Simulation Modelling in Healthcare: Challenges and Trends

AbstractIn this paper, we describe simulation models in healthcare that have been developed in the past two decades. Simulation systems, ranging from simulation of patient flow in emergency rooms to simulation of populations with a specific chronic diseases, are reviewed. Simulation types included discrete event simulation (DES) and agent based simulation (ABS). A trend of variability and scalability were identified, and discussed in terms of platform used to develop the model, data sources, and computational power needed to run the simulation. In the synthesis of simulation models, programming languages and products emerged as clusters. Design models and systems engineering development processes are examined with a focus on requirements discovery, models and scenarios of simulation. Graphic user interfaces in the simulation tools in healthcare are reviewed in terms of visual design and human factors. Furthermore, interaction modes and trends of information visualization techniques used for the simulations are reported. Agent-based simulation models in particular were reviewed, and findings suggest agent characteristics varied across literature researched in aspects such as socio-demographic design considerations

Improving surgeon utilization in an orthopedic department using simulation modeling

Purpose: Worldwide more than two billion people lack appropriate access to surgical services due to mismatch between existing human resource and patient demands. Improving utilization of existing workforce capacity can reduce the existing gap between surgical demand and available workforce capacity. In this paper, the authors use discrete event simulation to explore the care process at an orthopedic department. Our main focus is improving utilization of surgeons while minimizing patient wait time. Methods: The authors collaborated with orthopedic department personnel to map the current operations of orthopedic care process in order to identify factors that influence poor surgeons utilization and high patient waiting time. The authors used an observational approach to collect data. The developed model was validated by comparing the simulation output with the actual patient data that were collected from the studied orthopedic care process. The authors developed a proposal scenario to show how to improve surgeon utilization. Results: The simulation results showed that if ancillary services could be performed before the start of clinic examination services, the orthopedic care process could be highly improved. That is, improved surgeon utilization and reduced patient waiting time. Simulation results demonstrate that with improved surgeon utilizations, up to 55% increase of future demand can be accommodated without patients reaching current waiting time at this clinic, thus, improving patient access to health care services. Conclusion: This study shows how simulation modeling can be used to improve health care processes. This study was limited to a single care process; however the findings can be applied to improve other orthopedic care process with similar operational characteristics. Keywords: waiting time, patient, health care processpublishedVersio

Simulación de un sistema de emergencias: caso E.S.E. Hospital San Rafael

Este articulo presenta los resultados de una investigación sobre el proceso de prestación de servicio de emergencias del Hospital San Rafael (Tunja, Boyacá), específicamente para procedimientos mínimos o menores, donde habitualmente se presentan solicitudes de atención de usuarios que exceden la capacidad asistencial y generan demoras para el acceso al servicio. Por lo anterior, se utilizó una simulación del entorno real mediante el software Flexsim, para encontrar una opción de mejora del servicio. Inicialmente se realizó un diagnóstico del sistema, para luego hacer una medición del trabajo con el fin de crear tres escenarios posibles de operación de los recursos humanos y físicos en la prestación del servicio. Mediante la evaluación de las alternativas de mejora se planteó el objetivo de encontrar una configuración factible que proporcione el menor tiempo de atención al paciente que requiere procedimientos mínimos o menores. Con el modelo propuesto se obtuvo una mejora del 18,7% en el tiempo de espera de usuarios, lo cual apoya la toma de decisiones de las directivas del hospital y genera un beneficio para los usuarios

Mapeamento do fluxo de valor em operações hospitalares: análise e simulação em um hospital oncológico

