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Using System Dynamics to Improve Patient Care

Using System Dynamics to Improve Patient Care

By Şanser Güz, Orkun İrsoy, and Naz Beril Akan

Why do many people practice and advocate systems thinking in biomedical sciences? The human body is a system with strong regulatory mechanisms that maintain the steady state of internal physiological conditions, homeostasis. The regulatory mechanisms of various subsystems of the body emerge from the interaction of feedback signals and provide the body with an internal balancing structure against natural disturbances. But what if the disturbances are far from natural, what if they are chronic or repetitive or interfering with the system itself? Such disruptions in those well-regulated homeostatic systems are the possible leverage points where systemic analysis can add a great deal of value.  These valuable insights can range from deepening inferences about the internal causes to providing alternative methods to alleviate the problem.

Hematological dynamics, in particular, is one of the topics well-covered in the field of System Dynamics, not because of its popularity but due to its inherent delay and feedback-rich nature. Unidirectional thinking falls short in providing successful management of such systems, which attracts the system thinkers. Not surprisingly, including ours, 3 out of 4 articles in the special issue of System Dynamics Review on Biomedical Modeling are related to hematological dynamics.

In our recent study, we take on a hematological disorder called chemotherapy-induced neutropenia (CIN). Along with its targets, the malignant tumors, chemotherapy also damages the valuable stem cell stocks in the bone marrow as a “side effect”. So why are stem cells so valuable to begin with? Stem cells are the earliest precursor cells in the blood cell production chain. When their stock is damaged by a strong disturbance such as chemotherapy, it results in a short supply of blood cells which can only be observed after a certain time. Effectively, we are dealing with a physiological high order supply chain residing in the human body. When the chemotherapy hits the production facility, effects are visible at the consumer level (i.e. blood cells in circulation) after several material delays. 

Aforementioned internal homeostatic regulation is strong, however, for a disturbance that is repetitive.  Having delayed effects such as chemotherapy, endogenous mechanisms may prove to be insufficient to address it. Intensive chemotherapy regimens often result in short supply and oscillations in the leading white blood cells of the immune system, the neutrophils, giving rise to chemotherapy-induced neutropenia (CIN). This is a risky condition for a patient having cancer treatment as it leaves the patient with a vulnerable immune system, against even the simplest of infections. Granulocyte-Colony Stimulating Factor (G-CSF) is the supplementary agent used in the treatment of CIN, stimulating neutrophil production from many stages. However, long delays along the blood cell production chain, susceptibility of stem cells to chemotherapy, and mobilizing effect of G-CSF which depletes the neutrophil reservoir, eventually creates multiple trade-offs inhibiting an easy solution.

In our work, “Dynamic trade-offs in granulocyte colony-stimulating factor (G-CSF) administration during chemotherapy”, we modeled the process in the light of available evidence and previous mechanistic models from other domains of research. With this research, we were able to provide insights on which physiological processes are at play in shaping the patient’s response to treatment and which loops are dominant for the prescription of https://www.papsociety.org/xanax-alprazolam-1-mg/ treatment protocols. Even though the base model was built for a standard patient profile, we see this study as an advancement towards personalized treatments of CIN and plan to build on this subject in future research. We imagine a flight simulator that can be calibrated for individual patients that can be used for generating effective personalized treatment protocols. Following this path has the potential to alleviate neutropenia for people under chemotherapy and improve patient care in a personalized manner.

We started studying the management of CIN nearly two years ago as our bachelor’s graduation project topic.  The work evolved continuously during this time period, with its latest output being this journal article. Our group of three worked on this long enough that System Dynamics and chemotherapy-induced neutropenia became one emerged bilateral entity, and it is only half a joke. As we delved deeper into medical literature and System Dynamics simultaneously, we found astonishing similarities in storytelling on both sides. Our task as modelers was to make a necessary language translation between two mediums and to make an adequate implementation of the method at hand. Because of this very similarity, endogenous feedback structures and systems modeling have been well recognized among the people of medicine. Hence, System Dynamics practitioners like us can use this opportunity to direct their work in this domain of research, where the toolset they use has the potential to systemically analyze, give useful returns, and make a positive change.

 

 

Want to learn more about Biomedical Modeling?

Join us for a Seminar on the special issue of the System Dynamics Review! 

