1. Syndemics Prevention Network System Dynamics and the Physics of Possibility in Health Policy Tools for Developing a Dynamic Understanding of Access-to-Care Options During HIV Prevention Trials Family Health International October 25, 2004 Chapel Hill, NC Jack Homer Homer Consulting Voorhees, New Jersey Bobby Milstein Centers for Disease Control and Prevention Atlanta, Georgia

2. Syndemics Prevention Network The Dynamic Dilemma of HIV Prevention Trials

3. Syndemics Prevention Network

4. Syndemics Prevention Network “When we attribute behavior to people rather than system structure the focus of management becomes scapegoating and blame rather than the design of organizations in which ordinary people can achieve extraordinary results.” -- John Sterman Sterman J. System dynamics modeling: tools for learning in a complex world. California Management Review 2001;43(4):8-25. “The tendency to blame other people instead of the system is so strong that psychologists call it the fundamental attribution error.” Beyond Scapegoating

5. Syndemics Prevention Network Time Series Models Describe trends Multivariate Stat Models Identify historical trend drivers and correlates Patterns Structure Events Increasing: Depth of causal theory Degrees of uncertainty Robustness for longer- term projection Value for developing policy insights Increasing: Depth of causal theory Degrees of uncertainty Robustness for longer- term projection Value for developing policy insights Dynamic Models Anticipate future trends, and find policies that maximize chances of a desirable path Tools for Policy Analysis Developed by Jack Homer, Homer Consulting

6. Syndemics Prevention Network Different Modeling Approaches For Different Purposes Logic Models (flowcharts, maps or diagrams) System Dynamics (causal loop diagrams and simulation models) Forecasting Models Articulate steps between actions and anticipated effects Improve understanding about the plausible effects of a policy over time Focus on patterns of change over time (e.g., long delays, worse before better) Make accurate forecasts of key variables Focus on precision of point predictions and confidence intervals

7. Syndemics Prevention Network Questions for Today What are system dynamics models? What questions guide their development? What the analytic steps involved? How can they be used to support learning and effective, transformative action? How can we begin thinking about the dynamic forces that affect HIV prevention trials? Examples from Diabetes Modeling

8. Syndemics Prevention Network System Dynamics Focuses on the Connection Between Behavior and Structure System behavior is determined by feedback structure -- including accumulation, delay, and nonlinear response Problem Situation 8 6 4 2 0 02468101214161820 Seconds elapsed Ounces Water Level Over Time System BehaviorSystem Structure

9. Syndemics Prevention Network Water Glass Model Diagram (Vensim ™ software) Current water level Water flow Desired water level Water level gap Perceived water level gap Time to perceive water level gap Faucet openness Water flow at full open Maximum faucet openness decision

10. Syndemics Prevention Network Re-Directing the Course of Change Questions from System Modeling and Social Navigation 20202010 How? Why? Where? Who? People with Diagnosed Diabetes, US 0 5 10 15 19801985199019952000 Million people Data Source: CDC DDT and NCCDPHP. -- Change in measurement in 1996.

11. Syndemics Prevention Network Steps for Developing Dynamic Policy Models Enact Policy Build power and organize actors to establish chosen policies Test Proposed Policies Search for policies that best govern change Test Proposed Policies Search for policies that best govern change Run Simulation Experiments Compare model’s behavior to expectations and/or data to build confidence in the model Create a Dynamic Hypothesis Identify and map the main causal forces that create the problem Convert the Map Into a Simulation Model Formally quantify the hypothesis using all available evidence Identify a Persistent Problem One that exists due to dynamic complexity

12. Syndemics Prevention Network Diabetes System Modeling Project Where is the Leverage for Health Protection? People with Undiagnosed, Uncomplicated Diabetes People with Diagnosed, Uncomplicated Diabetes People with Diagnosed, Complicated Diabetes People with Undiagnosed PreDiabetes People with Diagnosed PreDiabetes People with Undiagnosed, Complicated Diabetes People with Normal Glycemic Levels Diagnosing Diabetes Diagnosing Diabetes Diabetes Detection Dying from Complications Developing Complications Diabetes Control PreDiabetes Detection Diagnosing PreDiabetes Diabetes Onset PreDiabetes Control PreDiabetes Onset Recovering from PreDiabetes Recovering from PreDiabetes Obesity Prevention Homer J, Jones A, Seville D, Essien J, Milstein B, Murphy D. The CDC diabetes system modeling project: developing a new tool for chronic disease prevention and control. 22nd International Conference of the System Dynamics Society; Oxford, England; 2004.

