Policy Evaluation Exploring the Dynamic and Democratic Dimensions

Policy Evaluation Exploring the Dynamic and Democratic Dimensions of Health Protection Policies Bobby Milstein Syndemics Prevention Network Centers for Disease Control and Prevention bmilstein@cdc. gov http: //www. cdc. gov/syndemics Syndemics Prevention Network Edinburgh Evaluation Summer School Edinburgh, Scotland June 6, 2007

Appreciating the Unique Character of Evaluative Inquiry “It is easier to find facts than it is to face them. ” Research Systematic Methods Questions of Fact (descriptions, associations, effects) Evaluation Questions of Values (merit, worth, significance) Centers for Disease Control and Prevention. What procedures are available for planning and evaluating initiatives to prevent syndemics? Syndemics Prevention Network, 2001. Available at . Syndemics Prevention Network

Picture a Neighborhood Where… • • People are either afflicted by or at risk for numerous mutually reinforcing health problems • Citizen leaders are making an effort to alleviate afflictions and improve living conditions, but their power is limited • James Nachtwey in Sachs J. How to end poverty. Time Magazine 2005 March 14. Conditions are not supportive of healthy living More could be done through better local organizing and with effective assistance from outside allies (e. g. , philanthropy, government) How does public health policy typically proceed in such circumstances? Which forms of policy planning and evaluation are most relevant and promising? Syndemics Prevention Network

Policy Planning & Evaluation Engages Questions of Social Navigation Prevalence of Diagnosed Diabetes, US 40 ode Historical Data ? e er h Million people 30 ore F kov Mar M ting l cas W 20 What? Ho 10 0 1980 Why? 1990 2000 Trend is not destiny! 2010 Wh w? Markov Model Constants • Incidence rates (%/yr) • Death rates (%/yr) • Diagnosed fractions (Based on year 2000 data, per demographic segment) o? 2020 2030 2040 2050 Honeycutt A, Boyle J, Broglio K, Thompson T, Hoerger T, Geiss L, Narayan K. A dynamic markov model forecasting diabetes prevalence in the United States through 2050. Health Care Management Science 2003; 6: 155 -164. Syndemics Prevention Network Jones AP, Homer JB, Murphy DL, Essien JDK, Milstein B, Seville DA. Understanding diabetes population dynamics through simulation modeling and experimentation. American Journal of Public Health 2006; 96(3): 488 -494.

A Field in Transition Modern public health policy—and evaluation—are 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, reflexive, critical, practical) Concerned with creating and protecting values like health, equity, dignity, security, satisfaction, justice, wealth, and freedom in both means and ends Syndemics Prevention Network

Framework for Program Evaluation “Both a synthesis of existing evaluation practices and a standard for further improvement. ” Left Unexamined… • • Democratic aspects of public health work (e. g. , alignment among multiple actors, including those who are not professionals and who may be pursuing other goals) • Prevention Network Dynamic aspects of program effectiveness (e. g. , better-before-worse patterns of change) • Syndemics Singular “program” as the unit of inquiry (N=1 organizational depth) Evaluative aspects of planning 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 .

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 Syndemics Prevention Network

Serious Challenges for Planners and Evaluators • • Differentiating questions that focus on attribution vs. contribution • Balancing trade-offs between short- and long-term effects • Avoiding the pitfalls of professonalism (e. g. , over-specialization, arrogance, reinforcement of the status quo) • Harnessing the power of intersectoral and citizen-led public work • Prevention Network Constructing credible knowledge without comparison/control groups • Syndemics Locating categorical disease or risk prevention programs within a broader system of health protection Defining standards and values for judgment • Others…

Topics for Today • Health Protection Policy in a Dynamic and Democratic World – Concepts, keywords, structures • Looking Backward, Looking Forward – Retrospectively evaluating past policy – Prospectively crafting/evaluating future policy • Highlighting One Promising Methodology – System Dynamics simulation modeling • Syndemics Prevention Network Questions and Discussion Throughout

Defining Keywords Policy is… • The plans, programs, principles, or more broadly the course of action of some actor(s), which may include a degree of deliberate inaction as well • Explicit or implicit rules for deciding how to respond to circumstances and pressures • Priorities guiding resource allocation Policy evaluation is… • The systematic process of determining—and improving —the merit, worth, or significance of decisions about what to do, or not to do, in a given domain • The articulation and assessment of alternative possible futures, each corresponding to a different policy Adapted from: Milio N. Glossary: healthy public policy. Journal of Epidemiology and Community Health 2001; 55(9): 622 -623. Forrester JW. Policies and decisions. In: Industrial Dynamics. Cambridge, MA: MIT Press; 1961. p. 93 -108. Syndemics Prevention Network Bennett T, Grossberg L, Morris M. New keywords: a revised vocabulary of culture and society. Malden, MA: Blackwell Pub. , 2005. Scriven M. Evaluation thesaurus. 4 th ed Newbury Park, CA: Sage Publications, 1991.

