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Healthcare services are being redesigned and improved in terms of reducing waste, enhancing the patient experience and contributing to population health. Models linked with data about individual patients and particular services are being used to improve clinical decisions by health professionals, engaging patients and their carers in self-management, and tailoring treatment approaches to individuals based on their genetics, body system physiology, psychology and social networks. Modelling and simulation are also used at the policy and program level to evaluate the cost effectiveness of mixtures of interventions, not only in testing and treatment, but also in health promotion and risk prevention. An important aspect is to understand the different results of programs in different contexts, especially in terms of social determinants of health and changes in health disparities and inequities. The challenges of organizing health and social systems to improve wellbeing, healthcare value and accessibility require multiple ways of abstracting problem situations at the aggregate and individual level, including process and agent interaction events, and understanding feedbacks and network structures. AnyLogic can combine theory and data in simulation models which can test interventions in different virtual experiment scenarios to assess their suitability for a particular country, region, organization, service or target group.
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Reviews & testimonials

  • 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
  • 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 sufficiently flexible to support systems and policy research, yet robust enough to produce stand-alone applications that can be used by others to support their professional work.

    Neil McEvoy,
  • The most flexible simulation modeling tool on the market - 1) through the Java platform and access to Java programming when needs for tailor-making the model appears 2) through the possibility to mix different modeling methods. Good libraries with predesigned objects and building blocks (with great flexibility in themselves), continuous improvements and enhancements in new versions, and a very good and customer-oriented support function, makes the big picture more or less complete in my view!

    Stefan Bengtsson,
    County of Stockholm
  • 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
  • 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
  • AnyLogic is proved to be a very useful tool as I can build simulations using different simulation methodologies and create intuitive and appealing interfaces for end-users. Most functionality is available as predefined objects but it is nice to have the flexibility to add your own structures if necessary. Their technical support team is very knowledgeable and responsive; their support has been outstanding in my experience.

    Principal Informatics Scientist,
    AstraZeneca Pharmaceuticals
  • 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,
  • 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
  • I've used AnyLogic and a number of other simulation tools as part of hospital services design over many years. I prefer AnyLogic for its flexibility and multimodal capabilities and wholeheartedly recommend it.

    Keith Stockman,
    Monash Health
  • I have been using AnyLogic for a few years for models in the social and healthcare context. I like that you can start using it almost out of the box and get some results with straightforward presentations. I like the fact that I can mix and match simulation paradigms like ABM and System Dynamics... in my models keeps my opportunities open. Easy interface with Java classes or libraries makes the full system customizable. I can easily publish the models to a web site or for individual deployment. And last but not least, I can work in teams by using typical source control SVN...

    David Lovece,
    Northeastern University
  • I've been using AnyLogic for the last two years, and I think is the most complete and useful simulation software in the market. I’ve also had experience with other tools, and none of them are capable of integrating the multimethod modeling paradigm, and AnyLogic is. If you have a low background in programming, probably your learning curve can be hard at the beginning, however once you get some experience, you can simulate anything. Currently, we use AnyLogic as simulation tool for several projects, like logistics, or clinical activities, or patient/staff flow modeling. If you are looking for a complete solution, this can be a good choice.

    Alvaro Gil,
    Jewish General Hospital - Montreal

These companies already use AnyLogic for healthcare

Case Studies

  • 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.
  • Modeling of a Pharmaceutical Product Launch
    One of the huge pharmaceutical companies employed Bayser Consulting for development of product launch strategy. Simulation modeling was applied for reconstruction of interactions between the company, doctors and patients.
  • 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.