A Simulation--Based Optimization approach for analyzing the ambulance diversion phenomenon in an Emergency-Department network

Ambulance Diversion (AD) is one of the possible strategies for relieving the worldwide phenomenon of Emergency Department (ED) overcrowding. It can be carried out when an ED is overloaded and consists of redirecting incoming by ambulance patients to neighboring EDs. Properly implemented, AD should result in reducing delays of patient treatment, ensuring safety and rescue of life-threatening patients. From an operational point of view, AD corresponds to a resource pooling policy among EDs in a network. In this paper we propose a novel model for studying the effectiveness of AD strategies, based on the Simulation-Based Optimization (SBO) approach. In particular, we developed a discrete event simulation model for reproducing the ED network operation. Then, for each AD policy considered, we formulate and solve an optimal resources allocation problem consisting of a bi-objective SBO problem where the target is the minimization of the non-value added time spent by patients and the overall cost incurred by the ED network. A set of optimal points belonging to the Pareto frontier is obtained for each policy. To show the reliability of the proposed approach, a real case study consisting of six large EDs in the Lazio region of Italy is considered, analyzing the effects of adopting different AD policies.Comment: 22 page

Modeling the Emergency Care Delivery System Using a Queueing Approach

This thesis considers a regional emergency care delivery system that has a common emergency medical service (EMS) provider and two hospitals, each with a single emergency department (ED) and an inpatient department (ID). Patients arrive at one of the hospital EDs either by ambulance or self-transportation, and we assume that an ambulance patient has preemptive priority over a walk-in patient. Both types of patients can potentially be admitted into the ID or discharged directly from the ED. An admitted patient who cannot access the ID due to the lack of available inpatient beds becomes a boarding patient and blocks an ED server. An ED goes on diversion, e.g., requests the EMS provider to divert incoming ambulances to the neighboring facility, if the total number of its ambulance patients and boarding patients exceeds its capacity (the total number of its servers). The EMS provider will accept the diversion request if the neighboring ED is not on diversion. Both EDs choose its capacity as its diversion threshold and never change the threshold value strategically, and hence they never game. Although the network could be an idealized model of an actual operation, it can be thought of as the simplest network model that is rich enough to reproduce the variety of interactions among different system components. In particular, we aim to highlight the bottleneck effect of inpatient units on ED overcrowding and the network effects resulting from ED diversions. A continuous time Markov chain is introduced for the network model. We show that the chain is irreversible and hence its stationary distribution is difficult to characterize analytically. We identify an alternative solution that builds on queueing decomposition and matrix-analytic methods. We demonstrate through discrete-event simulations the effectiveness of this solution on deriving various performance measures of the original network model. Moreover, by conducting extensive numerical experiments, we provide potential explanations for the overcrowding and delays in a network of hospitals. We suggest remedies from a queueing perspective for the operational challenges facing emergency care delivery systems

A generic method to develop simulation models for ambulance systems

In this paper, we address the question of generic simulation models and their role in improving emergency care around the world. After reviewing the development of ambulance models and the contexts in which they have been applied, we report the construction of a reusable model for ambulance systems. Further, we describe the associated parameters, data sources, and performance measures, and report on the collection of information, as well as the use of optimisation to configure the service to best effect. Having developed the model, we have validated it using real data from the emergency medical system in a Brazilian city, Belo Horizonte. To illustrate the benefits of standardisation and reusability we apply the model to a UK context by exploring how different rules of engagement would change the performance of the system. Finally, we consider the impact that one might observe if such rules were adopted by the Brazilian system

