1. Syndemics Prevention Network Maine Center for Public Health Evaluation Forum Portland, ME Friday July 22, 2005 Innovations in Planning and Evaluating System Change Ventures Bobby Milstein Centers for Disease Control and Prevention bmilstein@cdc.gov Don Seville Sustainability Institute dseville@sustainer.org Navigating Health Futures

2. Syndemics Prevention Network General Plan for the Workshop Dilemmas and innovations in system change ventures A navigational view of public health work Navigating diabetes dynamics in an era of rising obesity: the power of “what if...” questions Working lunch: Developing diabetes policy scenarios and anticipating change Using simulation studies to learn in and about dynamic systems Transforming health evaluation Adjourn

3. Syndemics Prevention Network Starting Premises Public health work has changed significantly since its formalization in the 19th Century, and even today it is poised for further transformation It matters how we think about the trends, dilemmas, and innovations that we experience, and it matters whether our thinking and actions match We are not talking about theories to explain, but conceptual and methodological orientations: the frames that shape how we think, how we act, and how we value the work

4. Syndemics Prevention Network Innovations in Public Health Work Steps in Public Health Problem SolvingTrends and Emerging Priorities Define the problem Eliminate health disparities Preparedness Avoid activity limitation Promote life satisfaction Increase healthy days Determine the cause Social determinants of health Built environment Adverse childhood experiences Genetics Develop and test interventions Comprehensive community initiatives Ecological perspectives Inter-sector collaboration Health impact assessments Simulation experiments and game-based scenarios Implement programs and policies Policy interventions Community and systems change Adaptation to local context Increasing health care access Broad-based citizen organizing And scores more….

5. Syndemics Prevention Network How have you observed public health work changing? What types of dilemmas and innovations are driving those transformations? Where is the field headed? Leadership Panel

6. Syndemics Prevention Network Public health work is becoming more… Inter-connected ( ecological, multi-causal, dynamic, systems-oriented) Concerned more with leverage than control Public (broad-based, partner-oriented, citizen-led, inter-sector, democratic) Concerned with many interests and mutual-accountability Questioning (evaluative, reflective, critical, pragmatic) Concerned with creating and protecting values like health, dignity, security, satisfaction, justice, wealth, and freedom in both means and ends A Field in Transition Many other orientations rely on disconnected, singular, and unthinking approaches where means and ends have very different qualities (e.g., security by means of war)

7. Syndemics Prevention Network Locating categorical disease programs within a broader system of health protection Constructing credible knowledge without comparison/control groups Differentiating questions that focus on attribution versus contribution Balancing trade-offs between short- and long-term effects Avoiding the pitfalls of professonalism Harnessing the power of citizen-led actions Reconciling different standards and values for judgment Others… Serious Challenges for Planners and Evaluators

8. Syndemics Prevention Network “Public health is probably the most successful system of science and technology combined, as well as social policy, that has ever been devised…It is, I think, a paradigmatic model for how you do concerned, humane, directed science.” -- Richard Rhodes Rhodes R. Limiting human violence: an emerging scientific challenge. Sarewitz D, editor. Living With the Genie: Governing Science and Technology in the 21st Century; New York, NY: Center for Science, Policy, and Outcomes; 2002. Protecting Health Through Public Work Great Depression End of WW II Nonsmoker s Rights Movement Begins 1st Surgeon General’s Report 1st Smoking- Cancer Concern Federal Cigarette Tax Doubles Broadc ast Ad Ban Source: USDA; 1986 Surgeon General's Report Adult Per Capita Cigarette Consumption and Major Smoking-and-Health Events United States, 1900-1998

9. Syndemics Prevention Network A Navigational View of Public Health Work Thompson N. Reflections on voyaging and home. Polynesian Voyaging Society, 2001. Accessed July 18 at.

