Healthcare innovation: System Dynamics saves Mayo Clinic 35% ESA drug costs & improves ESRD patients’ quality of life

Here’s an example healthcare industry case study that quantifies the value of System Dynamics. I saw the presentation at the 2011 International System Dynamics Conference. The presentation made an impression as it clearly explained the complex medical problem, how System Dynamics was used to create teh solution, and financial benefits.

Case study of healthcare innovation: System Dynamics computer model helps Mayo Clinic improve anemia management, substantially reduce treatment cost, and improve quality of life of End Stage Renal Disease (ESRD) patients.

Mayo Clinic is a nonprofit medical care provider and research group based in Rochester, Minnesota. In 2012, they treated over one million unique clinic patients.

This study is conducted by researchers from Advance Management Group, LLC, Mayo Clinic, and Dana-Farber Cancer Institute. The paper, Individualized Medicine and Biophysical System Dynamics: An Example from Clinical Practice in End Stage Renal Disease, is by Jim Rogers, Edward Gallaher, Craig Hocum, David Dingli, T. Ronald Chrisope, James McCarthy.

BACKGROUND: hemodialysis patients

According to the CDC ((CDC: “In 2011, kidney disease was the ninth leading cause of death in the United States. More than 10% (>20 million) of U.S. adults aged ≥20 years have chronic kidney disease (CKD), and most of them are unaware of their condition. If left untreated, CKD can lead to kidney failure, requiring dialysis or transplantation for survival”)), more than 10% (over 20 million) of U.S. adults aged 20 years and older have chronic kidney disease (CKD), also known as chronic renal disease. Most are not aware of their condition. If left untreated, CKD can develop into more severe conditions.

Kidney produces Erythropoietin or EPO, a hormone that induces red blood cell production. So without proper kidney function, one of the severe conditions is anemia caused by chronic renal failure. Patients who develop this type of anemia mostly use Erythropoietic Stimulating Agents (ESA) to manage the condition.


ESAs were in use since 1988 but the drug remains expensive (U.S. government’s Medicare reimbursements for ESA in 2008 approached two billion dollars). Furthermore, even with 25 years of use and refinement of treatment process, the drug can still cause side effects.

Mayo Clinic noticed this major problem: The standard ESA treatment protocols lead to undesirable oscillations in hemoglobin (Hgb) levels. An example of Hgb flucations result from standard ESA treatment protocol on the left:

Sample patient hemoglobin level with standard ESA treatment and with System Dynamics model perscribed personalized medicine

Sample patient hemoglobin level with standard ESA treatment and with System Dynamics model perscribed personalized medicine


Problem for patients: they can suffer health risks when their hemoglobin is not in the optimal range. The patients require additional medical treatments. Their quality of life suffers. According to the research, Hgb “values that are too low lead to anemia, fatigue, and poor quality of life, whereas values that are too high are associated with increased risk of cardiovascular disease and stroke. ”

Problem for Mayo Clinic: additional staff time and hospital resources are required to treat patients with abnormal Hgb levels.


A System Dynamics bio-pharmacokinetic computer model of erythropoiesis was created to determine the cause of oscillation.

Researchers discovered that the oscillations are due to time delay of the Erythropoietin Stimulating Agents. The causal loop diagram shows with a normal person, kidney regulates blood oxygen level by increasing Erythropoietin. But with ESRD patients, that function is not available (crossed out in the lower corner). The patients require ESA Therapy. The problem is that there’s a 15-20 day delay.

ESA Therapy System Dynamics Causal Loop Diagram

ESA Therapy System Dynamics Causal Loop Diagram

A System Dynamics computer model was created to help calculate the optimal personalized medicine prescriptions for each individual:

Mayo Clinic ESRD patient ESA treatment System Dynamics computer model

Mayo Clinic ESRD patient ESA treatment System Dynamics computer model


Result from this Mayo Clinic System Dynamics study:

  • “Examined prevailing mental models of erythropoiesis and brought about significant changes in understanding”
  • Improved patient care
  • Saved hospital money (ESA prescription)
  • Saved hospital staff time (fewer admissions due to Hgb oscillation)

Improved patient care:

“This new understanding has compounded healthcare value delivery in a number of significant ways: (i) Patients feel better, are more compliant and more motivated to continue with the rigors of life on hemodialysis, (ii) since patients have adequate and stable Hgb values, patient care is simplified and (iii) when Hgb values change or even make excursions above or below the target range, this triggers a search for the development of concomitant problems (e.g. bleeding) leading to an improvement in medical care.”

“Exceptional performance” of System Dynamics computer model. 63% reduction of high risk patients over two years (p.15 Figure 8 caption):

“The percentage of patients with Hgb [over] 13 has been reduced from 30% in 2007 to 11% at the end of 2009. In the industry, this is exceptional performance.”

Mayo Clinic System Dynamics personalized medicine prescription benefit

Mayo Clinic System Dynamics personalized medicine prescription benefit

Reduced ESA drug costs results in savings of $3.3 million over a three-year period (p.16 Figure 9):

“During January 2007 through January 2007, we tested the model based protocol extensively. As our confidence in the model increased, we enrolled patients at a faster rate. EAS use was reduced by 37%, reducing expenses by $1.1M per year over the 36 month period. (297 – 185) * 2.66 per mcg * 311 patients * 12 months per year = $1.1 M per year.”

Reduced hospital resource requirements:

“Anemia management resource requirements have been reduced by more than 50%.”


As an opportunity for other System Dynamics practitioners in healthcare innovation, the study noted: “Such an approach can be applied to other pathophysiologic systems.

At the 2011 presentation, the researchers said a product is under development for the wider medical industry. So, what happened since then?

SDwise got in touch with McCarthy, James T., M.D. of Mayo Clinic. He declined to comment at this time for reasons of confidentiality. He wrote that there’s a possibility that he can offer some comments in six to eight months.

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