Models of Emergency Departments for Reducing Patient Waiting Times

In this paper, we apply both agent-based models and queuing models to investigate patient access and patient flow through emergency departments. The objective of this work is to gain insights into the comparative contributions and limitations of these complementary techniques, in their ability to contribute empirical input into healthcare policy and practice guidelines. The models were developed independently, with a view to compare their suitability to emergency department simulation. The current models implement relatively simple general scenarios, and rely on a combination of simulated and real data to simulate patient flow in a single emergency department or in multiple interacting emergency departments. In addition, several concepts from telecommunications engineering are translated into this modeling context. The framework of multiple-priority queue systems and the genetic programming paradigm of evolutionary machine learning are applied as a means of forecasting patient wait times and as a means of evolving healthcare policy, respectively. The models' utility lies in their ability to provide qualitative insights into the relative sensitivities and impacts of model input parameters, to illuminate scenarios worthy of more complex investigation, and to iteratively validate the models as they continue to be refined and extended. The paper discusses future efforts to refine, extend, and validate the models with more data and real data relative to physical (spatial–topographical) and social inputs (staffing, patient care models, etc.). Real data obtained through proximity location and tracking system technologies is one example discussed

THE USE OF SIMULATION TO EVALUATE AND ENHANCE THE PERFORMANCE OF PASSPORTS AND CIVIL AFFAIRS SECTOR

In this thesis, the proposed project intends to study the use of Decision Support Systems in simulating Gaza Civil Affairs and Passports Directorate (GCAPD) through identifying the current environment, analyzing the status, and proposing a new system using simulation to determine the optimal number of service providers for the system in order to reduce the postponement of the public services

Coordination of Autonomous Healthcare Entities: Emergency Response to Multiple Casualty Incidents

In recent years, many urban areas have established healthcare coalitions (HCCs) composed of autonomous (and often competing) hospitals, with the goal of improving emergency preparedness and response. We study the role of such coalitions in the specific context of response to multiple-casualty incidents in an urban setting, where on-scene responders must determine how to send casualties to medical facilities. A key function in incident response is multi-agency coordination. When this coordination is provided by an HCC, responders can use richer information about hospital capacities to decide where to send casualties. Using bed availability data from an urban area and a suburban area in the United States, we analyze the response capability of healthcare infrastructures under different levels of coordination, and we develop a stress test to identify areas of weakness. We find that improved coordination efforts should focus on decision support using information about inpatient resources, especially in urban areas with high inter-hospital variability in resource availability. We also find that coordination has the largest benefit in small incidents. This benefit is a new value proposition for HCCs, which were originally formed to improve preparedness for large disasters

