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Examining Healthcare Policy for Surgical Oncology Delivery


Examining Healthcare Policy for Surgical Oncology Delivery

In cancer patients, an inability to access the surgical system can be lethal, but accessing it can be impoverishing, especially in low- and middle-income countries (LMICs).  A group from the Global Surgery and Social Change, Department of Global Health and Social Medicine, Harvard Medical, supported by National Cancer Institute used AnyLogic Software to evaluate the health, financial, and equity impacts of governmental and charitable policies for surgical oncology in a resource-limited setting.

Outpatient Appointment Scheduling


Outpatient Appointment Scheduling

Indiana University Health Arnett (IUHA) is an integrated healthcare system which consists of a full service acute care hospital and a multispecialty clinic with approximately 200 providers at numerous locations. In the past, provider schedules were driven by individual preference which led to increased variation in scheduling rules that failed to meet employer or patient expectations. To better serve patients and maintain provider approval, IUHA sought to develop a scheduling methodology that provides same day access for a designated patient population while allowing acceptable access to the remaining patient population.

Beyond Market Mix Models


Beyond Market Mix Models

Traditional Marketing Mix models attempt to explore the tradeoffs amongst different marketing channels and the spends associated with them. The weaknesses of these models are, generally, their static nature and the restrictive assumptions required to apply their results. For these reasons, an American pharmaceutical company, one of the largest in the world, engaged with Sterling Simulation to explore the benefits of agent-based modeling, prior to launching a new product. The use-case was presented by Scott Hebert, Vice President of Sterling Simulation at the AnyLogic Conference 2015.

How Simulating Hospital Systems May Improve Care


How Simulating Hospital Systems May Improve Care

The Children’s Hospital of Philadelphia (CHOP) is well known as one the best places in the world for a child to come and get medical care. Less known, is the behind-the-scenes work of Dr. T. Eugene Day, Program Manager for Health Systems in the Office of Safety and Medical Operations to improve quality, safety, and overall patient care. Like many hospitals, CHOP is met with a multitude of challenges beyond the daily task of performing life-saving procedures and providing care for patients. Dr. Day utilizes simulation modeling with AnyLogic software to identify opportunities and aid planning for systemic improvements versus typical approaches.

Beyond Marketing-Mix Models


Beyond Marketing-Mix Models

A multi-national pharmaceutical company recently launched a new non-generic drug. Since the company already owned the leading non-generic drug in that market, cannibalization was a concern. The goal was to create market share for the new drug, while maintaining or increasing market share for the well-established drug by modifying types of promotional spend. Traditionally, the Analytics Department would employ a Marketing-Mix Model (MMM) to determine the impact of promotional spend, but the company was looking for further insight into the mechanics behind the MMM. After exploring multiple options, they determined agent-based modeling, and ultimately AnyLogic would allow for the greatest flexibility and visualization.

Immunization Program Evaluation


Immunization Program Evaluation

Alexander Doroshenko, Weicheng Qian and Nathaniel D. Osgood from the Division of Preventive Medicine at the University of Alberta in Canada were recently published in PeerJ, an Open Access, peer-reviewed, scholarly journal. It considers and publishes Research Articles in Biological and Medical Sciences. The objective of the University of Alberta project was to investigate the effect of outbreak response immunization (ORI) among adolescents as an emergency public health intervention in light of a recent re-emergence of pertussis outbreaks. ORI is supplementary immunization given over and above the routine vaccination schedule, including to those who may be fully immunized or those who did not receive their scheduled vaccines.

Warehouse Modeling and Optimization Saves Millions for Cardinal Health


Warehouse Modeling and Optimization Saves Millions for Cardinal Health

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.

IBM Project Published in Journal of Medical Systems and Recognized by the United States House of Representatives


IBM Project Published in Journal of Medical Systems and Recognized by the United States House of Representatives

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.

Cancer Cell Growth Using Game Theory in AnyLogic PLE


Cancer Cell Growth Using Game Theory in AnyLogic PLE

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.