醫療保健應用的其它領域»

医疗服务业正在从减少浪费、改善病人体验、提高全民健康水平的方面进行重新设计和改进。健康专家使用模型来提升临床诊断,该模型与单独的病人和特定的医疗服务数据相链接,从而保证病人及其护理人员可以进行自我管理,基于病人的遗传特性、身体生理状况、心理和社交网络来调整治疗的方法。在政策和程序层面上也会使用建模和仿真来评估混合干预措施的成本效益,不仅是检测和治疗,还可以促进健康并预防风险。一个重要的方面是要去理解不同背景下产生的不同结果,尤其是要从健康问题的社会决定因素及其差异性和不平等性的变化方面去理解。想要通过组织健康和社会系统来改善健康、医疗价值和可及性,是一个挑战,它要求我们从总体和个体层面用多种方式将问题抽象化,包括过程和主体交互事件,以及对反馈和网络结构的理解。AnyLogic 可以在仿真模型中将理论和数据结合起来,这些模型可以用来测试不同虚拟试验场景中的干预措施,以评估这些措施是否适合特定的国家、地区、组织、服务或目标群体。
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评论&评价

  • AnyLogic被证明是一款非常有用的工具,用它我可以使用不同的仿真方法,创建对最终用户直观而有吸引力的接口。大多数功能是可以预定义对象,但如果有必要你可以添加你自己的结构,它提供了这样的灵活性。它们的技术支持团队知识丰富且反应迅速;在我看来他们的支持是非常出色的。

    Principal Informatics Scientist,
    AstraZeneca Pharmaceuticals
  • AnyLogic有足够的灵活性来支持系统和政策研究。而且足够强大来产生独立的可以被他人使用来支持他们专业工作的应用。

    Neil McEvoy,
    HealthEngineer
  • 市场上最灵活的仿真建模工具- 1) 当需要定制模型时,可通过Java平台访问Java编程进行2)混合不同的建模方法。带有预设对象和建模块的函数库(本身具有极大的灵活性),在新版本中进行了持续改进和增强,以及支持顾客导向的功能,使得整个图形几乎完整的呈现在我眼前!

    Stefan Bengtsson,
    斯德哥尔摩
  • We chose AnyLogic to tackle our large complex problem because of the multimethod models you can use, the mix of agent based, discrete event and system dynamics is a very useful combination. My favorite part of AnyLogic is all the dashboard features, the great charts and business intelligence you can get from the agents that are working in the model.

    Kyle Johnson, Global Business Services, Advanced Analytics and Optimization,
    IBM
  • Multimethod modeling is the most important feature of AnyLogic. The biggest advantage for me was the capability for advanced healthcare modelling and simulation.

    Geoff McDonnell, Director,
    Adaptive Care Systems and Synergia
  • AnyLogic allows to describe processes and explain them to decision makers. Its advantages are the great flexibility in reproduction of problems and the possibility to use system dynamics, agent based and discrete event simulation in one model.

    Romeo Placido, Director Hospital Radiology,
    Azienda Sanitaria Provinciale di Messina
  • AnyLogic is flexible: I don't feel hemmed in with any approach, and version 7 is a huge leap forward in the multimethod capability. We usually make changes with our eyes wide open thanks to AnyLogic!

    Keith Stockman, Manager of Projects and Operations Research, General Medicine Program,
    Monash Health
  • We have found AnyLogic to be powerful, robust, and suitable for a wide variety of modeling projects. The ability to model using any of the major paradigms (or a combination) allows us to tailor our models appropriately. The user interface is easy to understand for people of all levels of education and experience. AnyLogic's superb technical support has helped us to model very complex systems that we would not have been able to do otherwise.

    Mark Kazmierczak,
    Gryphon Scientific
  • We’ve been using AnyLogic probably for four years now. Most of my work time I was working with another academically based agent based modeling system. We were aware that AnyLogic existed, but only after a while did we think that maybe we should look at it instead of looking at the system we were using, and we found that it was easier for us to learn and to implement.

    Neil McEvoy, Director,
    Centre for Research in Healthcare Engineering
  • I see modeling and simulation capabilities, especially agent-based modeling techniques, as critical to helping identify breakthroughs with complex phenomena associated with health care delivery. Integrating diverse types of data with multi-method simulation can advance our understanding of biological phenomena in order to deliver higher quality health care. AnyLogic’s leadership in agent-based modeling, combined with its unique approach in a Java-based architecture, enables Health Services Consulting to navigate new territory and pursue cutting-edge projects now and in the future. I’m excited about the possibilities.