10. Syndemics Prevention Network A Navigational View of Public Health Work "How do you know," I asked, "that in twenty years those things that you consider special are still going to be here?" At first they all raised their hands but when they really digested the question every single one of them put their hands down. In the end, there was not a single hand up. No one could answer that question. It was the most uncomfortable moment of silence that I can remember…That was the defining moment for me. I recognized that I have to participate in answering that question otherwise I am not taking responsibility for the place I love and the people I love.” -- Nainoa Thompson Thompson N. Reflections on voyaging and home. Polynesian Voyaging Society, 2001. Accessed July 18 at.

11. Syndemics Prevention Network Navigating Health Futures in Maine Adolescent Pregnancy Mills DA, Maine Bureau of Health. Healthy Maine 2010: longer and healthier lives. Augusta, ME: Maine Department of Human Services 2002. Available at http://www.maine.gov/dhhs/boh/healthyme2k/hm2010a.htm

12. Syndemics Prevention Network Navigating Health Futures in Maine Mills DA, Maine Bureau of Health. Healthy Maine 2010: longer and healthier lives. Augusta, ME: Maine Department of Human Services 2002. Available at http://www.maine.gov/dhhs/boh/healthyme2k/hm2010a.htm Asthma

13. Syndemics Prevention Network Navigating Health Futures in Maine Mills DA, Maine Bureau of Health. Healthy Maine 2010: longer and healthier lives. Augusta, ME: Maine Department of Human Services 2002. Available at http://www.maine.gov/dhhs/boh/healthyme2k/hm2010a.htm Heart Disease

14. Syndemics Prevention Network Navigating Health Futures in Maine Mills DA, Maine Bureau of Health. Healthy Maine 2010: longer and healthier lives. Augusta, ME: Maine Department of Human Services 2002. Available at http://www.maine.gov/dhhs/boh/healthyme2k/hm2010a.htm Infant Mortality

15. Syndemics Prevention Network Scott JC. Seeing like a state: how certain schemes to improve the human condition have failed. New Haven ; London: Yale University Press, 1999. "Certain forms of knowledge and control require a narrowing of vision. The great advantage of such tunnel vision is that it brings into sharp focus certain limited aspects of an otherwise far more complex and unwieldy reality. This very simplification, in turn, makes the phenomenon at the center of the field of vision more legible and hence more susceptible to careful measurement and calculation….making possible a high degree of schematic knowledge, control, and manipulation." There is Great Power in Focusing on One Problem at a Time -- John Scott Great Depression End of WW II Nonsmoker s Rights Movement Begins 1st Surgeon General’s Report 1st Smoking- Cancer Concern Federal Cigarette Tax Doubles Broadc ast Ad Ban Source: USDA; 1986 Surgeon General's Report Adult Per Capita Cigarette Consumption and Major Smoking-and-Health Events United States, 1900-1998

16. Syndemics Prevention Network But “Solutions” Can Also Create New Problems Merton RK. The unanticipated consequences of purposive social action. American Sociological Review 1936;1936:894-904. Forrester JW. Counterintuitive behavior of social systems. Technology Review 1971;73(3):53-68.

17. Syndemics Prevention Network Side Effects of Specialization Confusion, inefficiency, organizational disarray Competition for shared resources Attention to “local” causes, near in time and space Neglected feedback (+ and -) Confounded evaluations Coercive power dynamics Priority on a single value, implicitly or explicitly devaluing others Limited mandate to address context (living conditions) or infrastructure (public strength) Disappointing track record for assuring the conditions for health, especially with regard to inequalities A C B D E ABCD E Issue Organizations Neighborhood

18. Syndemics Prevention Network Navigating Health Futures in Maine Centers for Disease Control and Prevention. Behavioral risk factor surveillance system, prevalence data. Atlanta, GA: U.S. Department of Health and Human Services, 2005. Available at http://apps.nccd.cdc.gov/HRQOL/TrendV.asp?State=21&Category=1&Measure=5 Adult Unhealthy Days, Maine 1993-2003