13. Syndemics Prevention Network Diabetes System Modeling Project Where is the Leverage for Health Protection? People with Undiagnosed, Uncomplicated Diabetes People with Diagnosed, Uncomplicated Diabetes People with Diagnosed, Complicated Diabetes Diagnosing Uncomplicated Diabetes People with Undiagnosed PreDiabetes People with Diagnosed PreDiabetes Diagnosing PreDiabetes Developing Complications from Undx diab Developing Diabetes from Undx PreD, People with Undiagnosed, Complicated Diabetes Diagnosing Complicated Diabetes Dying from Undx Complications People with Normal Glycemic Levels Diabetes Detection Obese Fraction of the Population Risk for PreDiabetes Caloric Intake Physical Activity PreDiabetes Control Diabetes Control PreDiabetes Detection Medication Affordability Ability to Self Monitor Clinical Management of PreDiabetes Adoption of Healthy Lifestyle Clinical Management of Diagnosed Diabetes Living Conditions Personal Capacity PreDiabetes Testing for Access to Preventive Health Services Testing for Diabetes PreDiabete s Onset Recovering from PreDiabetes Recovering from PreDiabetes Diabetes Onset Dying from Complications Developing Complications

14. Syndemics Prevention Network Selected Data Sources for Model Calibration High Risk Population, Incidence, Prevalence, Deaths –National Diabetes Statistics: http://diabetes.niddk.nih.gov/dm/pubs/statistics/index.htm –Prevalence of Selected Chronic Conditions: United States, 1990-1992: http://www.cdc.gov/nchs/data/series/sr_10/sr10_194.pdf –Healthy People 2000 Review, 1997: http://www.cdc.gov/nchs/data/hp2000/hp2k97.pdf –Deaths: Preliminary Data for 2000: http://www.cdc.gov/nchs/data/nvsr/nvsr49/nvsr49_12.pdf –Estimated number of adults with prediabetes in the U.S. in 2000: opportunities for prevention, Benjamin SM et al (DDT/CDC), Diabetes Care 26: 645-9, 2003. –A Dynamic Markov Model for Forecasting Diabetes Prevalence in the United States through 2050, Honeycut AA et al. (DDT/CDC), Health Care Mgmt Sci 6: 155-164, 2003. Complications and Benefits of Control –Model of Complications of NIDDM--1. Model Construction and Assumptions, Eastman RC et al, Diabetes Care 20: 725-734, 1997. –Model of Complications of NIDDM--2. Analysis of the Health Benefits and Cost-Effectiveness of Treating NIDDM with the Goal of Normoglycemia, Eastman RC et al., Diabetes Care 20: 735-744, 1997. –The Prevention or Delay of Type 2 Diabetes, position statement from ADA and NIDDK, Diabetes Care 25: 742-749, 2002 –Effect of Improved Glycemic Control on Health Care Costs and Utilization, EH Wagner et al., JAMA 285: 182-189, 2001 –Health Economic Benefits and Quality of Life During Improved Glycemic Control in Patients with Type 2 Diabetes Mellitus: A Randomized, Controlled Double-Blind Trial, Testa MA and Simonson DC, JAMA, 280: 1490-6, 1998 One immediate benefit of the modeling process is often knowledge integration

15. Syndemics Prevention Network Diabetes System Modeling Project Simulating Policy Scenarios Homer J, Jones A, Seville D, Essien J, Milstein B, Murphy D. The CDC diabetes system modeling project: developing a new tool for chronic disease prevention and control. 22nd International Conference of the System Dynamics Society; Oxford, England; 2004. Historical Calibration Exploring Plausible Futures Diagnosed Diabetes % of Adults Obese % of Adults 0.0035 0.003 0.0025 0.002 0.0015 19801990200020102020203020402050 Time (Year) Diabetes-related death rate per year for adult population Status Quo Disease Mgmt Reduced Obesity Partial Disease Mgmt & Obesity Reduction

16. Syndemics Prevention Network Setting Realistic Expectations HP 2010 Diabetes Objectives Baseline HP 2010 Target Percent Change Reduce Diabetes–related Deaths Among Diagnosed (5-6) 8.8 per 1,000 7.8-11% Increase Diabetes Diagnosis (5-4) 68%80%+18% Reduce New Cases of Diabetes (5-2) 3.5 per 1,000 2.5-29% Reduce Prevalence of Diagnosed Diabetes (5-3) 40 per 1,000 25-38% U.S. Department of Health and Human Services. Healthy People 2010. Washington DC: Office of Disease Prevention and Health Promotion, U.S. Department of Health and Human Services; 2000. http://www.healthypeople.gov/Document/HTML/Volume1/05Diabetes.htm

