Methodology for profiling literature in healthcare simulation

The publications that relate to the application of simulation to healthcare have steadily increased over the years. These publications are scattered amongst various journals that belong to several subject categories, including Operational Research, Health Economics and Pharmacokinetics. The simulation techniques that are applied to the study of healthcare problems are also varied. The aim of this study is to present a methodology for profiling literature in healthcare simulation. In our methodology, we have considered papers on healthcare that have been published between 1970 and 2007 in journals with impact factors that belonging to various subject categories reporting on the application of four simulation techniques, namely, Monte Carlo Simulation, Discrete-Event Simulation, System Dynamics and Agent-Based Simulation. The methodology has the following objectives: (a) to categorise the papers under the different simulation techniques and identify the healthcare problems that each technique is employed to investigate; (b) to profile, within our dataset, variables such as authors, article citations, etc.; (c) to identify turning point (strategically important) papers and authors through co-citation analysis of references cited by the papers in our dataset. The focus of the paper is on the literature profiling methodology, and not the results that have been derived through the application of this methodology. The authors hope that the methodology presented here will be used to conduct similar work in not only healthcare but also other research domains

Improving the Efficiency of Physical Examination Services

The objective of our project was to improve the efficiency of the physical examination screening service of a large hospital system. We began with a detailed simulation model to explore the relationships between four performance measures and three decision factors. We then attempted to identify the optimal physician inquiry starting time by solving a goal-programming problem, where the objective function includes multiple goals. One of our simulation results shows that the proposed optimal physician inquiry starting time decreased patient wait times by 50% without increasing overall physician utilization

Applications of simulation within the healthcare context

This is a pre-print of an article published in Journal of the Operation Research Society. The definitive publisher-authenticated version Katsaliaki, K., Mustafee, N.,(2010). Applications of simulation within the healthcare context. Journal of the Operation Research Society. 62, 1431-1451 is available online at: http://www.palgrave-journals.com/jors/journal/v62/n8/full/jors201020a.htmlA large number of studies have applied simulation to a multitude of issues related to healthcare. These studies have been published over a number of unrelated publishing outlets, and this may hamper the widespread reference and use of such resources. In this paper we analyse existing research in healthcare simulation in order to categorise and synthesise it in a meaningful manner. Hence, the aim of this paper is to conduct a review of the literature pertaining to simulation research within healthcare in order to ascertain its current development. A review of approximately 250 high quality journal papers published between 1970 and 2007 on healthcare-related simulation research was conducted. The results present: a classification of the healthcare publications according to the simulation techniques they employ; the impact of published literature in healthcare simulation; a report on demonstration and implementation of the studies’ results; the sources of funding; and the software used. Healthcare planners and researchers will benefit from this study by having ready access to an indicative article collection of simulation techniques applied in healthcare problems that are clustered under meaningful headings. This study facilitates the understanding of the potential of different simulation techniques for solving diverse healthcare problems

A simulation-based decision support tool for informing the management of patients with Parkinson’s disease

This is an Accepted Manuscript of an article published by Taylor & Francis Group in International Journal of Production Research, on 9 April 2015, available online via: http://dx.doi.org/10.1080/00207543.2015.1029647We describe a decision support toolkit that was developed with the aim of assisting those responsible with the management and treatment of Parkinson’s disease (PD) in the UK. Having created a baseline model and established its face validity, the toolkit captures the complexity of PD services at a sufficient level and operates within a user friendly environment, that is, an interface was built to allow users to specify their own local PD service and input their own estimates or data of service demands and capacities. The main strength of this decision support tool is the adoption of a team approach to studying the system, involving six PD specialist nurses across the country, ensuring that variety of views and suggestions are taken as well as systems modelling and simulations. The tool enables key decision makers to estimate the likely impact of changes, such as increased use of community services on activity, cost, staffing levels, skill-mix, and utilisation of resources. Such previously unobtainable quantitative information can be used to support business cases for changes in the increased use of community services and its impact on clinical outcomes (disease progression), nurse visits and costing.Peer reviewedFinal Accepted Versio

Examining The Influence Of Dependent Demand Arrivals On Patient Scheduling

This research examines the influence of batch appointments on patient scheduling systems. Batch appointments are characterized by multiple patients within a family desiring appointments within the same time frame

