Modelling and solving healthcare decision making problems under uncertainty

The efficient management of healthcare services is a great challenge for healthcare managers because of ageing populations, rising healthcare costs, and complex operation and service delivery systems. The challenge is intensified due to the fact that healthcare systems involve various uncertainties. Operations Research (OR) can be used to model and solve several healthcare decision making problems at strategic, tactical and also operational levels. Among different stages of healthcare decision making, resoure allocation and capacity planning play an important role for the overall performance of the complex systems. This thesis aims to develop modelling and solution tools to support healthcare decision making process within dynamic and stochastic systems. In particular, we are concerned with stochastic optimization problems, namely i) capacity planning in a stem-cell donation network, ii) resource allocation in a healthcare outsourcing network and iii) real-time surgery planning. The patient waiting times and operational costs are considered as the main performance indicators in these healthcare settings. The uncertainties arising in patient arrivals and service durations are integrated into the decision making as the most significant factors affecting the overall performance of the underlying healthcare systems. We use stochastic programming, a collection of OR tools for decision-making under uncertainty, to obtain robust solutions against these uncertainties. Due to complexities of the underlying stochastic optimization models such as large real-life problem instances and non-convexity, these models cannot be solved efficiently by exact methods within reasonable computation time. Thus, we employ approximate solution approaches to obtain feasible decisions close to the optimum. The computational experiments are designed to illustrate the performance of the proposed approximate methods. Moreover, we analyze the numerical results to provide some managerial insights to aid the decision-making processes. The numerical results show the benefits of integrating the uncertainty into decision making process and the impact of various factors in the overall performance of the healthcare systems

Optimising cardiac services using routinely collected data and discrete event simulation

Background: The current practice of managing hospital resources, including beds, is very much driven by measuring past or expected utilisation of resources. This practice, however, doesn’t reflect variability among patients. Consequently, managers and clinicians cannot make fully informed decisions based upon these measures which are considered inadequate in planning and managing complex systems. Aim: to analyse how variation related to patient conditions and adverse events affect resource utilisation and operational performance. Methods: Data pertaining to cardiac patients (cardiothoracic and cardiology, n=2241) were collected from two major hospitals in Oman. Factors influential to resource utilisation were assessed using logistic regressions. Other analysis related to classifying patients based on their resource utilisation was carried out using decision tree to assist in predicting hospital stay. Finally, discrete event simulation modelling was used to evaluate how patient factors and postoperative complications are affecting operational performance. Results: 26.5% of the patients experienced prolonged Length of Stay (LOS) in intensive care units and 30% in the ward. Patients with prolonged postoperative LOS had 60% of the total patient days. Some of the factors that explained the largest amount of variance in resource use following cardiac procedure included body mass index, type of surgery, Cardiopulmonary Bypass (CPB) use, non-elective surgery, number of complications, blood transfusion, chronic heart failure, and previous angioplasty. Allocating resources based on patient expected LOS has resulted in a reduction of surgery cancellations and waiting times while overall throughput has increased. Complications had a significant effect on perioperative operational performance such as surgery cancellations. The effect was profound when complications occurred in the intensive care unit where a limited capacity was observed. Based on the simulation model, eliminating some complications can enlarge patient population. Conclusion: Integrating influential factors into resource planning through simulation modelling is an effective way to estimate and manage hospital capacity.Open Acces

Healthcare Logistics: the art of balance

Healthcare management is a very complex and demanding business. The pro - cesses involved – operational, tactical and strategic – are extremely divers, sophisticated, and we see medical-technological advancements following on each other’s heels at breathtaking speed. And then there is the constant great pressure exerted from many sides: ever-increasing needs and demands from patients and society, thinking about organizations, growing competition, necessity to incorporate these rapidly succeeding medical-technological advancements into the organization, strict cost containment, growing demand for healthcare, and a constant tightening of budgets. These developments force healthcare managers in the individual organizations to find a balance between said developments, the feasibilities of organization in question, and the desired healthcare outcomes in an ever-changing world. The search for individual organizational balances requires that the world of professional competencies, i.e. the clinicians, and the world of healthcare managers should speak the same language when weighing the various developments and translating the outcomes into organizational choices. For the clinicians to make the right choices they must be facilitated to appraise the effects of their choices on organizational outcomes. Likewise, the healthcare managers’ decision- making process should include the effects on the medical policies pursued by the individual clinicians in the own organization. This thesis places a focus on developing methods for allocation of hospital resources within a framework that enables clinicians and healthcare managers to balance the developments on the various levels, thus providing a basis for policymaking

