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Jack Homer, Andrew Jones, Don Seville Homer Consulting & Sustainability Institute Joyce Essien

The CDC’s Diabetes Systems Modeling Project: Developing a New Tool for Chronic Disease Prevention and Control. Jack Homer, Andrew Jones, Don Seville Homer Consulting & Sustainability Institute Joyce Essien Rollins School of Public Health, Emory University Bobby Milstein Dara Murphy

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Jack Homer, Andrew Jones, Don Seville Homer Consulting & Sustainability Institute Joyce Essien

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  1. The CDC’s Diabetes Systems Modeling Project: Developing a New Tool for Chronic Disease Prevention and Control Jack Homer, Andrew Jones, Don Seville Homer Consulting & Sustainability Institute Joyce Essien Rollins School of Public Health, Emory University Bobby Milstein Dara Murphy Centers for Disease Control and Prevention International SD Conference Oxford, U.K. July 27, 2004

  2. SAFER • HEALTHIER • PEOPLE ™ Client and Issue • Client: CDC’s Division of Diabetes Translation • Policy and Epidemiology Branches • Issue: What are the pros and cons of “upstream” (prevention) and “downstream” (control) efforts?

  3. Public Health Efforts Today Upstream Prevention and Protection ---------------------------------- Total  3% Downstream Care and Management -------------------------------- Total  97%

  4. Growth of Obesity and Diabetes in the U.S. & with Diagnosed Diabetes Diagnosed Dx diabetes TIME Magazine Cover Story, 8 December 2003.

  5. Upstream Downstream Model Structure BMI/Obesity Clinical Management of Diagnosed PreD & Diabetes

  6. Base Run Diabetes Prevalence Obesity Prevalence 0.15 0.5 0.125 0.4 0.1 0.3 0.075 0.2 0.05 0.1 1980 1990 2000 2010 2020 2030 2040 2050 1980 1990 2000 2010 2020 2030 2040 2050 Time (Year) Time (Year) Deaths per Population Deaths per Complicated 0.0035 0.08 0.003 0.07 0.0025 0.06 0.002 0.05 0.04 0.0015 1980 1990 2000 2010 2020 2030 2040 2050 1980 1990 2000 2010 2020 2030 2040 2050 Time (Year) Time (Year)

  7. Downstream Downstream-Only Intervention Deaths per Population 0.0035 0.003 Base 0.0025 0.002 0.0015 1980 1990 2000 2010 2020 2030 2040 2050 Time (Year) Blue: Base run; Red: Clinical mgmt of diagnosed up from 66% to 90%

  8. Upstream Upstream-Only Intervention Deaths per Population 0.0035 0.003 Base 0.0025 Downstream 0.002 0.0015 1980 1990 2000 2010 2020 2030 2040 2050 Time (Year) Blue: Base run; Red: Clinical mgmt up from 66% to 90%; Green: Caloric intake down 4% (99 Kcal/day)

  9. Mixed Mixed Intervention Deaths per Population 0.0035 0.003 Base 0.0025 Upstream Downstream 0.002 0.0015 1980 1990 2000 2010 2020 2030 2040 2050 Time (Year) Blue: Base run; Red: Clinical mgmt up from 66% to 90%; Green: Caloric intake down 4% (99 Kcal/day); Black: Clin mgmt up to 80% & Intake down 2.5% (62 Kcal/day)

  10. Linking Insights to Action • Cross-stakeholder model-based learning laboratories • Analyzing the effectiveness of goal-setting

  11. +24% No progress +14% Meet onset goal (-29%) 2010 prevalence goal 2000 prevalence goal -38% -11% Goals, Actual Performance, and Model Runs Diagnosed Prevalence Fraction Relative to 2000 Value 1.5 “It felt like we flunked” 1.25 +33% 1 0.75 0.5 1990 1995 2000 2005 2010 Time (Year)

  12. Level rises until the inflow is less than the outflow Onset * Large inflow, double the outflow Small outflow, people can live for decades with the disease Deaths Chronic Disease Prevalence * * Diagnosed

  13. “It is expected that if you do a good job, things ought to go down.” – Diabetes Branch Leader

  14. Level falls as inflow quickly drops below outflow Onset Large inflow, but usually fast to reduce Large outflow via recovery or death Deaths Recovery Acute Infectious Disease Think measles, flu or SARS Prevalence

  15. Three of the Resulting Actions • Head of the division amended the 38% goal for prevalence to say that they are not aiming for a decline • Clients now broadcasting an improved mental model for chronic disease • Epidemiology and Policy leaders co-writing their first paper on using SD to improve internal consistency of goals

  16. Bridging the SD/Audience Divide • Sometimes a stock/flow-dominated model is what client needs • Help client to identify and communicate the shortcomings of old mental models and benefits of the new

  17. Supplementary Materials

  18. Possible Areas for Intervention BMI/Obesity Clinical Management of Diagnosed PreD & Diabetes

  19. Now CDC is Exploring More “Upstream” Interventions Diabetes onset Complications onset Deaths from complications Obese Fraction of Population Caloric Intake Mean body weight/BMI Basal metabolic rate Caloric balance Physical Activity

  20. Past Focus of Interventions into the Diabetes System Has Been “Downstream” Diabetes onset Complications onset Deaths from complications