Facets of trust in simulation studies

This is the author accepted manuscript. The final version is available on open access from Elsevier via the DOI in this recordThe purpose of a modelling and simulation (M&S) study for real-world operations management applications is to support decision-making and inform potential action, therefore investigating the aspects of the modelling process which influence trust is important. Previous work has considered the question of trust through the lens of model validation. However, whilst a simulation model may be technically well executed, stakeholders’ trust in the results may also depend upon intangible factors such as interpersonal relationships. Existing literature has also focused on the credibility of the simulation practitioner, however the credibility attribute belongs to the stakeholder, and it ignores the trust aspects that may exist between the stakeholders and the model itself. In this paper, we argue that different facets of trust emerge throughout the stages of a simulation study, and both influence, and are influenced by, the interaction between the model, the modeller and the stakeholders of the study. We present a synthesis of existing literature and extend it by proposing a formative model of trust which presents a conceptualisation of this tripartite relationship. Our contribution is the identification of the different facets of trust in the lifecycle of a modelling and simulation study. We argue that these interacting facets converge via the three-way relationship between modeller, model and stakeholders toward epistemic trust in the knowledge generated by the simulation study and ultimately model acceptability and implementation. To the best of our knowledge, ours is the first study that focuses solely on the question of trust in an M&S study.Economic and Social Research Council (ESRC

Resilience of critical structures, infrastructure, and communities

In recent years, the concept of resilience has been introduced to the field of engineering as it relates to disaster mitigation and management. However, the built environment is only one element that supports community functionality. Maintaining community functionality during and after a disaster, defined as resilience, is influenced by multiple components. This report summarizes the research activities of the first two years of an ongoing collaboration between the Politecnico di Torino and the University of California, Berkeley, in the field of disaster resilience. Chapter 1 focuses on the economic dimension of disaster resilience with an application to the San Francisco Bay Area; Chapter 2 analyzes the option of using base-isolation systems to improve the resilience of hospitals and school buildings; Chapter 3 investigates the possibility to adopt discrete event simulation models and a meta-model to measure the resilience of the emergency department of a hospital; Chapter 4 applies the meta-model developed in Chapter 3 to the hospital network in the San Francisco Bay Area, showing the potential of the model for design purposes Chapter 5 uses a questionnaire combined with factorial analysis to evaluate the resilience of a hospital; Chapter 6 applies the concept of agent-based models to analyze the performance of socio-technical networks during an emergency. Two applications are shown: a museum and a train station; Chapter 7 defines restoration fragility functions as tools to measure uncertainties in the restoration process; and Chapter 8 focuses on modeling infrastructure interdependencies using temporal networks at different spatial scales

Layout Evaluation by Simulation Protocol for Identifying Potential Inefficiencies Created by Medical Building Configuration

With the healthcare industry in a state of change, one focus is on efficiency in the healthcare environment. The trend for architects is a focus on an evidence-based design decision making process. In this context, simulation is gaining acceptance as a source of evidence. This research developed the Layout Evaluation by Simulation (LES) protocol to evaluate the design of a healthcare facility layout. The approach contains a Systems-of-Systems analysis for developing a healthcare delivery (HD) model, a computer model and simulation of an existing medical facility validated by existing data. Then simulations are run through the validated model inserting the future facility design to evaluate efficiency in a proposed new spatial layout. Through a real-world case study, the research contains an evaluation of the predictive capacity of the LES protocol. In the research, a completely Agent Based Modeling and Simulation, a completely Discrete Event Simulation, and a hybrid were investigated. As detail was added to all models, simulations were run creating a matrix of results for comparison to existing data. The LES protocol was confirmed to be effective. The results demonstrate that the healthcare delivery (HD) model provides a sufficient basis from which to develop the computer model and simulation. The LES protocol is a valuable tool for evaluating situations for emergent behavior. The research also confirmed the need for some degree of agent based modeling to detect emergent behavior