Robust Optimization Framework to Operating Room Planning and Scheduling in Stochastic Environment

Arrangement of surgical activities can be classified as a three-level process that directly impacts the overall performance of a healthcare system. The goal of this dissertation is to study hierarchical planning and scheduling problems of operating room (OR) departments that arise in a publicly funded hospital. Uncertainty in surgery durations and patient arrivals, the existence of multiple resources and competing performance measures are among the important aspect of OR problems in practice. While planning can be viewed as the compromise of supply and demand within the strategic and tactical stages, scheduling is referred to the development of a detailed timetable that determines operational daily assignment of individual cases. Therefore, it is worthwhile to put effort in optimization of OR planning and surgical scheduling. We have considered several extensions of previous models and described several real-world applications. Firstly, we have developed a novel transformation framework for the robust optimization (RO) method to be used as a generalized approach to overcome the drawback of conventional RO approach owing to its difficulty in obtaining information regarding numerous control variable terms as well as added extra variables and constraints into the model in transforming deterministic models into the robust form. We have determined an optimal case mix planning for a given set of specialties for a single operating room department using the proposed standard RO framework. In this case-mix planning problem, demands for elective and emergency surgery are considered to be random variables realized over a set of probabilistic scenarios. A deterministic and a two-stage stochastic recourse programming model is also developed for the uncertain surgery case mix planning to demonstrate the applicability of the proposed RO models. The objective is to minimize the expected total loss incurred due to postponed and unmet demand as well as the underutilization costs. We have shown that the optimum solution can be found in polynomial time. Secondly, the tactical and operational level decision of OR block scheduling and advance scheduling problems are considered simultaneously to overcome the drawback of current literature in addressing these problems in isolation. We have focused on a hybrid master surgery scheduling (MSS) and surgical case assignment (SCA) problem under the assumption that both surgery durations and emergency arrivals follow probability distributions defined over a discrete set of scenarios. We have developed an integrated robust MSS and SCA model using the proposed standard transformation framework and determined the allocation of surgical specialties to the ORs as well as the assignment of surgeries within each specialty to the corresponding ORs in a coordinated way to minimize the costs associated with patients waiting time and hospital resource utilization. To demonstrate the usefulness and applicability of the two proposed models, a simulation study is carried utilizing data provided by Windsor Regional Hospital (WRH). The simulation results demonstrate that the two proposed models can mitigate the existing variability in parameter uncertainty. This provides a more reliable decision tool for the OR managers while limiting the negative impact of waiting time to the patients as well as welfare loss to the hospital

Improvement in operating theatre efficiency through better measurement and scheduling

An operating theatre complex at a South African private hospital was measured against a framework to gauge its effectiveness and efficiency. Eight key metrics are proposed against which the complex recorded an overall score of 5/12. Simulated alternative states explored scheduling and rostering stratagems to broadly improve the usefulness of the theatre and its utilisation specifically. Modifications to the management strategy were made. These implementations were simulated in Rockwell Arena. The simulated states showed significant improvement in overall theatre utilisation and effectiveness, moving from a current state utilisation of 47 % to a theoretical level of 85 % whilst the effectiveness score rose from 5/12 to 11/12. This change is significant and meets established international best practice benchmarks. Major issues include a lack of scheduling, planning and control by support functions, poor adherence to schedules by surgeons and interpersonal politics between the two groups

The application of innovative virtual world technologies to enhance healthcare education