June 09 @ 11 am NY

 CALL TO ACTION

  • Find Modelers…do you envision a similar project? contact the society to be connected to modelers to help you out (have it go to rebecca@systemdynamics.org)
  • Join now for free access to the journal

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Practitioner Profile: Douglas McKelvie, Symmetric Scenarios

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Welcome to Practitioner Profiles, a series of up-close blog-length interviews with experienced System Dynamics practitioners.  We have a standard set of 10 questions and let practitioners take the responses in any direction they choose.  They tell us about who they are, how they got involved with the field, how they work with clients, and in what new directions they may be heading.  A new profile will be posted every few weeks during 2021. 

For any questions or comments, please contact the editors of these interviews, Dr. Jack Homer (jack@homerconsulting.com) and Dr. Saras Chung (saras@skipdesigned.com). 

For today’s spotlight, we talked with Douglas McKelvie with Symmetric Scenarios. 

What kinds of SD project applications does Symmetric Scenarios do?

Our emphasis is on health and social care and related domains, such as services for children, criminal justice, and workforce development and planning.  

What is the history of the organization?

Symmetric was founded in 2005 by a small group led by Eric Wolstenholme.  Initially, Eric, David Todd, and I were the main modelers, working alongside non-modeler colleagues, David Monk and Steve Arnold, who came from health services management.  David Todd returned to New Zealand ten years ago, and Eric gradually retired. Now, I work with Donald Scott, a former social work colleague. Eric still contributes valued insights and mentorship.

What is your current role with the organization?

As owner, I run the business.  I take the lead on model building (typically group model building), where I work with expert facilitators and other associates.  I am based in Edinburgh and work across the United Kingdom, occasionally beyond.

What is distinctive in your approach to SD projects?

We almost always simulate, true to Forrester’s maxim that you cannot tell how a complex system will behave from a diagram alone.  STELLA’s modular capabilities have made a big difference to how we develop models.
Our models often combine some simple structures, such as capacity-constrained service pathways, ageing chains, workforce chains, and financial flows. Modules make it much easier to lay out such structures.

How else is Symmetric distinctive?

For several of us, a strong commitment to a particular area, human services, pre-dated our interest in SD.  And we collaborate—for example, we are currently working with action researchers on the subject of family support.

How did you originally get interested in System Dynamics, and when was that?

My first career was as a social worker. In the 1990s, I had a national policy role, planning the Scottish social services workforce.  Concurrently, I did masters study that introduced me to simulation.  In 2002, I moved into consultancy, fortuitously becoming a colleague of Eric Wolstenholme and learning SD from him.

What individuals and organizations are inspirations to you?

Many.  I aspire to combine Eric’s insights on service flows and capacity constraints with the pioneering work by Jack Homer and Gary Hirsch on the dynamics of specific diseases.  I admire how John Sterman and Kim Warren explain SD clearly and concisely.  I also enjoy model-chat with Sarah Wylie Boyar.  And I feel indebted to isee systems, who keep extending the power of STELLA for modelling and communicating insights.

What have you been able to achieve with your SD modeling?

It’s important that our models have integrity and provide meaningful insights for the client.  These insights may sometimes seem obvious to a systems thinker, but they do not start that way for our clients.  For example, in the UK health system, the discourse around waiting times distorts people’s mental models to the point that they forget the simple physics of capacity limitation.  When people become expert at managing the problems generated by poorly designed systems, they can end up confused about cause and effect.  We try to shift their mental models so they can see how things work and what is possible.

What challenges have you experienced with respect to SD project work?

There’s usually a point in the project when everybody wants to see a full running model, and you have to commit to a level of granularity and a policy time horizon.  That can be a stressful time, having to place a bet on how best to address the client’s questions.  Also, there’s the issue of data.  For all the talk of being ‘data-led’, few organizations have a proper comprehensive approach to data collection.  Wouldn’t it be nice to start every project with time series data covering all key variables?

What kinds of work would you like to be doing over the next 5 years?

I’d like to spend more of my time training people in how to build good models, as well as developing exploratory models based on my own interests.  Also, I’d like to write more.  Eric Wolstenholme and I published a book in 2019, The Dynamics of Care (Springer), outlining a variety of models built by Symmetric.

Have questions/comments? Reach out to Douglas McKelvie or leave a note below in the comments!

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