Policy is Continual, Iterative Process of particular our general approach toward a problem or area of concern… Policy Planning & Evaluating ASSESSMENT Many Methodologies… Communications Auditing Law Enforcement Leadership & Organizing Power mapping Non-violent action Social Navigation ASSURANCE Surveys Needs Assessment Asset Mapping Frame analysis Concept mapping Network analysis Time-trend analysis Assuring Healthful Conditions for All Many Methodologies… Pilot and Demonstration Theories of Change Health impact assessment Simulation modeling Futuring or Storytelling POLICY DEVELOPMENT Institute of Medicine. The future of public health. Washington, DC: National Academy Press, 1988. Syndemics Prevention Network Institute of Medicine. The future of the public's health in the 21 th century. Washington, DC: National Academy Press, 2002.

Defining Keywords Policy vs. Decisions • Policy usually involves a series of specific decisions, programs, actions • But the distinction is blurry – Policy makers never start from a blank sheet of possibilities – Ad hoc decisions may together add up to forceful implicit policy Artist: Boyce Watt “Policy is the selection of non-contradictory means to achieve non-contradictory ends over the medium to long term. Policy is the thread of conviction that keeps a government from becoming the prisoner of events. ” -- Michael Ignatieff Walt G. Health policy: an introduction to process and power. Atlantic Highlands, NJ: Zed Books, 1994. Syndemics Prevention Network Ignatieff M. The grey empitness inside John Major. The Observer 1992 November 15; 25.

Events Pattern Structure Water Temperature Water Level R Melting Syndemics Prevention Network Economic Activity & Emissions Flood Damage

Tools for Policy Planning & Evaluation Events Increasing: Time Series Models Describe trends • Depth of causal theory Patterns • Robustness for longerterm projection • Value for developing policy insights • Degrees of uncertainty Structure Syndemics Prevention Network Multivariate Stat Models Identify historical trend drivers and correlates Dynamic Simulation Models Anticipate new trends, learn about policy consequences, and set justifiable goals

Consider the Track Record… • Low tar and low nicotine cigarettes Lead to greater carcinogen intake • Fad diets Produce diet failure and weight gain • Antibiotic & pesticide use Stimulate resistant strains • Road building to ease congestion Attracts development, increases traffic, delays, and pollution • Air-conditioning use Raises neighborhood heat • Forest fire suppression Builds deadwood fueling larger, hotter, more dangerous fires • War on drugs Raises price and attracts supply • Suppressing dissent Inspires radicalization and extremism Syndemics Prevention Network Sterman JD. Learning from evidence in a complex world. American Journal of Public Health 2006; 96(3): 505 -514. Forrester JW. Counterintuitive behavior of social systems. Technology Review 1971; 73(3): 53 -68.

Defining Keywords Policy Resistance is… “The tendency for interventions to be delayed, diluted, or defeated by the response of the system to the intervention itself. ” -- Meadows, Richardson & Bruckmann Meadows DH, Richardson J, Bruckmann G. Groping in the Dark: The First Decade of Global Modelling. Wiley: New York, 1985. Syndemics Prevention Network

Seeking High-Leverage Policies “Give me a firm place to stand I will move the earth. ” -- Archimedes Wall painting in the Stanzino delle Matematiche in the Galleria degli Uffizi (Florence, Italy). Painted by Giulio Parigi in the years 1599 -1600. Syndemics Prevention Network Meadows DH. Leverage points: places to intervene in a system. Sustainability Institute, 1999. Available at .

Public Health Work Literally Involves Redirecting the Course of Change Actual and Expected Death Rates for Coronary Heart Disease, 1950– 1998 700 Rate if trend continued Age-adjusted Death Rate per 100, 000 Population 600 500 Peak Rate 400 300 Overall Decline is Linked to… • Reduced smoking 200 100 684, 000 fewer deaths in 1998 alone • Changes in diet Actual Rate • Better diagnosis and treatment • More heath services utilization 50 1955 1960 1965 1970 1975 1980 1985 1990 1995 Year Marks JS. The burden of chronic disease and the future of public health. CDC Information Sharing Meeting. Atlanta, GA: National Center for Chronic Disease Prevention and Health Promotion; 2003. Syndemics Prevention Network Centers for Disease Control and Prevention. Achievements in public health, 1900 -1999: decline in deaths from heart disease and stroke -- United States, 1900 -1999. MMWR 1999; 48(30): 649 -656. Available at

One Observer's View… “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 Syndemics Prevention Network Rhodes R. Limiting human violence: an emerging scientific challenge. Sarewitz D, editor. Living With the Genie: Governing Science and Technology in the 21 st Century; New York, NY: Center for Science, Policy, and Outcomes; 2002.