19. Syndemics Prevention Network The Ecological Perspective—Broad but Static Health Status Prevention of Disease, Injury, Disability Individual Factors Behavioral Settings Social Norms and Values  Home and Family  School  Community  Work Site  Healthcare  Genetics  Psychosocial  Other Personal Factors  Food and Beverage Industry  Agriculture  Education  Media  Government  Public Health Systems  Healthcare Industry  Business and Workers  Land Use and Transportation  Leisure and Recreation Sectors of Influence Protective BehaviorRisk Behavior

20. Syndemics Prevention Network Navigating Health Futures in Maine Questions Addressed by System Dynamics Modeling Centers for Disease Control and Prevention. Behavioral risk factor surveillance system, prevalence data. Atlanta, GA: U.S. Department of Health and Human Services, 2005. Available at http://apps.nccd.cdc.gov/HRQOL/TrendV.asp?State=21&Category=1&Measure=5 Adult Unhealthy Days, Maine 1993-2003 2020 2010 How? Where? Who? Why?

21. Syndemics Prevention Network Science, 256, (12 June 1992) pp. 1520-1521

22. Syndemics Prevention Network Acknowledging Plurality Efforts to Reduce Population Health Problems Problem, problem solver, response Efforts to Organize a System that Assures Healthful Conditions for All Dynamic interaction among multiple problems, problem solvers, and responses Bammer G. Integration and implementation sciences: building a new specialisation. Cambridge, MA: The Hauser Center for Nonprofit Organizations, Harvard University 2003. “You think you understand two because you understand one and one. But you must also understand ‘and’.” -- Sufi Saying

23. Syndemics Prevention Network "A bad solution is bad because it acts destructively upon the larger patterns in which it is contained...because it is formed in ignorance or disregard of them. A bad solution solves for a single purpose or goal, such as increased production. And it is typical of such solutions that they achieve stupendous increase in production at exorbitant biological and social costs…Good solutions recognize that they are part of a larger whole. They solve more than one problem and don't create new problems. A good solution should not enrich one person by the distress or impoverishment of another." -- Wendell Berry Berry W. Solving for pattern. In: The Gift of Good Land. San Francisco: North Point; 1981. p. 134-45. Solving for Pattern

24. Syndemics Prevention Network Possible What may happen? Plausible What could happen? Probable What will likely happen? Preferable What do we want to have happen? Bezold C, Hancock T. An overview of the health futures field. Geneva: WHO Health Futures Consultation; 1983 July 19-23. “Most organizations plan around what is most likely. In so doing they reinforce what is, even though they want something very different.” -- Ciement Bezold Seeing Beyond the Probable

25. Syndemics Prevention Network Navigating Diabetes Futures The Power of “What if…” Questions

26. Syndemics Prevention Network CDC Diabetes System Modeling Project Discovering Dynamics Through Action Labs Jones A, Homer J, Milstein B, Essien J, Murphy D, Sorensen S, Englegau M. Modeling the population dynamics of a chronic disease: the CDC's diabetes system model. American Journal of Public Health (in press).

27. Syndemics Prevention Network Transforming the Future of Diabetes… "Every new insight into Type 2 diabetes... makes clear that it can be avoided--and that the earlier you intervene the better. The real question is whether we as a society are up to the challenge... Comprehensive prevention programs aren't cheap, but the cost of doing nothing is far greater..." Gorman C. Why so many of us are getting diabetes: never have doctors known so much about how to prevent or control this disease, yet the epidemic keeps on raging. how you can protect yourself. Time 2003 December 8. Accessed at http://www.time.com/time/covers/1101031208/story.html. …in an Era of Epidemic Obesity

28. Syndemics Prevention Network Prevalence of Diagnosed Diabetes, US 0 10 20 30 40 19801990200020102020203020402050 Million people Historical Data: CDC DDT and NCCDPHP. (Change in measurement in 1996). Model Forecast: Honeycutt et al. 2003, "A Dynamic Markov model…" Historical Data Model Forecast Key Constants Incidence rates (%/yr) Death rates (%/yr) Diagnosed fractions (Based on year 2000 data, per demographic segment) Honeycutt A, Boyle J, Broglio K, Thompson T, Hoerger T, Geiss L, Narayan K. A dynamic markov model for forecasting diabetes prevalence in the United States through 2050. Health Care Management Science 2003;6:155-164. Other Models Exist, But Are Not Designed to Explore Intervention Scenarios

