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Being #26 in last years’ Fortune 500 list, Cardinal Health is a billion dollar pharmaceutical distribution and logistics company. Its clients are hospitals, pharmacies, physicians, and individual consumers. They face a multitude of typical distribution warehouse challenges that are further complicated by the nature of pharmaceutical products, which are smaller in size, consumable, expensive, and could be life critical. Company’s warehouses have narrow passages, and workers operate big multilevel trolleys. That increases the probability of employees’ mistakes and makes these mistakes costly.

At the AnyLogic Conference 2014, Kyle Johnson, Global Business Services in Advanced Analytics and Optimization at IBM partnered with Otsuka Pharmaceuticals, presented a “Multi-Agent-Based Simulation of a Complex Ecosystem of Mental Health Care.” To date, the research paper was published in the Journal of Medical Systems and received the attention of the United States House of Representatives [1]. The project revolves around the housing cycle of the United State’s Severely and Persistently Mentally Ill (SPMI). An SPMI patient defines someone with a diagnosis of Schizophrenia, Bipolar Disorder, or Major Depressive Disorder, and this group constitutes about 1.7% of the US population. To better understand the condition and possible improvements, IBM Global Research and Otsuka Pharmaceuticals used an agent-based approach to model the SPMI living situations over the second half of the 20th century.

At the beginning of 2015 we were proud to release a free version of the software called PLE, or Personal Learning Edition meant for learning, teaching, and self-study. Since the release, we have been extremely impressed with not only the increase in the number of users but the complex projects produced with the free version. Our latest discovery is from Mihir Paithane, a student in the STEM (Science, Technology, Engineering, and Math) Program at Mills E. Godwin High School in Richmond, Va. Mihir built a model to analyze the “Effect of Cellular Interactions on Cancer Cell Growth Using Evolutionary Game Theory.” In this experiment, game theory was used to assess the interactions between three cell phenotypes usually found in cancer. The three defined cells were autonomous growth cells, invasive and motile malignant cells, and cells that performed anaerobic glycolysis. Based on preset variables in the payoff matrix, analytical equations were deduced that allowed for the analysis of the proportion of autonomous growth and malignant cells in a tumor. AnyLogic was also used to simulate the interactions between cancerous and healthy cells.

Do you apply simulation modeling in healthcare, or interested in learning more? Dr. Nathaniel Osgood, Associate Professor at University of Saskatchewan, has provided a series of video lectures, step-by-step tutorials, and example models that demonstrate how-to build multimethod, or hybrid simulation models. These models are utilized to solve problems in the area of health research. Dr. Osgood focused his materials on multimethod model-building because he believes it can provide greater capacity to respond to a modeler’s intention, and is capable of more precisely addressing various research questions. As a result, AnyLogic is his simulation software of choice.

“Cesarean delivery” is a method of childbirth in which a surgeon cuts through the pregnant woman’s abdomen and uterus to deliver the baby. The more natural method of childbirth is called “vaginal delivery”, in which the baby leaves the mother’s uterus through her vaginal canal. Ideally, cesarean delivery would only be used when vaginal delivery would endanger the life or health of the child or mother, because cesarean delivery involves major abdominal surgery that is accompanied by much greater risks for both mother and child than vaginal delivery. Cesarean delivery also costs about 50 percent more. Over the last 40 years, the U.S. rate of cesarean delivery has increased dramatically.

There are many cases of simulation modeling in healthcare. Application areas can vary, from process optimization in hospitals to macrolevel agent-based epidemiology models. Due to its multimethod nature, AnyLogic allows models to be built at various abstraction levels. A good illustration of how researchers and consultants can apply the same tool to different problems is the three models built by the Stockholm County Health Administration in Sweden. The models included macro, meso, and micro abstraction level applications in healthcare simulation. The microlevel model simulated the maternity ward in a hospital that was currently under construction. The purpose of the model was to support discussions related to which resources, capacity, and work methods were required in the new ward. One relevant discussion was whether to keep mother and child in the same room during their entire stay or to have dedicated rooms for antenatal care, delivery, and postnatal care.

An initiative of the Department of Mechanical and Industrial Engineering at the University of Toronto, the Centre for Research in Healthcare Engineering (CRHE) is a response to the immediate and compelling desire for efficiency and quality improvements in the Canadian health care system. CRHE is committed to both research and education in the field of healthcare delivery. From an academic perspective, their work falls into two categories: research and service. A study completed by the Commenwealth Fund Commision (http://www.commonwealthfund.org/) ranked Canada very low in the categories of quality of health care, access to health care, efficiency, equity and expenditures. This study among others, prompted the CRHE to dedicate a research project that would test potential changes in Canadian healthcare policy that could increase the quality of patient care.

Before launching a new drug, a pharmaceutical company should decide the optimal promotional mix for both patient and doctors, and the optimal sampling level, high enough to induce therapy without cannibalizing paid prescriptions. Using AnyLogic Simulation Modeling, JP Tsang, Ph.D. & MBA, addresses the complexities of launching a new drug in the pharmaceutical industry, the need for a Contract Sales Organization (CSO) and the influence of Key Opinion Leaders (KOL). The project zeroed in on the medical group practice in order to better understand the dynamics between physician and patient, and between physician and medical representatives. The Agent Based Model (ABM) allows you to understand local behavior, identify bottlenecks regarding certain output variables and better grasp the big picture.

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. The AASI assembled routine care data upon reimbursement of heath care providers, which includes drugs prescribed, services rendered and diagnosis. Typical statistics and mathematical modeling were considered as a tool to analyze the data, but simulation was chosen to ensure the mass amount of data could be fully utilized, thus increasing the accuracy of the analysis and results.

The University of Erlangen-Nuremburg Computer Networks and Communication Systems group specializes in the simulation of large-scaled complex systems such as healthcare, automotive, industry and energy. One of the latest projects concerned the possibility and location of Mobile Stroke Units (MSU’s) due to the increase of stroke victims in an aging population. A stroke is typically caused by Thrombosis and should be treated with thrombolysis. Stroke causes severe disability and produces high costs for care and rehab if not treated quickly.