Immense Challenges Ahead World Population Growth United Nations Department of Economic and Social Affairs. Population Division. The world at six billion. Washington D C: Population Division Dept. of Economic and Social Affairs United Nations Secretariat, 1999. Syndemics Prevention Network CNN. Sarajevo baby to be honored as 6 billionth person on Earth. CNN, 1999. Accessed July 5, 2003 at .

Resource Depletion & Related Conflict Syndemics Prevention Network

A Glimpse Into 2020 Murray CJL, Lopez AD. The global burden of disease: summary. Cambridge, MA: Harvard University Press, 1996. Syndemics Prevention Network

A Glimpse Into 2020 Off the List On the List Measles War Malaria HIV Falls Violence Anemia Self-inflicted injury Malnutrition Cancer of the trache bronchus, and lung Syndemics Prevention Network Murray CJL, Lopez AD. The global burden of disease: summary. Cambridge, MA: Harvard University Press, 1996.

Broad Dynamics of the Health Protection Enterprise Prevalence of Vulnerability, Risk, or Disease 100% Values for Health & Equity Size of the Safer, Healthier Population B Taking the Toll R Potential Threats Drivers of Growth B Prevalence of Vulnerability, Risk, or Disease Responses to Growth Health Protection Efforts B - Obstacles Resources & Resistance R Reinforcers Broader Benefits & Supporters 0% Time Syndemics Prevention Network The concepts and methods of policy evaluation must engage the basic features of this dynamic and democratic system

A Complementary Science of Relationships True innovation occurs when things are put together for the first time that had been separate. – Arthur Koestler • 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 Institute of Medicine. The future of public health. Washington, DC: National Academy Press, 1988. Institute of Medicine. The future of the public's health in the 21 th century. Washington, DC: National Academy Press, 2002. Syndemics Prevention Network Bammer G. Integration and implementation sciences: building a new specialisation. Cambridge, MA: The Hauser Center for Nonprofit Organizations, Harvard University 2003.

John Snow Heroic Success or Cautionary Tale? Broad Street, One Year Later “No improvements at all had been made. . . open cesspools are still to be seen. . . we have all the materials for a fresh epidemic. . . the water-butts were in deep cellars, close to the undrained cesspool. . . The overcrowding appears to increase. " Summers J. Soho: a history of London's most colourful neighborhood. Bloomsbury, London, 1989. p. 117. Syndemics Prevention Network

Another Prototypical Example Attempts to Reform the U. S. Health Care Delivery System Number of Uninsured Americans, 1976 -2003 “At least six times since the Depression, the United States has tried and failed to enact a national health insurance program. ” Himmelstein, Woolhandler, Carrasquillo – Tabulation from CPS and NHIS Syndemics Lee P, Paxman D. Reinventing public health. Annual Reviews of Public Health 1997; 18: 1 -35. Prevention Network – Lee & Paxman

Crafting Health Policies that will Succeed in a Large, Dynamic System Efforts to reform health care policy have been ineffective because of • Piecemeal approaches • Failure to address root problems • Inattention to the larger political and economic system “Most of the analytic strategies popular among academics, politicians, and policy makers fail to observe the system as a whole…to discuss processes of mutual change that are occurring, or to analyze how innovations fit into larger nonequilibrium dynamics that are developing. ” -- Max Heirich Syndemics Prevention Network Heirich M. Rethinking health care: innovation and change in America. Boulder, CO: Westview Press, 1999.

Understanding Dynamic Complexity Forrester JW. Counterintuitive behavior of social systems. Technology Review 1971; 73(3): 53 -68. Meadows DH. Leverage points: places to intervene in a system. Sustainability Institute, 1999. Available at . Syndemics Prevention Network Richardson GP. Feedback thought in social science and systems theory. Philadelphia, PA: University of Pennsylvania Press, 1991. Sterman JD. Business dynamics: systems thinking and modeling for a complex world. Boston, MA: Irwin Mc. Graw-Hill, 2000.