    Roger A. Edwards, ScD, Vice-President,
    Health Services Consulting Corporation
  • 我过去的两年已经使用AnyLogic。我认为它是市场上最完整和有用的仿真软件。我也有使用其它工具的经验,没有一个可以集成多方法建模范式,但AnyLogic可以。目前,我们在几个项目中使用AnyLogic作为仿真工具,如物流、或者临床活动、或者病人/员工流建模。如果你在寻找一个完整的解决方案,这可能是一个不错的选择。

    Alvaro Gil,
    Jewish General Hospital - Montreal
  • 我已经使用AnyLogic和大量其它仿真工具作为医院服务设计的一部分好多年了。我偏爱AnyLogic因为它的灵活性和多范式的能力,并竭诚的推荐它。

    Keith Stockman,
    Monash Health
  • 我已经使用AnyLogic在社会和卫生保健方面建模几年了。我喜欢它你可以立即使用就可以得到简单展示的结果。我喜欢可以混合和匹配仿真范式如ABM和系统动力学...在我的模型中可以敞开我的机会。使用Java类文件或者库文件的简单接口使整个系统可定制。我可以很容易的在网站上发布模型或者提供个人部署。最后但并不是不重要,我可以与团队使用典型源代码控制SVN来工作...

    David Lovece,
    Northeastern University

已有公司使用Anylogic来进行: 醫療保健

案例研究

  • Healthcare Decision-Support by Hybrid Simulation – Mobile Stroke Units
    Stroke causes severe disability, produces high costs for care and rehab, and its incidences are increasing due to an ageing population. Thrombosis causes most strokes and if possible, should be treated with thrombolysis (not in case of haemorrhagic strokes and after 4.5 hours have been elapsed). Currently, the process of transportation and internal hospital administration causes the patient to lose valuable time. Mobile Stroke Units have been suggested as a possible improvement.
  • Simulation Modeling Based on Healthcare Routine Data
    Decisions made by health care professionals require tools for planning, testing and assessment of new technologies or interventions. The complex structures, interactions and processes involved in health care, make change and innovation an ongoing challenge. Patrick Einzinger and Christoph Urach from DWH Simulation Services and Vienna University of Technology in partnership with the Austrian Association of Social Insurances (AASI) were given an opportunity to analyze public data for the purpose of critical future decision making.
  • Simulation of Maternity Ward Operations
    This model simulates the maternity ward in a hospital currently under construction. The purpose of the model is to support discussions related to which resources, capacity, and work methods are required on the new ward. The project was carried out for Karolinska University Hospital in the Stockholm County, Sweden.
  • Evaluating Hospital Inpatient Care Capacity
    Stockholm County, Sweden was in the process of building a new, highly specialized hospital. The Health Administration of the county questioned whether they would get an acceptable level of care production with the current investments and reasoning concerning various operational and strategic issues. To find the answers, they used simulation modeling in AnyLogic.
  • Handling Total Care Need for Dialysis Patients
    The County of Stockholm (Sweden), like any country or region, experiences a continuous need to handle the healthcare necessities of various patient groups. Each group can be seen as a subpopulation, with its own distinctive traits, characteristics, and challenges. The discussed simulation project focused on the dialysis patients, a group who needs to visit caregiving facilities frequently.
  • Disaster Response Applications Using Agent-Based Modeling
    In an effort to find practical operational solutions for response to an unexpected crisis or natural disaster, Battelle, world’s largest, non-profit, independent R&D organization, needed to test the effectiveness of a 48 hour shelter-in-place order for an Improvised Nuclear Device scenario. The goal was to reduce radiation dosages received during an uncoordinated mass evacuation, by comparing immediate evacuation and shelter-in-place order.
  • Evaluating Healthcare Policies to Reduce Rates of Cesarean Delivery
    The challenge of reducing the cesarean delivery rate has been recognized by numerous researchers for years. For the first time, in research conducted for the Washington State, Alan Mills, FSA MAAA ND, a research actuary, and his colleagues reproduced this part of the United States healthcare system in a simulation model to allow the stakeholders, including health agencies, insurers, clinicians, and legislators, to test their assumptions on the model to find the right solutions.
  • Shaping Healthcare Policy Using Simulation
    An initiative by the Department of Mechanical and Industrial Engineering at the University of Toronto, the Centre for Research in Healthcare Engineering (CRHE), was in response to the immediate and compelling desire for efficiency and quality improvements in the Canadian healthcare system.
  • An Agent-Based Explanation for SPMI Living Situation Changes
    Over the past 60 years, the number of Severely and Persistently Mentally Ill (SPMI) patients in the US living in the community increased. Yet a growing minority of people with severe illness are worse off because they are homeless or incarcerated. In this case study, IBM Global Research and Otsuka Pharmaceuticals used an agent-based approach to model these remarkable swings.
  • Outpatient Appointment Scheduling Using Discrete Event Simulation Modeling
    Indiana University Health Arnett Hospital, consisting of a full-service acute care hospital and a multispecialty clinic, faced poor statistics because the number of no-show patients (those who don’t show up for their scheduled appointments) rose dramatically to 30%. This was primarily connected to the fact that clinic schedules were driven by individual preferences of the medical staff, which led to increased variations in scheduling rules. To eliminate the problem, the client wanted to develop a scheduling methodology that would benefit the clinic, doctors, and patients.