Modélisation et simulation de la trajectoire des patients en radiothérapie

RÉSUMÉ : Modélisation et Simulation de la trajectoire des patients en radiothérapie - De nombreux traitements existent afin de lutter contre le cancer. Parmi les plus répandus, nous notons la chirurgie, la chimiothérapie et la radiothérapie. Cette dernière est considérée comme une référence étant donné que près de la moitié des patients ont passé par une phase de radiothérapie seule ou combinée durant leur régime de traitement. Le processus complet associé à cette technique implique une organisation complexe du point de vue des ressources et des flux des patients. Les réels enjeux d’une optimisation de ces processus sont multiples. En ce qui concerne les patients, l’enjeu majeur concerne la qualité des soins qui leur sont apportés et la minimisation des délais d’attente. En effet, diminuer ou éliminer les temps d’attente avant l’accès aux traitements signifie une meilleure qualité de service rendu au patient, mais également, une augmentation du nombre des patients pris en charge, et par conséquent, un accroissement de l’efficience de fonctionnement du centre de traitement. Depuis quelques dizaines d’années, les méthodes de recherche opérationnelle et les techniques de l’ingénierie industrielle font leur apparition dans le milieu hospitalier afin d’améliorer la performance de ces systèmes opératoires. En particulier, la radiothérapie présente une problématique intéressante liée à la conjonction de la rareté des ressources et à la complexité de la synchronisation de la trajectoire des soins. La résolution de ces problèmes nécessite une adoption de bonnes pratiques assurant d’une part, l’optimisation de la trajectoire des patients et d’autre part l’utilisation efficace des ressources disponibles. Dans ce contexte, les cliniques se sont retournées vers les outils d’aide à la décision. Parmi ces derniers, notons un outil permettant de modéliser toute la trajectoire des patients et comparer plusieurs politiques de gestion tout en étudiant leur impact sur la performance globale du système. Nous abordons cette question en débutant par une revue de la littérature sur la modélisation, la simulation et la planification en radiothérapie. Bien que cette étude se révèle limitée dans le contexte du processus complet, plusieurs approches ont été élaborées afin de traiter des parties du processus. En outre, elles sont appliquées à un cas spécifique lié à un seul centre de traitement. Dans cette optique, vient l’idée de ce projet ayant comme objectif le développement d’un modèle de simulation générique. Dans la première partie de ce travail, confronté aux limites du cadre de modélisation utilisé jusqu’aujourd’hui, nous avons développé une modélisation originale de la trajectoire des patients permettant une représentation plus fidèle de la réalité au niveau des flux physiques des patients, des ressources, des tâches, etc. En particulier, un langage de modélisation de processus normalisé (BMPN) a été utilisé pour élaborer une cartographie permettant de mieux comprendre le parcours d’un patient et sa trajectoire. Dans la deuxième partie, cette cartographie a été reproduite avec le langage de programmation Java et implémenté dans le modèle de simulation afin de pouvoir évaluer plusieurs nouvelles stratégies de gestion. Le simulateur obtenu nous a permis de modéliser et simuler la trajectoire des patients ainsi que leurs interactions avec les ressources tout en conservant la qualité de représentation de la réalité. En outre, il a permis de constater et d’évaluer l’impact de plusieurs scénarios par rapport aux différents indicateurs de performance. Finalement, la simulation du système radio-oncologique nous a abouti à prévoir des recommandations que nous avons jugé fiable, après la phase de validation, assurant l’amélioration de la qualité des soins apportés aux patients par la diminution des délais de prise en charge et le respect des temps d’attentes prescrits par la grille de classification. Mots-Clés : Modélisation, simulation, radiothérapie, trajectoires, stratégies et modèles de planification, ressources ----------ABSTRACT : Modeling and simulation of patient trajectory in radiotherapy centers - In the fight against cancer, major path are surgery, chemotherapy and radiotherapy. Radiation therapy is recognized as a reference since more than 50% of the patients received radiation during their treatment regimen. The treatment process associated with this technique involves a complex organization as regards as resources and patient flows. Concerning radiotherapy centers, they need to reduce treatment cost and manage resources utilization while keeping better quality of service. Regarding patients, major concern is quality of the care they receive and improvement of waiting time. In fact, reducing or eliminating waiting time before access to treatment means better quality of service to the patient, but also an increase in the number of treated patients, and consequently in the efficiency of treatment. Since several decades, operational research methods and industrial management techniques have appeared in healthcare. In particular, radiotherapy care trajectories are interesting because of the combination of critical resources and multiples care activity repetition. The resolution of these problems requires the adoption of good practices ensuring on the one hand the optimization of the trajectory of patients and on the other hand the efficient use of available resources. In this context, clinics have turned to decision-making tools. Among these, a tool that can model the entire patient trajectory and compare several management policies while studying their impact on the overall performance. We address this issue by starting with a review of the literature on modeling, simulation and planning in radiotherapy. Although several promising approaches have been developed, literature in this filed is scare. In fact, the majority of study reviewed handle only some phases of the process. In addition, they are applied to a specific case related to a single treatment center. In this perspective that this project was born with the objective of developing a generic simulation model. In the first part, we have developed an original model of the trajectory of patients allowing more accurate representation of reality of the processes. In particular, a standardized process modeling language (BMPN) was used to develop a precise mapping to better understand a patient's trajectory. In the second part, this mapping was reproduced and implemented in Java in order to evaluate several new management strategies. The simulator that we developed allowed us to simulate the trajectory of patients as well as their interactions with resources. In addition, it was possible to observe and evaluate the impact of several scenarios in terms of the objectives of centers, quantified using appropriate indicators such as waiting time. Finally, using the knowledge accumulated during the simulation of different scenarios, we made recommendations ensuring the improvement of quality of care given to patients by reducing delays and maximizing the uses of existing resources. Keywords: Modeling, simulation, radiotherapy, trajectories, planning strategies, resource