Changing Views of Population Health What Accounts for Population Health? • God’s will • Humors, miasma, ether • Poor living conditions, immorality (e. g. , ? ) 1840 • Single disease, single cause (e. g. , ? ) 1880 • Single disease, multiple causes (e. g. , ? ) 1950 • Single cause, multiple diseases (e. g. , ? ) • Multiple causes, multiple diseases (but no feedback dynamics) (e. g. , ? ) • Dynamic feedback among afflictions, living conditions, and public strength (e. g. , ? ) 1960 1980 2000 Milstein B. Hygeia's constellation: navigating health futures in a dynamic and democratic world [Doctoral Dissertation]. Cincinnati, OH: Union Institute & University; 2006. Syndemics Prevention Network Richardson GP. Feedback thought in social science and systems theory. Philadelphia, PA: University of Pennsylvania Press, 1991.

Placing Health in a Wider Set of Relationships Health “Health Policy” Power to Act Living Conditions “Social Policy” This orientation explicitly includes within it our power to craft policies, along with an understanding of the changing pressures, constraints, and consequences that shape it. Syndemics Prevention Network

Two Orientations Retrospective • • • What have been the observed consequences of prior decisions? For whom? When? Why? At what cost? Recommendations to continue or change strategy Prospective • • Syndemics Prevention Network What is the range of plausible consequences of policy options? For whom? When? Why? At what cost? Which alternative futures are most highly valued, or feared? What must be done to move in the desired direction?

Prospective Policy Evaluation Explicitly recognizes the evaluative aspects of planning: • • Developing options • Prevention Network Setting priorities • Syndemics Defining problems Selecting strategies Risley J. Public policy evaluation. Kalamazoo, MI: The Evaluation Center, Western Michigan University; February 26, 2004. .

When Faced with the Vast Scope of Public Health Threats… Narrow the Focus and Specialize • • Syndemics Implement policy • Evaluate policy • Prevention Network Formulate policy • Breeding Ground for Disease (Karen Kasmauski, National Geographic, 2001). Identify problem Repeat steps 1 -4, as necessary!

Diseases of Disarray Hardening of the categories Tension headache between treatment and prevention Hypocommitment to training Cultural incompetence Political phobia Input obsession Wiesner PJ. Four disease of disarray in public health. Annals of Epidemiology. 1993; 3(2): 196 -8. Syndemics Prevention Network Chambers LW. The new public health: do local public health agencies need a booster (or organizational "fix") to combat the diseases of disarray? Canadian Journal of Public Health 1992; 83(5): 326 -8.

Dangers of Getting Too Specific Conventional problem solving proliferates problems Opens a self-reinforcing niche for professional problem solvers Obscures patterns that transcend any specific problem (e. g. , nonviolence is entirely neglected) Krug EG, World Health Organization. World report on violence and health. Geneva: World Health Organization, 2002. Syndemics Prevention Network

Examples of Nonviolent Action Dismantling dictatorships Blocking coups d’état Defending against foreign invasions and occupations Providing alternatives to violence in extreme ethnic conflicts “A phenomenon that cuts across ethnic, cultural, religious, geographic, socioeconomic and other demographic lines. ” -- Albert Einstein Institution Challenging unjust social and economic systems Developing, preserving and extending democratic practices, human rights, civil liberties, and freedom of religion Resisting genocide Albert Einstein Institution. Applications of nonvilolent action. Albert Einstein Institution, 2001. Syndemics Prevention Network Powers RS, Vogele WB, Kruegler C, Mc. Carthy RM. Protest, power, and change: an encyclopedia of nonviolent action from ACT-UP to women's suffrage. New York: Garland Pub. , 1997.

Systems Archetype “Fixes that Fail” + Problem Symptom + - B Fix - + Delay R Unintended Consequence Syndemics Prevention Network + Kim DH. Systems archetypes at a glance. Cambridge, MA: Pegasus Communications, Inc. , 1994. Characteristic Behavior: Better before Worse

“Fixes that Fail” in Public Health Vocabulary The Risk of Targeted Interventions + - Health Problem + What issues tend to be exclude d? Syndemics Prevention Network Targeted Response B - R + Exclusions Delay +

Some Categories of Exclusions Social Disparity & Disconnection Disorientation Political Conceptual Disarray Organizational Together, these forces may seriously undermine the effectiveness of health protection policy Syndemics Prevention Network

How Many Triangles Do You See? Syndemics Prevention Network Wickelgren I. How the brain 'sees' borders. Science 1992; 256(5063): 1520 -1521.

