviewed articles) has identified five key frameworks for patient experience including: UK Picker Institute Principles and US H-CAHPS. The frameworks have enabled the identification of a potential range of patient experience dimensions and helped in grouping them into nine categories. However, there are still opportunities to address research gaps in developing a unified index to represent patient experience, and offering a practical framework to inform quality improvement strategies in hospitals. An extensive exploratory study is developed to complement the literature review. This study aims to confirm the importance of the identified nine dimensions from patients’ views, explore staff perceptions of patient experience, then compare patients’ views and staff’s perceptions. Semistructured interviews with 77 participants (26 senior staff members and 51patients) across three major acute Irish hospitals are conducted. Five important dimensions are highlighted from patients’ responses such as: staff communication and being treated with respect. While dimensions such as: continuity of care and involving family members are identified as less important. While staff in this study perceive dimensions such as quicker access to care and informing the patient with their status updates as more significant in shaping the patient experience. Both the exploratory study and literature review outcomes have contributed to the design of a patient experience questionnaire which examine dimensions that matter most to patient experience. The questionnaire is included as a component of a multi-method framework that integrated data analytics, simulation modelling, and optimisation. With an ultimate objective to improve patient experience, the proposed framework has been piloted in an Emergency Department of one of the leading and busiest university hospitals in Dublin. Fifty-eight patients responded to the questionnaire and their responses are analysed using a Partial Least Squares (PLS) model. PLS results have identified access to care as a negative predictor to patient experience. Improvement strategies such as increasing the internal capacity of the department are proposed by the management team to improve the Length of Stay (LOS) and provide better access to care. To examine and assess the impact of proposed strategies on LOS, a simulation model has complemented the solution framework. Results have showed that internal capacity of an ED has no direct impact on LOS and does not act as a performance constraint. However, other factors such as increasing downstream department’s capacity and the staffing levels can lead to a reduction in LOS (up to 25%)

OECD reviews of higher education in regional and city development, State of Victoria, Australia

With more than 5.3 million inhabitants Victoria is the second most populous state in Australia. Once a manufacturing economy, Victoria is now transforming itself into a service and innovation-based economy. Currently, the largest sectors are education services and tourism. In terms of social structure, Victoria is characterised by a large migrant population, 24% of population were born overseas and 44% were either born overseas or have a parent who was born overseas. About 70% of the population resides in Melbourne. Victoria faces a number of challenges, ranging from an ageing population and skills shortages to drought and climate change and increased risk of natural disasters. Rapid population growth, 2% annually, has implications for service delivery and uneven development as well as regional disparities. There are barriers to connectivity in terms of transport and infrastructure, and a high degree of inter-institutional competition in tertiary education sector. The business structure in Victoria includes some highly innovative activities such as in biotechnology, but other sectors, especially those with high number of small and medium-sized enterprises, are lagging behind. Most of the larger manufacturing enterprises are externally controlled and there is uncertainty over the long term investments they will make in the state, as well as the place of Victoria in the global production networks

The Sanitation Triangle

This open access book deals with global sanitation, where SDG 6.2 sets a target of enabling access to sanitation services for all, but has not yet been achieved in low- and middle-income countries. The transition from the United Nations MDGs to the SDGs requires more consideration based on the socio-cultural aspects of global sanitation. In other words, equitable sanitation for those in vulnerable situations could be based on socio-cultural contexts. Sanitation is a system that comprises not only a latrine but also the works for the treatment and disposal of human waste. Sanitation systems do not function by themselves but have significance only through social management. The process of decision-making also largely depends on socio-cultural conditions, and the importance of sanitation needs to be socially acknowledged. The health benefits of sanitation improvement—among the significant contributions of sanitation—also need to be considered in the socio-cultural milieu. Further, the social-culture itself is affected, and potentially even created, by sanitation. In this context, more progress on the improvement of sanitation requires a more holistic approach across disciplines. In this book, we present the concept of the Sanitation Triangle, which considers the interconnections of health, materials, and socio-culture in sanitation, as a holistic approach, and the case studies based on the Sanitation Triangle by diverse disciplines such as Cultural Anthropology, Development Studies, Health Sciences, Engineering, and Science Communication. By the deep theoretical examinations and inter-dialogues between the different disciplines, this book explores the potentialities of inter-disciplinary studies on global sanitation

Un modèle de patient pour la simulation des parcours de soin

RÉSUMÉ : Le cancer est la première cause de mortalité au Canada et presque la moitié de la population canadienne en développera un. Le traitement du cancer se caractérise par la convergence de nombreux services (ambulatoire, hospitalier, clinique, nutritionnel, etc.) et donc une complexité organisationnelle pour leur intégration. Pour diminuer l’impact de cette maladie sur la société, augmenter le taux de guérison et la qualité de vie, des mesures de standardisation de l’approche thérapeutique ont été mises en place. Ainsi pour améliorer ces standards il est nécessaire de tester régulièrement de nouvelles approches autant thérapeutiques qu’organisationnelles. Mais ces tests sont couteux et longs à mettre en place. Ce mémoire développe les bases d’une plateforme de simulation capable de simuler l’ensemble de la trajectoire de soin du cancer colorectal, de l’arrivée du patient jusqu’à la fin de son traitement, tout en prendre en compte les ressources utilisées ainsi que l’aspect physiologique et psychologique des patients. Celle-ci permettrait d’effectuer un grand nombre de tests organisationnels en quelques heures et aidera à la gestion de l’hôpital. Plus spécifiquement ce mémoire détaille un modèle d’évolution du cancer colorectal en fonction du temps et des traitements qui lui sont appliqués sur l’ensemble de son développement de son apparition à la fin des traitements n’effectuent pas le patient. De plus, un modèle préliminaire de la prise de décision du médecin quant au traitement à suivre par le patient est également décrit. Le modèle d’évolution du cancer, en plus de servir de base pour la plateforme de simulation, pourra servir d’outil d’aide à la décision pour le traitement des patients.----------ABSTRACT : Cancer is the leading cause of death in Canada, and almost half of the Canadian population will develop one. The treatment of cancer is characterized by the convergence of many services (ambulatory, hospital, clinical, nutritional, etc.) and therefore an organizational complexity for their integration. To reduce the impact of this disease on society, increase the cure rate and quality of life, action to standardize the therapeutic approach were implemented. And to improve these standards it is necessary to test regularly _ new therapeutic approaches and organizational. But these tests are expensive and time consuming to implement. This paper develops the foundations of a simulation platform able to simulate the whole trajectory of care for colorectal cancer, when the patient arrives until the end of treatment, while taking into account the resources used as well as physiological and psychological aspects of patients. This would allow doing a large number of organizational tests in a few hours and helping the management of the hospital. More specifically, this paper describes a model of evolution of the colorectal cancer over time and treatments, over his entire development time from his appearance until the end of patient’s treatment. In addition, a preliminary model of decision-making by the doctor for treatment to be followed by the patient is also disclosed. The evolution model of cancer, in addition to serving as a basis for the simulation platform, can be used as a tool for decision support in the treatment of patients