Optimisation des opérations dans les services d’urgence

Emergency Department (ED) is the service within hospitals responsible for providing unscheduled care to a wide variety of patients over 24 hours a day, 7 days a week. As a result to the existing mismatch between available caring capacity and patients demand, EDs are currently facing a recurrent worldwide problem, namely overcrowding. The objective of this thesis is to develop internal and cost-effective solutions to alleviate overcrowding in EDs and improve their performance, using Operations Research/Operations Management (OR/OM) methods. Such solutions are of great interest for managers. In order to achieve this objective, we address a series of research questions.The first category of research questions include prospective questions about ED Key Performance Indicators (KPIs) and about the diverse factors contributing to overcrowding. We first conduct a detailed literature review on the commonly used KPIs from an OR/OM perspective. The review summarizes the advantages and drawbacks of each KPI and provides several useful insights. In addition, a series of statistical analysis are performed in the purpose of identifying the main influencing factors of performance.The second category consists in resource-related questions that are associated to the dimensioning of ED resource capacity. A realistic ED discrete-event simulation model is thus proposed. The model accounts for the most essential structural and functional characteristics of EDs thanks to a close collaboration with practitioners. Using simulation optimization, we minimize the patient average length of stay (LOS), by integrating a staffing budget constraint and a constraint securing that the most severe incidents will see a doctor within a specified time limit. The obtained results allow us to provide useful insights to managers about the impact of the budget on performance and how investments priorities should be allocated among resources, as well as the effect of combining two different major KPIs. Furthermore, we propose a heuristic for the optimization of the shifts of human resources. The method combines simulation optimization and linear programming.The third category of questions deals with process-related issues. We investigate potential alternative and innovative ED patient flow designs (with fixed budget). Typically in current ED practices, each patient is assigned to a single physician who will be exclusively responsible of him/her during all stages of the process (“Same Patient Same Physician”, SPSP rule). We conduct a survey which confirms that SPSP stands as the standard practice in most EDs worldwide, and that removing SPSP rule is very controversial among practitioners. We next use a complexity-augmented Erlang-R queueing network modeling. We show and quantify the potential benefits of removing the SPSP restriction as a function of the system parameters. For a second process-related issue, we compare the Triage Nurse ordering (TNO) diagnostic tests against the standard procedure, i.e., waiting for the physician to examine the patient and order tests. We demonstrate the efficiency of TNO on ED performance as a function of key parameters, such as triage nurse ability, system load and triage time extension.In summary, this thesis addresses innovative OM research questions for EDs. It provides decision makers with recommendations and tools in order to improve ED performance. It also highlights various avenues for future research related to the optimization of ED operations.Un Service d’urgence (SU) est le service hospitalier ayant comme responsabilité de fournir des soins non programmés à une grande variété de patients, 24 heures sur 24, 7 jours sur 7. Les SU sont actuellement confrontés à un problème international et récurrent, à savoir la saturation des urgences qui résulte de l’actuelle inadéquation entre les capacités médicales et la demande des patients. L'objectif est de développer des solutions internes et économiques permettant d’atténuer le phénomène de saturation des urgences et d’améliorer leur performance, à l'aide de méthodes issues de la Recherche Opérationnelle/Gestion des Opérations (RO/GO). Ces solutions sont d'un grand intérêt pour les gestionnaires. Afin d'atteindre cet objectif, nous abordons trois ensembles de questions de recherche.La première catégorie comprend des questions prospectives portant sur les indicateurs clés de performance (ICP) ainsi que sur les différents facteurs contribuant à l’encombrement des urgences. La deuxième catégorie est constituée de questions liées au dimensionnement de la capacité des ressources humaines dans un SU. Un modèle réaliste de simulation à événements discrets des urgences est élaboré. En utilisant l'optimisation basée sur la simulation, la durée moyenne de séjour des patients (LOS) est minimisée, en intégrant une contrainte budgétaire ainsi qu’une contrainte assurant que les patients les plus critiques accèderont à un médecin dans un délai déterminé. Les résultats obtenus permettent de fournir aux gestionnaires des urgences des indications utiles sur l'impact du budget sur la performance et sur la manière dont les investissements devraient être priorisés et répartis entre les ressources, ainsi que sur l'effet de la prise en compte de deux principaux ICP différents. Nous proposons également une heuristique pour l'optimisation de la structure des shifts (roulements) du personnel dans la journée. La méthode combine l'optimisation basée sur la simulation avec de la programmation linéaire. La troisième catégorie de questions porte sur le processus de soins des patients. Nous analysons des modifications et des alternatives innovantes dans le parcours du patient (à budget fixe). Typiquement, dans les pratiques actuelles, chaque patient dans un SU est affecté à un seul médecin qui en sera exclusivement responsable pendant toutes les étapes du processus (règle du "Même Patient Même Médecin", MPMM). Dans un premier temps, nous menons une enquête auprès des praticiens qui confirme que MPMM représente la pratique standard dans la plupart des SU à travers le monde. L’enquête révèle également que la suppression de cette règle est très controversée parmi les urgentistes. Nous utilisons ensuite une modélisation en réseau de files d’attente Erlang-R contenant une complexité additionnelle. Nous montrons et quantifions les avantages potentiels de la suppression de la restriction MPMM en fonction des paramètres du système. Une seconde étude portant sur le processus est menée, à savoir la prescription des examens par l’infirmière chargée du tri (PIT) avant la consultation initiale. Nous comparons le fait d’autoriser l’infirmière à prescrire certains examens complémentaires, avec la procédure standard consistant à attendre que le médecin examine le patient et lui prescrive des examens. Nous démontrons l'efficacité de PIT sur la performance du SU en fonction de paramètres clés, tels que le niveau de compétence de l’infirmière, la charge du système et l'extension de la durée du tri.De manière générale, cette thèse aborde d’innovantes questions de recherche dans la gestion des opérations des SU. Elle fournit aux décideurs des recommandations et des outils permettant d’améliorer la performance des urgences. Cette thèse ouvre également la voie pour de futurs axes de recherche liés à l'optimisation des opérations dans les SU