The World Wide Web has evolved leading to the development of three- dimensional virtual worlds. These are online, accessible environments through which a user may engage, communicate and interact via their digital self, known as their avatar. These virtual worlds offer the opportunity for further content to be generated in order to provide new environments and simulations. This research work explores the potential of virtual worlds in providing an educational platform for healthcare professionals. In order to establish this, the effectiveness of a virtual world environment was determined through the use of a custom-built virtual world operating theatre, which was utilised to train operating theatre novices in preparation for the real-life environment. Following the application of a virtual world environment, this research explored the development of a virtual patient scenario for training healthcare professionals. The virtual patient scenario focused on the management of adverse events associated with medical infusion devices with a nurse user group assessing the simulation face validity. The next step was to devise a methodology to develop a series of immersive virtual patients. This involved the use of allied web technologies to produce a robust, reproducible method of 3D virtual patient generation. Three virtual patients were constructed, with distinct surgical pathologies at three levels of increasing complexity. Subsequently the face, content and construct validity of the virtual patients was established to differentiate surgeons of different training grades. Finally the virtual patients were utilised to emulate real clinical situations, in which handoff of patient information occurred. The virtual patients were used to establish if the quality of handoff impacted on the subsequent patient management in a simulated setting. Overall this research has demonstrated the efficacy of virtual world environments and simulations in providing an alternative educational platform for healthcare professionals.Open Acces

Discrete Event Simulations

Considered by many authors as a technique for modelling stochastic, dynamic and discretely evolving systems, this technique has gained widespread acceptance among the practitioners who want to represent and improve complex systems. Since DES is a technique applied in incredibly different areas, this book reflects many different points of view about DES, thus, all authors describe how it is understood and applied within their context of work, providing an extensive understanding of what DES is. It can be said that the name of the book itself reflects the plurality that these points of view represent. The book embraces a number of topics covering theory, methods and applications to a wide range of sectors and problem areas that have been categorised into five groups. As well as the previously explained variety of points of view concerning DES, there is one additional thing to remark about this book: its richness when talking about actual data or actual data based analysis. When most academic areas are lacking application cases, roughly the half part of the chapters included in this book deal with actual problems or at least are based on actual data. Thus, the editor firmly believes that this book will be interesting for both beginners and practitioners in the area of DES

Decision support systems for task scheduling: applications in manufacturing and healthcare