The value stream mapping in association with the discrete-event simulation have been of great contribution to the service operations. In Brazil, the demand for oncology services is expected to grow in the coming years. Taking into account that the Brazilian health services have already been facing some deficiencies, this field has opportunities still not explored to apply the tools mentioned in the hospital context. The objective of this article was to propose improvements to the outpatient clinic of a Brazilian cancer treatment hospital. With that purpose, in loco visits were made to analyze the activities developed in the area, followed by the construction of a value stream map for the current state, the identification of opportunities to improve, and, finally, the proposal and simulation of a future state map. The main problems identified in the hospital were the queues in the medical triage, the use of patients as means to transfer necessary information, loss of patients’ records, non-optimized chemotherapy schedules, and long waiting times to clinical appointments. The proposals for the future state map have shown opportunities to reduce the average lead time of the treatment from 57 days and 16 minutes to 33 days and 6 minutes. The simulation of one of the proposals for the outpatient clinic has shown promising results, with possible execution of the improvement without investments in new resources. On the other hand, a shorter treatment period seems to lead to an expressive increase in the waiting times and the average number of patients in line.O mapeamento do fluxo de valor unido à simulação de eventos discretos tem se mostrado de grande valia na análise de operações de serviços. A tendência ao aumento na demanda de serviços de oncologia para os próximos anos no Brasil, junto com um sistema de saúde que já apresenta deficiências, representam uma oportunidade ainda pouco explorada de aplicação de tais ferramentas no contexto hospitalar. Com o objetivo de propor melhorias ao setor ambulatorial de um hospital brasileiro especializado no tratamento de câncer, foram analisadas as atividades desenvolvidas neste ambiente através de visitas in loco, seguindo com o mapeamento do fluxo de valor do estado atual, a identificação de oportunidades de melhoria, e, por fim, a proposição e a simulação do estado futuro. Os principais problemas identificados no hospital foram as filas na triagem médica, o uso dos pacientes como meios de transferência de informação, perda de prontuários, agenda de quimioterapia não otimizada e longas esperas para realização de consultas. As propostas apresentadas para o desenvolvimento do mapa do estado futuro demonstraram oportunidades de redução do lead time médio do tratamento de 57 dias e 16 minutos para 33 dias e 6 minutos. A simulação de uma destas propostas para o ambulatório do hospital apresentou resultados promissores, com possibilidade de execução da melhoria sem investimentos em novos recursos. Por outro lado, a redução do período total do tratamento parece levar a um aumento expressivo nos tempos de espera e número médio de pacientes nas filas

A Simulation-Based Evaluation Of Efficiency Strategies For A Primary Care Clinic With Unscheduled Visits

In the health care industry, there are strategies to remove inefficiencies from the health delivery process called efficiency strategies. This dissertation proposed a simulation model to evaluate the impact of the efficiency strategies on a primary care clinic with unscheduled walk-in patient visits. The simulation model captures the complex characteristics of the Orlando Veteran\u27s Affairs Medical Center (VAMC) primary care clinic. This clinic system includes different types of patients, patient paths, and multiple resources that serve them. Added to the problem complexity is the presence of patient no-shows characteristics and unscheduled patient arrivals, a problem which has been until recently, largely neglected. The main objectives of this research were to develop a model that captures the complexities of the Orlando VAMC, evaluate alternative scenarios to work in unscheduled patient visits, and examine the impact of patient flow, appointment scheduling, and capacity management decisions on the performance of the primary care clinic system. The main results show that only a joint policy of appointment scheduling rules and patient flow decisions has a significant impact on the wait time of scheduled patients. It is recommended that in the future the clinic addresses the problem of serving additional walk-in patients from an integrated scheduling and patient flow viewpoint

Utilização da simulação híbrida para representar o fator humano em sistemas produtivos.

A simulação computacional tem se tornado uma ferramenta amplamente utilizada no ambiente empresarial por auxiliar gestores a compreender melhor a dinâmica de processos complexos, que por muitas vezes não é captada por ferramentas matemáticas convencionais. Os projetos de simulação são desenvolvidos a fim de entender, analisar e prever o comportamento de diversos elementos de um sistema. O elemento humano é um dos elementos mais críticos de sistemas produtivos, uma vez que tem influência direta no comportamento destes sistemas, principalmente em sistemas onde se tem um trabalho com mão de obra manual intensiva. Embora pesquisadores já tenham visto a importância de compreender o elemento humano em uma organização, diversos autores apontam que em muitos projetos de simulação este elemento não é bem representado. Eles criticam ainda o fato de se ter uma grande preocupação em detalhar máquinas e equipamentos, enquanto o elemento humano é tratado como simples recursos que se desempenham de forma constante. Esta visão errônea do fator humano pode prejudicar os resultados gerados pelos modelos de simulação. A simulação a eventos discretos (SED), apesar de apresentar vantagens como flexibilidade e alto poder de análise de processos, apresenta dificuldade em termos de representação do fator humano, principalmente, por este apresentar comportamento bastante complexo. Ao utilizar esta ferramenta, devem-se fazer diversas suposições e adequações para representar o comportamento do ser humano em sistemas produtivos. Já a simulação baseada em agentes (SBA) tem sido apontada como uma excelente alternativa para representar o fator humano em diversas áreas, pois os agentes são seres autônomos, proativos e inteligentes, características inerentes ao ser humano. Portanto, combinou-se a SBA com a simulação a eventos discretos a fim de verificar se esta simulação híbrida torna os resultados simulados mais próximos do real. Nesta simulação híbrida, o fluxo do processo foi construído pela SED e o elemento humano representado por agentes, agentes estes que são influenciados por um fator que afeta a sua produtividade, neste caso o ritmo circadiano. Para tanto, três projetos de simulação de diferentes sistemas produtivos com mão de obra manual intensiva foram desenvolvidos e foi possível verificar que em ambos os casos o modelo de simulação híbrida (SBA e SED) foi estaticamente validado, apresentando resultados mais próximos do real quando comparados aos resultados de modelos de SED dos mesmos sistemas avaliados. Foi possível verificar também que a inserção do ritmo circadiano nestes casos, além de tornar a representação do fator humano mais próxima do real, não exige uma extensiva coleta de dados de tempo para alimentar o modelo computacional, reduzindo assim tempo e custo do desenvolvimento dos projetos de simulação