  21. Bridging the Divide • Learn client’s analytic needs and turn-ons • “Go Native” in language and form • Help client to identify and communicate shortcomings of old mental models

  22. Missing Goals Was Attributed as Failure • “The current epidemiology of type 2 diabetes could be used to argue that the [National Diabetes Prevention and Control Program] has been a monumental failure… [One] hypothesis, that this is a little known government bureaucracy spending large sums of money without achieving the desired goals, cannot be refuted based on the information at hand.” • Anonymous reviewer of paper by client

  23. What We Did • Used model to check realism of objectives • We “Went Native” in language and form • Fit to their variable names • Results in table format, not graphs

  24. We’ll Focus On the Two Stocks that, Together, are “Diagnosed Prevalence” Diabetes onset Complications onset Deaths from complications Obese Fraction of Population Caloric Intake Mean body weight/BMI Basal metabolic rate Caloric balance Physical Activity

  25. The Public Health Challenge of Chronic Disease • Leading cause of illness, disability, and death in developed countries • 70-80% of U.S. health care claims • Over 50% of U.S. adult population have at least one chronic disease; 25% have two or more • A systems approach is needed • Dynamic complexity: Long delays of disease progression • Need SD for better goal-setting, priorities, coordination • Need to understand over-time impacts of “upstream” and “downstream” interventions

  26. SAFER • HEALTHIER • PEOPLE ™ Chronic Disease Interventions, and the CDC’s Stated Mission “UPSTREAM” “DOWNSTREAM” “CDC: Enhancing Health Protection!” – Dr. Julie Gerberding, Director

  27. Diabetes Stocks & Flows Diabetes onset Complications onset Deaths from complications Obese Fraction of Population Mean body weight/BMI Caloric Intake Basal metabolic rate Caloric balance Physical Activity

  28. In 2000, They Set HP 2010 Goals “It is expected that if you do a good job, things ought to go down.”

  29. People with Undiagnosed Diabetes Diabetes onset People with And if the deaths flow drops 11% Normal Diagnosis Glycemic rate Levels If the diagnosis flow rises sufficient to boost the fraction diagnosed by 12 points People with Diagnosed Deaths from Diabetes complications It is physically impossible for the diagnosed prevalence to fall at all, much less 38% We Looked at the Stock/Flow Internal Consistency of the Objectives

  30. And if the deaths flow drops 11% If the diagnosis flow rises sufficient to boost the fraction diagnosed by 12 points It is physically impossible for the diagnosed prevalence to fall at all, much less 38% We Looked at the Stock/Flow Internal Consistency of the Objectives

  31. Unexpected Behavior from the Model +24% No continued progress +13% Meet onset goal Meet prevalence goal -38% “It is expected that if you do a good job, things ought to go down.” – Diabetes Branch Leader

  32. Recovery Interventions in infectious diseases boost an important outflow: recovery Exploring the Existing Mental Model: Infectious Disease People with Undiagnosed Onset Infectious Disease People with Diagnosis rate Normal Health People with Diagnosed Deaths from Infectious Disease complications “Even here in chronic disease, we are still living with the model that you find the patients, you give them a shot, and they recover.”

  33. +42% Meet detection goal +24% No progress +13% Meet onset goal (-29%) Meet prevalence goal -38% Unexpected Behavior from the Model Diagnosed Prevalence Fraction Relative to 2000 Value 1.5 1.25 1 0.75 0.5 1990 1995 2000 2005 2010 Time (Year) “It is expected that if you do a good job, things ought to go down.” – Diabetes Branch Leader

  34. One goal aimed to boost the fraction diagnosed by 12 points Another aimed for a 29% reduction in the onset rate Yet another aimed for the deaths flow to drop 11% Can they meet the goal of a 38% drop in diagnosed prevalence? Then 2000, they set goals for 2010, including Diagnosed Prevalence

  35. 3. Quarantines and vaccinations can cut onset significantly 1. People who die, die soon 2. Those who don’t die, recover naturally and quickly When you cut the inflow to a bathtub with two big drains, the water level falls quickly Exploring the Existing Mental Model: Acute Infectious Disease Think measles, flu or SARS People with Undiagnosed Onset Infectious Disease People with Diagnosis rate Normal Health People with Diagnosed Recovery Deaths from Infectious Disease complications

  36. In 2000, They Set HP 2010 Goals • In 2000, they set a goal of 38% reduction in diagnosed prevalence by 2010 • At same time, other goals for diagnosis and care • Fraction diagnosed up 12 percentage points • Reduce diabetes–related deaths among diagnosed by 11% “It is expected that if you do a good job, things ought to go down.” – Diabetes Branch Leader

  37. +33% History of Healthy People 2000 • In 1990, stakeholders set “Healthy People 2000” objectives • Goal for diagnosed prevalence was an 11% reduction between 1990 and 2000 • During 90s, significant advances • Combined effect by 2000 was 33% increase in diagnosed prevalence fraction • “It felt like we flunked” • Program person -11%

  38. Drivers Calibrated Using National Survey Data (Values shown are estimates for 2004.) 85% 20% 81% BMI/Obesity Clinical Management of Diagnosed PreD & Diabetes 66% 2,465 Kcal/day 480 Kcal/day 66% 84% 86% 60%

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