Open Access
Simulation and optimization methods to improve the management of resources and patients in health services. Application to emergency departments
(2019) Cildoz Esquíroz, Marta; Mallor Giménez, Fermín; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Gobierno de Navarra / Nafarroako Gobernua
The aim of this thesis is to contribute to the sustainability of public health services by means of data analysis and through the development and application of Operational Research methods and techniques for modeling and analyzing real planning and management problems generally affecting the public health sector and Emergency Departments (EDs) in particular. The focus of the research is on the development of methods of analysis that will yield practicable solutions to improve the efficiency and quality of patient care and working conditions of the health staff. A hospital ED provides medical and/or surgical care to patients arriving in need of immediate attention. The highly stochastic environment of these departments is especially difficult to manage due to the variability of the patient arrival rate, patient severity, and (material and human) health resource requirements. They also have to provide a 24/7 service, where physicians are required to work night, day and weekend shifts, and take on different assignments.reflecting the resource consumption (including the medical staff) required for treatment. A guideline is provided for the construction of a mathematical model of the ED designed to overcome some of the shortcomings of oversimplified queuing theorymodels and capture some important issues that previous simulation models have overlooked. The first part of the thesis addresses the problem of patient-to-physician allocation following triage. It offers a proposal for new allocation rules which prove to outperform the common cyclic allocation approach by taking into account a factor usually neglected by patient-flow management policies: i.e., the workload stress experienced by physicians, which is measured in real time using a method proposed and analyzed in this thesis. The stress score is used as the KPI to assess the performance of current patient-flow management policies and as a criterion for designing new ones. This thesis also illustrates the successful implementation of one of the proposed rules, from initial concept to practical application in the hospital. The tested allocation rule outperforms the current cyclic one, as demonstrated by using the simulation model and analysis of the real data gathered during the pilot test. The second part of the thesis addresses the physician scheduling problem, which is a combinatorial optimization problem posing particular difficulty when all the constraints and objectives observed in practice are considered. The problem is modeled by means of mathematical programming, and thus cannot be solved in practice by commercial software. This leads to the development of a new solution heuristic. A key feature of this algorithm is the greedy constructive phase, which is guided by solving a linear problem in combination with a memory structure. Initial good solutions are very quickly obtained, but they can be unfeasible in heavily constrained cases. The subsequent improvement phase combines a repair strategy based on variable neighborhood search with network optimization. This is the first proposal for such a strategy. A computational analysis and a real-case solution demonstrate the quality of the solutions and the good behavior of the methodology. The research presented in this thesis fulfills the following objectives: to propose a quantitative framework (based on simulation models and their combination with optimization procedures) for the analysis of problems involved in the dimensioning and assessment of management policies in hospital emergency services; to develop a methodology for the real-time assessment of pending workload stress in physicians; to provide new patient-to-physician allocation methods with criteria including the workload and stress balancing across physicians, and patient service quality; to analyze alternatives to pure priority rules for managing the queue of patients awaiting initial emergency assessment by a physician or reevaluation following tests and/or diagnosis; to design efficient algorithms for solving the physician work-shift assignment problem taking into account all real ergonomic constraints while balancing the workload.
Open Access
Accumulating priority queues versus pure priority queues for managing patients in emergency departments
(Elsevier, 2019) Cildoz Esquíroz, Marta; Ibarra, Amaia; Mallor Giménez, Fermín; Institute of Smart Cities - ISC
Improving the quality of healthcare in emergency departments (EDs) is at the forefront of many hospital managers’ efforts, as they strive to plan and implement better patient flow strategies. In this paper, a new approach to manage the patient flow in EDs after triage is proposed. The new queue discipline, named accumulative priority queue with finite horizon and denoted by APQ-h, is an extension of the accumulative priority queue (APQ) discipline that considers not only the acuity level of patients and their waiting time but also the stage of the healthcare treatment. APQ disciplines have been studied in the literature from a queueing theory point of view, which requires assumptions rarely found in real EDs, such as homogeneity in the patient arrival pattern and only one service stage. The APQ-h discipline accumulates priority from the point of waiting for the first physician consultation until the moment the waiting time exceeds the upper time limit set to access the physician after the patient's arrival. A recent study shows that a management strategy of this type is applied in practice in several Canadian EDs. The main aim of this paper is to explore the implementation of APQ-h managing policies in a real ED. For this purpose, a simulation model replicating a real ED is developed. This simulation model is also used to obtain the optimal APQ type polices through a simulation-based optimization method that solves a multi-objective and stochastic optimization problem. Arrival to provider time and total waiting time in the ED are considered to be the key ED performance indicators. An extensive computational analysis shows the flexibility of the APQ-h and APQ discipline and their superiority over other pure priority disciplines in a real setting and in a variety of ED scenarios. In addition, no superiority over the APQ discipline is demonstrated. © 2019 The Authors
Open Access
Necesidad de un enfoque holístico y cuantitativo para el diagnóstico y mejora de los servicios de urgencia hospitalarios
(Gobierno de Navarra, 2018) Mallor Giménez, Fermín; Cildoz Esquíroz, Marta; Ibarra, Amaia; Institute of Smart Cities - ISC
Carta al editor a raíz del artículo ‘Una propuesta de modelo fisiológico de servicio de urgencias hospitalario. Principios de funcionamiento, tipificación de la saturación y pautas para el rediseño’ y réplica de los autores del mismo.
Open Access
Desarrollo e implementación de un modelo de simulación para la mejora del Servicio de Urgencias
(2016) Cildoz Esquíroz, Marta; Mallor Giménez, Fermín; Azcárate Camio, Cristina; Escuela Técnica Superior de Ingenieros Industriales y de Telecomunicación; Telekomunikazio eta Industria Ingeniarien Goi Mailako Eskola Teknikoa
Since the new Emergency Department of the Hospital of Navarre was built (which has 3.500 square meters of facilities that serve a population of half a million people), it emerged the need to enhance the system performance by shortening the length of stay, improving patient satisfaction and reducing physicians’ work overload. As part of a larger project, it is studied how to avoid disparities between physicians in the mild patients’ circuit (A). At the present time, patients in triage are assigned to physicians cyclically as they arrive to the Emergency Department which facilitates the triage nurses decision making although it leads to an imbalanced workload of the physicians. Our approach consider the development of a discrete-event simulation model that takes into account an accurate description of patient flow, medical and nurse procedures, and characteristics of patient (health status, seasonal patterns of arrivals, etc.). The model parameters calibration and estimation is based on a thorough analysis of real historical data associated to this new department (more than 120.000 patient cases during its first operating year). By using this mathematical model, we compare the actual patient-physicians assignment policy with other assignment rules proposed by the medical teams who work in the new Hospital of Navarre Emergency Department (and also by the author) with the aim of balancing physicians’ workload and reducing patients waiting time.

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