Esta Tesis se centra en el problema de la programación de tareas. Aunque pueden encontrarse diferentes definiciones de la programación de tareas en la literatura, aquí se define como la asignación de un número de tareas – acciones individuales que deben realizarse para completar un determinado proceso-, a un conjunto de recursos, en momentos de tiempo específicos. Pueden encontrarse ejemplos de programación de tareas en muchos contextos, como por ejemplo, el orden en el que deben fabricarse las diferentes partes de un coche, la asignación de quirófanos y cirujanos a intervenciones quirúrgicas en un hospital, o el orden en el que deben ser servidos los clientes de un restaurante. La programación de tareas supone un elemento clave en muchas compañías, en el campo de los servicios y en el de la fabricación, ya que es esencial para la coordinación del trabajo entre los diferentes actores involucrados, tales como departamentos, recursos (físicos y humanos) o entidades externas. En la mayoría de los casos, la programación de tareas conlleva trabajar con grandes cantidades de datos relacionados con el proceso y gestionar correctamente el conjunto de restricciones que controlan el proceso. Como consecuencia de esto, la programación de tareas suele hacerse con ayuda de herramientas informáticas que ofrecen algún tipo de soporte para el decisor. A este respecto, el auge de las Tecnologías de la Información (TI) en las últimas décadas ha ayudado enormemente al desarrollo de sistemas computarizados que ofrecen soporte a la toma de decisiones – Sistemas de Soporte a la Decisión (SSD) – en muchos ámbitos, incluyendo la programación de tareas. Además, ha habido un notable aumento en la capacidad computacional que ha hecho posible afrontar problemas de programación de tareas que se consideraban irresolubles hace algunos años. A pesar de estos avances, se ha detectado un gap entre teoría y práctica al llevar estas nuevas condiciones a la práctica, que puede ser demostrado por el limitado número de sistemas que se han implementado y aceptado por los usuarios satisfactoriamente. La hipótesis de trabajo de esta Tesis es que, para reducir este gap entre teoría y práctica, estos sistemas deberían considerar un conjunto de aspectos que se han estudiado en la literatura pero que no se han tenido en cuenta en el proceso de implementación, tales como el rol del decisor en el sistema, el contexto organizacional donde se toman las decisiones para la programación o la consideración de la programación como un proceso dinámico. Normalmente, cada vez que una empresa necesita implementar un SSD para la programación de tareas (SSDPT), es posible elegir entre dos opciones: adquirir una solución off-the-shelf, o diseñar y desarrollar una herramienta personalizada. Cuando se elige la primera opción, normalmente la solución no se adapta perfectamente a las actividades de la empresa, y considerando que la programación de tareas es muy dependiente del contexto, esta opción puede resultar en una situación muy documentada en la literatura en la que se consigue una implementación muy limitada en la que hay diferentes sistemas de información trabajando en paralelo para tener en cuenta las diferentes especificidades de la empresa. Por otro lado, si se opta por la segunda opción, esta suele derivar en largos tiempos de implementación con resultados pobres, ya que el equipo de desarrollo podría no tener en cuenta los errores y aciertos de otras implementaciones, tales como las funcionalidades que un sistema debería tener o los perfiles que se debería dar a los diferentes usuarios. Como resumen podríamos decir que el diseño y la implementación de SSDPT tienen un conjunto de problemas que constituyes una de las principales causas del gap existente entre la teoría de la programación de tareas y su implementación en la práctica. Para mejorar la actividad de diseño y desarrollo de SSDPT, el objetivo de esta tesis es proponer un framework común para el desarrollo de SSDPT. Para asegurar su validez y analizar su rango de aplicación, se analiza su factibilidad en dos sectores de aplicación, fabricación y salud, y se llevan a cabo dos casos de estudio en estos sectores. Para conseguir el objetivo general de la Tesis, se consideran un conjunto de objetivos específicos: 1. Proponer un framework para el diseño y desarrollo de SSDPT. • El framework tiene en cuenta todos los problemas detectados en la literatura que tienen que ver con los fallo a la hora de implementar este tipo de sistemas. Este framework se detalla mediante un conjunto de perspectivas. 2. Analizar las implementaciones existentes de SSDPT para analizar la alineación del framework propuesto con las implementaciones existentes de este tipo de sistemas en los dos campos de aplicación. • Se lleva a cabo una revisión sistemática de la literatura en SSDPT en fabricación. Las contribuciones revisadas se clasifican de acuerdo a las funcionalidades que presentan. Se analizan y discuten una serie de resultados y conclusiones de los mismos. Además se realiza una revisión de SSDPT comerciales para la programación de quirófanos. Estas contribuciones también se clasifican según sus funcionalidades y se presentan y discuten una serie de resultados y conclusiones. 3. Levar a cabo el diseño e implementación de dos SSDPT de acuerdo con el framework propuesto para demostrar su validez. • Basándonos en el framework un SSDPT para fabricación y un SSDPT para la programación de quirófanos han sido propuestos: i. El SSDPT para fabricación se implementó para una empresa de fabricación situada en Sevilla. Primero se describe el contexto en el que el sistema actúa y el problema considerado. Después se estudian los principales casos de uso del sistema y se relacionan con el framework propuesto. Más tarde, se proponen una serie de métodos de resolución eficientes para el problema analizado. Finalmente, se realiza una breve discusión sobre los principales resultados de implementación del sistema. ii. El SSDPT para programación de quirófanos se implementó en un hospital situado en Sevilla. Primero se describe el contexto en el que el sistema actúa y el problema considerado. Después se estudian los principales casos de uso del sistema y se relacionan con el framework propuesto. Más tarde, se proponen una serie de métodos de resolución