29. Syndemics Prevention Network Healthy People 2010 Diabetes Objectives: What Can We Accomplish? -11%7.8 8.8 per 1,000 Reduce Diabetes–related Deaths Among Diagnosed (5-6) -38%25 40 per 1,000 Reduce Prevalence of Diagnosed Diabetes (5-3) -29%2.5 3.5 per 1,000 Reduce New Cases of Diabetes (5-2) Increase Diabetes Diagnosis (5-4) +18%80%68% Percent Change HP 2010 Target Baseline 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

30. Syndemics Prevention Network Simulated Status Quo Meet Detection Objective (5-4) Meet Onset Objective (5-2) HP 2010 Objective (5-3) HP 2000 Objective Setting Realistic Expectations History, HP Objectives, and Simulated Futures Reported A B C D E F G H I

31. Syndemics Prevention Network Connecting the Objectives Population Flows and Dynamic Accounting 101 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 without Diabetes 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

32. Syndemics Prevention Network Simulations for Learning in Dynamic Systems Plausible Futures (Policy Experiments)Dynamic Hypothesis (Causal Structure) Morecroft JDW, Sterman J. Modeling for learning organizations. Portland, OR: Productivity Press, 2000. Sterman JD. Business dynamics: systems thinking and modeling for a complex world. Boston, MA: Irwin McGraw-Hill, 2000. Multi-stakeholder Dialogue

33. Syndemics Prevention Network Health Care Capacity Provider supply Provider understanding, competence Provider location System integration Cost of care Insurance coverage Population Flows Discussions Pointed to Many Interacting Factors Personal Capacity Understanding Motivation Social support Literacy Physio-cognitive function Life stages Metabolic Stressors Nutrition Physical activity Stress Health Care Utilization Ability to use care (match of patients and providers, language, culture) Openness to/fear of screening Self-management, monitoring Civic Participation Social cohesion Responsibility for others Forces Outside the Community Macroeconomy, employment Food supply Advertising, media National health care Racism Transportation policies Voluntary health orgs Professional assns University programs National coalitions Local Living Conditions Availability of good/bad food Availability of phys activity Comm norms, culture (e.g., responses to racism, acculturation) Safety Income Transportation Housing Education

34. Syndemics Prevention Network Diabetes System Modeling Project Where is the Leverage for Health Protection? Jones A, Homer J, Milstein B, Essien J, Murphy D, Sorensen S, Englegau M. Modeling the population dynamics of a chronic disease: the CDC's diabetes system model. American Journal of Public Health (in press). 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

35. 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 People with Undiagnosed, Complicated Diabetes Diagnosing Complicated Diabetes People with Normal Glycemic Levels Diabetes Detection Obese Fraction of the Population Risk for PreDiabetes & Diabetes Caloric Intake Physical Activity PreDiabetes Control Diabetes Control PreDiabetes Detection Medication Affordability Ability to Self Monitor Adoption of Healthy Lifestyle Clinical Management of PreDiabetes 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

36. Syndemics Prevention Network Developing Diabetes Policy Scenarios and Anticipating Change What strategies do you see unfolding in Maine over the next five years to address the rise of diabetes? How will those strategies affect the burden of diabetes?

37. Syndemics Prevention Network The Diabetes Simulation Model Was Developed Using The Best Possible Available Data Information SourcesData U.S. Census Adult population and death rates Health insurance coverage National Health Interview Survey Diabetes prevalence Diabetes detection National Health and Nutrition Examination Survey Prediabetes prevalence Weight, height, and body fat Caloric intake Behavioral Risk Factor Surveillance System Glucose self-monitoring Eye and foot exams Participation in health education Use of medications Professional Literature Physical activity trends Effects of control and aging on onset, progression, death, and costs Expenditures