Using Case-Based Reasoning for Simulation Modeling in Healthcare

The healthcare system is always defined as a complex system. At its core, it is a system composed of people and processes and requires performance of different tasks and duties. This complexity means that the healthcare system has many stakeholders with different interests, resulting in the emergence of many problems such as increasing healthcare costs, limited resources and low utilization, limited facilities and workforce, and poor quality of services. The use of simulation techniques to aid in solving healthcare problems is not new, but it has increased in recent years. This application faces many challenges, including a lack of real data, complicated healthcare decision making processes, low stakeholder involvement, and the working environment in the healthcare field. The objective of this research is to study the utilization of case-based reasoning in simulation modeling in the healthcare sector. This utilization would increase the involvement of stakeholders in the analysis process of the simulation modeling. This involvement would help in reducing the time needed to build the simulation model and facilitate the implementation of results and recommendations. The use of case-based reasoning will minimize the required efforts by automating the process of finding solutions. This automation uses the knowledge in the previously solved problems to develop new solutions. Thus, people could utilize the simulation modeling with little knowledge about simulation and the working environment in the healthcare field. In this study, a number of simulation cases from the healthcare field have been collected to develop the case-base. After that, an indexing system was created to store these cases in the case-base. This system defined a set of attributes for each simulation case. After that, two retrieval approaches were used as retrieval engines. These approaches are K nearest neighbors and induction tree. The validation procedure started by selecting a case study from the healthcare literature and implementing the proposed method in this study. Finally, healthcare experts were consulted to validate the results of this study

Profitably Risky: A Study of Medicare Capitation Contracts for Primary Care Medical Practices

The Centers for Medicare and Medicaid Services is seeking to move medical providers from a fee-for-service reimbursement model to a value-based reimbursement model. In this dissertation, we studied the financial rewards and risks that accompany capitation contracts. We employed Poisson regression to estimate health-care utilization of beneficiaries under the care of primary care providers with varying levels of capitation. Then, we calculated capitation contract results for primary care practices using Monte Carlo simulations. We used three methods to predict medical payments for beneficiaries: (1) empirical probability distributions of annual medical payments, (2) theoretical probability distributions of annual medical payments, and (3) accumulated costs from simulating individual medical services received. We found that Medicare Advantage beneficiaries under the care of primary care physicians who were engaged in capitation contracts experienced significantly fewer visits in inpatient, outpatient, carrier, home health, and skilled nursing facility health-care venues. Their visit counts were 48.2%, 57.6%, 35.0%, 74.3%, and 66.2% fewer for the respective venues, compared with a group of Traditional Medicare beneficiaries. Reducing health-care service utilization was the greatest determinant of achieving positive financial rewards under capitation. Stop-loss provisions were, however, essential to protect practices from extreme costs that occurred for a few very sick patients. We found that, with appropriate contract provisions and proven reductions in healthcare utilization, primary care practices could have been protected from the financial failures of prior capitation attempts. Upside-only contracts also protected small practices from financial failure while providing strong financial incentives to reduce health care utilization