eficientes para el problema analizado. Finalmente, se realiza una breve discusión sobre los principales resultados de implementación del sistema.This thesis focuses on the problem of task scheduling. Although slightly different definitions of task scheduling can be found in the literature, here it is defined as the allocation of a number of tasks - single actions that must be performed to complete a specific process-, to a set of resources, at specific moments in time. Examples of task scheduling can be found in many settings, as for example, the order in which the different parts of a car have to be manufactured in a set of machines, the allocation of operating rooms and surgeons to the surgical interventions in a hospital, or the order in which the customers of a restaurant should be served. Clearly, task scheduling is a core activity of many companies, both in manufacturing and in services, as it is essential for the coordination of the work between the different involved actors, such as departments, resources (human and physical) or external entities. In most settings, task scheduling involves treating large amounts of data related to the process and properly handling the set of constraints controlling this process. As a consequence, task scheduling is usually carried out with the help of computer tools that offer some type of support to the decision maker. In this regard, the rising of Information Technologies (ITs) in the last decades has helped enormously to develop computer systems providing support for decision making - i.e. Decision Support Systems (DSSs) - for many decisions, including task scheduling. At the same time, there has been a notable increase in computer capacity that has made possible facing task scheduling problems that were considered unsolvable some years ago. Despite these advances, an important gap between theory and practice has been found when translating these new conditions into practice, as it can be proven by the relatively short number of documented systems that have been correctly implemented and accepted by users. The working hypothesis in this Thesis is that, in order to reduce this gap between theory and practice, these tools should consider a number of aspects that have been studied in the literature but that have not been taken into account in practice during the implementation process, such as the role of the decision makers in these tools, the organisational context where scheduling decisions take place or the consideration of scheduling as a dynamic process. Typically, each time a company requires to implement of a DSS for task scheduling, in the following DSSTS, it faces two different options: either acquiring an off-the-shelf solution, or designing and developing an in-house tool. If the former option is chosen, the acquired solution may not fit perfectly into the activities of the company, and, since task scheduling is company-specific, this approach may result in a situation widely documented in the literature where there exist limited implementations that needs information systems working in parallel to deal with the specificities of the company. On the contrary, the second option usually derives in large implementation times with poor results, as the development team may not take into account errors or successes from former implementations, such as the functionalities that the system should include or the profiles required for the decision makers among others. As a summary, the design and implementation of DSSTS suffer a number of problems which constitute a root cause for the existing gap between the scheduling theory and its implementation into practice. In order to improve the activity of designing and developing DSSTS, the aim of this thesis is to propose a common framework for the development of DSSTS. In order to ensure the validity and range of application of this framework, its feasibility is analysed within two specific fields of applications, namely manufacturing and healthcare, and two implementation case studies are conducted within these fields. In order to fullfil this general objective, a number of specific objectives can be detailed: 1. To propose a framework for the design and development of DSSTS. • This framework address all the issues found in literature regarding the common failures when implementing this type of systems. A number of perspectives of the framework are given in order to properly detail it. 2. To analyse existing implementations of DSSTS in order to check the alignment of the framework proposed with the task scheduling systems implemented in the two sectors chosen for the evaluation of the framework. • A systematic literature review on manufacturing DSSTS is carried out. The reviewed contributions are classified according to their functionalities. A number of findings and conclusions about these findings are discussed. Additionally, a review on commercial operating room DSSTS is done. These contributions are also classified according to their functionality and a number of findings and conclusions about these findings are discussed. 3. To conduct the design and implementation of two DSSTS according to the proposed framework in order to demonstrate its applicability. • Based on the proposed framework, a manufacturing DSSTS and an operating room DSSTS are implemented: i. The manufacturing DSSTS is applied to a real manufacturing company in Sevilla. First, we describe the context where the DSSTS is deployed and the problem addressed, i.e. the hybrid flowshop scheduling problem with missing operations. Then, the main use cases of the DSSTS are discussed and related to the framework. Next, a set of efficient solution procedures for the problem under study are proposed. And finally, a brief discussion on the main results of the implementation of the DSSTS is carried out. ii. The operating room DSSTS is applied to a real hospital in Sevilla. First, we describe the context where the DSSTS is deployed and the problem addressed, i.e. the the operating room scheduling problem. Then, the main use cases of the DSSTS are discussed and related to the framework. Next, a set of efficient solution procedures for the problem under study are proposed. And finally, a brief discussion on the main results of the implementation of the DSSTS is carried out