38. Syndemics Prevention Network Diabetes System Modeling Project Confirming the Model’s Fit to History Jones A, Homer J, Milstein B, Essien J, Murphy D, Sorensen S, Englegau M. Modeling the population dynamics of a chronic disease: the CDC's diabetes system model. American Journal of Public Health (in press). Diagnosed Diabetes % of AdultsObese % of Adults 0% 10% 20% 30% 40% 1980198519901995200020052010 Obese % of adults Data (NHANES) Simulated 0% 2% 4% 6% 8% 1980198519901995200020052010 Diagnosed diabetes % of adults Data (NHIS) Simulated

39. Syndemics Prevention Network Explaining the Past Growth in the Number of People with Diabetes More people with a primary risk factor…. Leads to rising total prevalence After a delay (plus aging and demographics, etc…) Obese Fraction of Adult Population 0.4 0.3 0.2 0.1 0 198019851990199520002005 Time (Year) People with Diabetes per Thousand Adults 100 80 60 40 20 0 198019851990199520002005 Time (Year) Model Output

40. Syndemics Prevention Network Controlled Fraction of Diagnosed Population 0.5 0.4 0.3 0.2 0.1 0 198019851990199520002005 Time (Year) Explaining the Past Reducing the Burden for People with Diabetes Model Output From around 5% To above 40% Model Output We have been finding them… And helping them stay under control Diagnosed Fraction of Diabetes Population 0.8 0.7 0.6 0.5 198019851990199520002005 Time (Year) (although there are disparities)

41. Syndemics Prevention Network Explaining the Past Deaths Due to Diabetes Have Fallen Combine to mean fewer U.S. adults dying 1980-2004 Complications Deaths per Thousand w Diabetes 40 30 20 10 0 198019851990199520002005 Time (Year) People with Diabetes per Thousand Adults 100 90 80 70 60 50 198019851990199520002005 Time (Year) More people with diabetes Deaths from Comps of Diabetes Per Thousand Adults 2.5 2 1.5 1 0.5 0 198019851990199520002005 Time (Year) Model Output Among people with diabetes, fewer dying every year

42. Syndemics Prevention Network From a 30,000 Foot View and Population Perspective, We Have Seen Two Forces Fighting to Change the Burden of Diabetes Stunning Progress in Reducing the Burden for the Average Person with Diabetes Huge Growth in Number of People with Diabetes Overall, Total Burden per Citizen Held at Bay

43. Syndemics Prevention Network Anticipating the Future Obese Fraction of Adult Population 0.6 0.45 0.3 0.15 0 19801995201020252040 Time (Year) Even if obesity has topped out … People with Diabetes per Thousand Adults 130 110 90 70 50 19801990200020102020203020402050 Time (Year) Diabetes prevalence continues to increase for decades. Model Output After a delay

44. Syndemics Prevention Network People with Diabetes per Thousand Adults 130 110 90 70 50 19801990200020102020203020402050 Time (Year) Complications Deaths per Thousand w Diabetes 40 30 20 10 0 19801990200020102020203020402050 Time (Year) Deaths from Complications of Diabetes Per Thousand Adults 2.5 1.25 19801990200020102020203020402050 Time (Year) Diabetes-related deaths would naturally rise. Anticipating the Future Deaths Under ‘Status Quo’ Assumptions* And assuming no further improvement in disease management... With diabetes prevalence continuing to increase... * Assuming no change after 2004 in the 9 key health behaviors

45. Syndemics Prevention Network Navigating the Future of Diabetes What Strategies Would You Like To Test? 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 People with Undiagnosed, Complicated Diabetes Diagnosing Complicated Diabetes People with Normal Glycemic Levels Diabetes Detection Obese Fraction of the Population Risk for PreDiabetes & Diabetes Caloric Intake Physical Activity PreDiabetes Control Diabetes Control PreDiabetes Detection Medication Affordability Ability to Self Monitor Adoption of Healthy Lifestyle Clinical Management of PreDiabetes Clinical Management of Diagnosed Diabetes 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

46. Syndemics Prevention Network Navigating the Future of Diabetes What strategies would you like to test in the simulated environment to better address diabetes?