17. Syndemics Prevention Network The Simple Physics of Diabetes It is impossible for any policy to reduce prevalence 38% by 2010! People with Undiagnosed Diabetes People with Diagnosed Diabetes Dying from Diabetes Complications Diagnosed Onset Initial Onset People with Normal Glycemic Levels As would stepped-up detection effort Reduced death would add further to prevalence With a diagnosed onset flow of 1.1 mill/yr And a death flow of 0.5 mill/yr (4%/yr rate) The targeted 29% reduction in diagnosed onset can only slow the growth in prevalence

18. Syndemics Prevention Network ReportedSimulated Status Quo Meet Detection Objective (5-4) Meet Onset Objective (5-2) HP 2010 Objective (5-3) HP 2000 Objective History and Futures for Diabetes Prevalence Reported Trends, HP Objectives, and Simulation Results A B C D E F G H I

19. Syndemics Prevention Network Projecting the Community-Wide Costs and Benefits of “Pursuing Perfection” in Whatcom County, WA Jack Homer & Gary Hirsch

20. Syndemics Prevention Network Whatcom County Pursuing Perfection (P2) Program A patient-centered team approach supported by: –Electronically shared clinical information: medical record, care plan, medication list –Idealized design of clinical office practice (IDCOP) for greater access and efficiency –Evidence-based guidelines –A clinical care specialist (RN) when needed –Cost-effective screening & preventive measures Initial disease focus: diabetes, heart failure Initial community participants: family practice group, cardiology group, geriatric practice, a community health center, the hospital, and three insurers Two years of funding by Robert Wood Johnson Foundation SEA MAR Clinica de la comunidad

21. Syndemics Prevention Network P2 Modeling Framework Program Adoption Healthcare Utilization Program Personnel* & Info System Costs Patient Disability Total Costs to Program, Payors, Providers, Patients, & Employers Pre-Program Quality of Care At-Risk Popn Demographics Disease Dynamics - Incidence - Progression - Complications - Deaths * Personnel include administrators and staff, process/OD consultants, and clinical care specialists.

22. Syndemics Prevention Network Deaths from Diabetes 2001-21: Four Scenarios Status Quo Full program* Full program + Medicare drug coverage Disease management only * Full program includes community-based screening; “positives” are referred to physician for follow-up testing and counseling. Disease-related deaths per year A similar pattern of results is seen for diabetes-related disability losses.

23. Syndemics Prevention Network Even during 2003-08 period of increased spending, cost per dollar of disability loss avoided averages only $0.37, and cost per life-year saved only $22,000. Impact of Full Program on Spending for Diabetes and Heart Failure 2001-21 Including Infrastructure Costs Excluding Infrastructure Costs (Health care spending only*) Constant (2001) dollars per year * Health care spending by insurers and patients pays for physicians, hospital, ancillary services, hospice, home care, skilled nursing facility, exercise rehab, drugs, and implanted devices.

24. Syndemics Prevention Network Financial Impacts 2003-08: Winners and Losers (in Year 2001 dollars)

25. Syndemics Prevention Network Commitment to a Comprehensive Strategy (based on model sensitivity testing) Disease management quickly starts improving health outcomes, but does not by itself reduce total spending Preventive measures produce increasing savings over time Solid program execution that delivers expected health benefits is necessary to achieve savings Clinical care specialists must be sufficient to meet referral demand Full drug coverage for the elderly would further improve health outcomes and program cost-effectiveness

26. Syndemics Prevention Network Toward a Dynamic View of HIV Prevention Trials

27. Syndemics Prevention Network Toward a Dynamic View of HIV Prevention Trials

28. Syndemics Prevention Network Toward a Dynamic View of HIV Prevention Trials

29. Syndemics Prevention Network Toward a Dynamic View of HIV Prevention Trials

30. Syndemics Prevention Network Toward a Dynamic View of HIV Prevention Trials

31. Syndemics Prevention Network Toward a Dynamic View of HIV Prevention Trials

32. Syndemics Prevention Network Toward a Dynamic View of HIV Prevention Trials

33. Syndemics Prevention Network Toward a Dynamic View of HIV Prevention Trials

34. Syndemics Prevention Network Widespread Interest in the Promise of a Systems Orientation See: http://www.cdc.gov/syndemics/ajph-systems.htm Submission Deadline: February 1, 2005