47. Syndemics Prevention Network Scenario Effect of Public Health Effort on… Clinical Management of Diagnosed Diabetes (% under control) Caloric Intake (Kcal/day) Base Run (no changes after 2000) Enhanced Disease Control (Downstream) Enhanced Obesity Prevention (Upstream) Combined Disease Control and Obesity Prevention (Up and Down) Developing a Scenario-based Research Design

48. Syndemics Prevention Network Diabetes System Modeling Project Where Flow Drivers are Involved in Each Strategy?

49. Syndemics Prevention Network Scenario Effect of Public Health Effort on… Clinical Management of Diagnosed Diabetes (% under control) Caloric Intake (Kcal/day) Base Run (no changes after 2000) 66%2465 Enhanced Disease Control (Downstream) Enhanced Obesity Prevention (Upstream) Combined Disease Control and Obesity Prevention (Up and Down) Developing a Scenario-based Research Design

50. Syndemics Prevention Network Deaths per Population 0.0035 0.003 0.0025 0.002 0.0015 19801990200020102020203020402050 Time (Year) Downstream-Only Intervention Blue: Base run Base

51. Syndemics Prevention Network Scenario Effect of Public Health Effort on… Clinical Management of Diagnosed Diabetes (% under control) Caloric Intake (Kcal/day) Base Run (no changes after 2000) 66%2465 Enhanced Disease Control (Downstream) Enhanced Obesity Prevention (Upstream) Combined Disease Control and Obesity Prevention (Up and Down) Developing a Scenario-based Research Design

52. Syndemics Prevention Network Scenario Effect of Public Health Effort on… Clinical Management of Diagnosed Diabetes (% under control) Caloric Intake (Kcal/day) Base Run (no changes after 2000) 66%2465 Enhanced Disease Control (Downstream) +24% (90% under control) No change Enhanced Obesity Prevention (Upstream) Combined Disease Control and Obesity Prevention (Up and Down) Developing a Scenario-based Research Design

53. Syndemics Prevention Network Deaths per Population 0.0035 0.003 0.0025 0.002 0.0015 19801990200020102020203020402050 Time (Year) Downstream-Only Intervention Blue: Base run; Red: Clinical mgmt of diagnosed up from 66% to 90% Base Downstream Disease control acts quickly but does not slow the growth in deaths.

54. Syndemics Prevention Network Scenario Effect of Public Health Effort on… Clinical Management of Diagnosed Diabetes (% under control) Caloric Intake (Kcal/day) Base Run (no changes after 2000) 66%2465 Enhanced Disease Control (Downstream) +24% (90% under control) No change Enhanced Obesity Prevention (Upstream) Combined Disease Control and Obesity Prevention (Up and Down) Developing a Scenario-based Research Design

55. Syndemics Prevention Network Scenario Effect of Public Health Effort on… Clinical Management of Diagnosed Diabetes (% under control) Caloric Intake (Kcal/day) Base Run (no changes after 2000) 66%2465 Enhanced Disease Control (Downstream) +24% (90% under control) No change Enhanced Obesity Prevention (Upstream) No Change -4% (99 fewer Kcal/day) Combined Disease Control and Obesity Prevention (Up and Down) Developing a Scenario-based Research Design

56. Syndemics Prevention Network Deaths per Population 0.0035 0.003 0.0025 0.002 0.0015 19801990200020102020203020402050 Time (Year) Upstream-Only Intervention Blue: Base run; Red: Clinical mgmt up from 66% to 90%; Green: Caloric intake down 4% (99 Kcal/day) Downstream Upstream Base Obesity prevention slows the growth but takes a long time to do so.

57. Syndemics Prevention Network Scenario Effect of Public Health Effort on… Clinical Management of Diagnosed Diabetes (% under control) Caloric Intake (Kcal/day) Base Run (no changes after 2000) 66%2465 Enhanced Disease Control (Downstream) +24% (90% under control) No change Enhanced Obesity Prevention (Upstream) No Change -4% (99 fewer Kcal/day) Combined Disease Control and Obesity Prevention (Up and Down) Developing a Scenario-based Research Design

58. Syndemics Prevention Network Scenario Effect of Public Health Effort on… Clinical Management of Diagnosed Diabetes (% under control) Caloric Intake (Kcal/day) Base Run (no changes after 2000) 66%2465 Enhanced Disease Control (Downstream) +24% (90% under control) No change Enhanced Obesity Prevention (Upstream) No Change -4% (99 fewer Kcal/day) Combined Disease Control and Obesity Prevention (Up and Down) +14% (80% under control) -2.5% (62 fewer Kcal/day) Developing a Scenario-based Research Design

59. Syndemics Prevention Network Deaths per Population 0.0035 0.003 0.0025 0.002 0.0015 19801990200020102020203020402050 Time (Year) Mixed Intervention 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) Base Downstream Upstream Mixed Striking an acceptable balance.

60. Syndemics Prevention Network The Modeling Process is Having an Impact Budget for primary prevention was doubled –from meager to modest HP2010 prevalence goal has been modified –from a large reduction to no change (but still not an increase) Research, program, and policy staff are working more closely –but truly cross-functional teams still forming State health departments and their partners are now engaged –initial engagement in VT, with two additional states being considered

61. Syndemics Prevention Network Transforming Health Evaluation

62. Syndemics Prevention Network “Simulation is a third way of doing science. Like deduction, it starts with a set of explicit assumptions. But unlike deduction, it does not prove theorems. Instead, a simulation generates data that can be analyzed inductively. Unlike typical induction, however, the simulated data comes from a rigorously specified set of rules rather than direct measurement of the real world. While induction can be used to find patterns in data, and deduction can be used to find consequences of assumptions, simulation modeling can be used as an aid to intuition.” -- Robert Axelrod Axelrod R. Advancing the art of simulation in the social sciences. In: Conte R, Hegselmann R, Terna P, editors. Simulating Social Phenomena. New York, NY: Springer; 1997. p. 21-40.. Sterman JD. Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston, MA: Irwin McGraw-Hill, 2000. Simulation Experiments Open a Third Branch of Science “The complexity of our mental models vastly exceeds our ability to understand their implications without simulation." -- John Sterman How? Where? Prevalence of Obese Adults, United States Why? Data Source: NHANES 2020 2010 Who? What?

63. Syndemics Prevention Network Learning In and About Dynamic Systems Benefits of Simulation/Game-based Learning Formal means of evaluating options Experimental control of conditions Compressed time Complete, undistorted results Actions can be stopped or reversed Visceral engagement and learning Tests for extreme conditions Early warning of unintended effects Opportunity to assemble stronger support Complexity Hinders Generation of evidence (by eroding the conditions for experimentation) Learning from evidence (by demanding new heuristics for interpretation) Acting upon evidence (by including the behaviors of other powerful actors) Sterman JD. Learning from evidence in a complex world. American Journal of Public Health (in press). Sterman JD. Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston, MA: Irwin McGraw-Hill, 2000. “In [dynamically complex] circumstances simulation becomes the only reliable way to test a hypothesis and evaluate the likely effects of policies." -- John Sterman

64. Syndemics Prevention Network Patterns Events Analysis Process for Developing Policy Adapted from: Successful Systems, Inc. Issue Identification Variable & Behavior Analysis Time Issue Identification Variable & Behavior Analysis Causal Mapping Understanding Strategy & Policy Implications Implementing Action Plan Structure Causal Mapping Simulation Modeling

65. 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

66. 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

67. Syndemics Prevention Network Transforming Essential Ways of Thinking Conventional ThinkingSystems Thinking Static Thinking: Focusing on particular events.Dynamic Thinking: Framing a problem in terms of a pattern of behavior over time. System-as-Effect Thinking: Focus on individuals as the sources of behavior. Hold individuals responsible or blame outside forces. System-as-Cause Thinking: Seeing the structures and pressures that drive behavior. Examine the conditions in which decisions are made, as well as their consequences for oneself and others. Tree-by-Tree Thinking: Focusing on the details in order to “know.” Forest Thinking: Seeing beyond the details to the context of relationships in which they are embedded. Factors Thinking: Listing factors that influence, or are correlated with, a behavior. To forecast milk production, consider economic elasticities. Operational Thinking: Understanding how a behavior is actually generated. To forecast milk production, you must consider cows. Straight-Line Thinking: Viewing causality as running one way, treating causes as independent and instantaneous. Root-Cause thinking. Closed-Loop Thinking: Viewing causality as an ongoing process, not a one-time event, with effects feeding back to influence causes, and causes affecting each other, sometimes after long delays. Measurement Thinking: Focusing on the things we can measure; seeking precision. Quantitative Thinking: Knowing how to quantify, even though you cannot always measure. Proving-Truth Thinking: Seeking to prove our models true by validating them with historical data. Scientific Thinking: Knowing how to define testable hypotheses (everyday, not just for research). Karash R. The essentials of systems thinking and how they pertain to healthcare and colorectal cancer screening. Dialogue for Action in Colorectal Cancer; Baltimore, MD; March 23, 2005.. Richmond B. Systems thinking: critical thinking skills for the 1990s and beyond. System Dynamics Review 1993;9(2):113-134. Richmond B. The "thinking" in systems thinking: seven essential skills. Waltham, MA: Pegasus Communications, 2000.

68. Syndemics Prevention Network “The macroscope filters details and amplifies that which links things together. It is not used to make things larger or smaller but to observe what is at once too great, too slow, and too complex for our eyes.” Rosnay Jd. The macroscope: a book on the systems approach. Principia Cybernetica, 1997. <http://pespmc1.vub.ac.be/MACRBOOK.html -- Joèel de Rosnay Looking Through the Macroscope

69. Syndemics Prevention Network Are We Posing Questions About Attribution or Contribution? “…if a program’s activities are aligned with those of other programs operating in the same setting, certain effects (e.g., the creation of new laws or policies) cannot be attributed solely to one program or another. In such situations, the goal for evaluation is to gather credible evidence that describes each program’s contribution in the combined change effort. Establishing accountability for program results is predicated on an ability to conduct evaluations that assess both of these kinds of effects.” p.11-12 Calls into question the conditions in which one focuses on a “program” as the unit of analysis Milstein B, Wetterall S, CDC Evaluation Working Group. Framework for program evaluation in public health. MMWR Recommendations and Reports 1999;48(RR-11):1-40. Available at.

70. Syndemics Prevention Network Questioning the Character of Public Health Work PUBLIC HEALTH WORK Innovative Health Ventures SYSTEMS THINKING & MODELING (understanding change) What causes population health problems? How are efforts to protect the public’s health organized? How and when do health systems change (or resist change)? PUBLIC HEALTH (setting direction) What are health leaders trying to accomplish? SOCIAL NAVIGATION (governing movement) Directing Change Charting Progress Who does the work? By what means? According to whose values? How are conditions changing? In which directions?

71. Syndemics Prevention Network Changing (and Accumulating) Ideas About Causation What accounts for poor population health? God’s will Humors, miasma, ether (e.g., epidemic constitution) Poor living conditions, immorality (e.g., sanitation) Single disease, single cause (e.g., germ theory) Single disease, multiple causes (e.g., heart disease) Single cause, multiple diseases (e.g., tobacco) Multiple causes, multiple diseases (but no feedback dynamics) (e.g., social epidemiology) Dynamic feedback among afflictions, living conditions, and public strength (e.g., syndemics) 1880 1950 1960 1980 2000 1840

72. Syndemics Prevention Network Syndemic Orientation Expanding Prevention Science “Public health imagination involves using science to expand the boundaries of what is possible.” -- Michael Resnick Epidemic Orientation People in Places Ecological Thinking Governing Dynamics Causal Mapping Plausible Futures Dynamic Modeling Navigational Freedoms Democratic Public Work

73. Syndemics Prevention Network For Additional Information http://www.cdc.gov/syndemics