Boundary Critique Creating a new theory is not like destroying an old barn and erecting a skyscraper in its place. It is rather like climbing a mountain, gaining new and wider views, discovering unexpected connections between our starting point and its rich environment. -- Albert Einstein Ulrich W. Boundary critique. In: Daellenbach HG, Flood RL, editors. The Informed Student Guide to Management Science. London: Thomson; 2002. p. 41 -42. . Syndemics Prevention Network Ulrich W. Reflective practice in the civil society: the contribution of critically systemic thinking. Reflective Practice 2000; 1(2): 247 -268. http: //www. geocities. com/csh_home/downloads/ulrich_2000 a. pdf

Boundary Critique Equalizing Experts and Ordinary Citizens • “Professional expertise does not protect against the need for making boundary judgements…nor does it provide an objective basis for defining boundary judgements. It’s exactly the other way round: boundary judgements stand for the inevitable selectivity and thus partiality of our propositions. • It follows that experts cannot justify their boundary judgements (as against those of ordinary citizens) by referring to an advantage of theoretical knowledge and expertise. • When it comes to the problem of boundary judgements, experts have no natural advantage of competence over lay people. ” -- Werner Ulrich W. Reflective practice in the civil society: the contribution of critically systemic thinking. Reflective Practice 2000; 1(2): 247 -268. Syndemics Prevention Network

“You Can Argue with Einstein” “For certain purposes, public judgment should carry more weight than expert opinion – and not simply because the majority may have more political power than the individual expert but because the public’s claim to know is actually stronger than the experts’. . . the judgment of the general public can, under some conditions, be equal or superior in quality to the judgment of experts and elites who possess far more information, education, and ability to articulate their views. ” -- Daniel Yankelovich Syndemics Prevention Network Yankelovich D. Coming to public judgment: making democracy work in a complex world. 1 st ed Syracuse, NY: Syracuse University Press, 1991. p. 220.

Boundary Critique Syndemics Prevention Network Ulrich W. Reflective practice in the civil society: the contribution of critically systemic thinking. Reflective Practice 2000; 1(2): 247 -268. http: //www. geocities. com/csh_home/downloads/ulrich_2000 a. pdf

Epi·demic • • Epidemiology first appeared just over a century ago (in 1873), in the title of J. P. Parkin's book "Epidemiology, or the Remote Cause of Epidemic Diseases“ • A representation of the cholera epidemic of the nineteenth century. Source: NIH The term epidemic is an ancient word signifying a kind of relationship wherein something unknown (or unknowable) is put upon the people Ever since then, the conditions that cause health problems have increasingly become matters of public concern and public work “The pioneers of public health did not change nature, or men, but adjusted the active relationship of men to certain aspects of nature so that the relationship became one of watchful and healthy respect. ” -- Gil Elliot G. Twentieth century book of the dead. New York, : C. Scribner, 1972. Martin PM, Martin-Granel E. 2, 500 -year evolution of the term epidemic. Emerging Infectious Diseases 2006. Available from http: //www. cdc. gov/ncidod/EID/vol 12 no 06/05 -1263. htm National Institutes of Health. A Short History of the National Institutes of Health. Bethesda, MD: 2006. Available from http: //history. nih. gov/exhibits/history/ Syndemics Prevention Network Parkin J. Epidemiology; or the remote cause of epidemic diseases in the animal and the vegetable creation. London: J and A Churchill, 1873.

Syn·demic Events Co-occurring • The term syndemic, first used in 1992, strips away the idea that illnesses originate from extraordinary or supernatural forces and places the responsibility for affliction squarely within the public arena • It acknowledges relationships and signals a commitment to studying population health as a a fragile, dynamic state requiring continual effort to maintain and one that is imperiled when social and physical forces operate in harmful ways Confounding Connecting* Synergism System Syndemic * Includes several forms of connection or inter-connection such as synergy, intertwining, intersecting, and overlapping Syndemics Prevention Network Milstein B. Hygeia's constellation: navigating health futures in a dynamic and democratic world. Doctoral dissertation. Cincinnati, OH: Union Institute and University. November, 2006. Milstein B. Spotlight on syndemics. Centers for Disease Control and Prevention, 2001. w

Health System Dynamics Public Work Society's Health Response General Protection Targeted Protection Primary Prevention Demand for response Becoming safer and healthier Safer Healthier People Becoming vulnerable Tertiary Prevention Secondary Prevention Vulnerable People Becoming afflicted Afflicted without Complications Developing complications Afflicted with Complications Adverse Living Conditions Dying from complications “One major task that CDC is intending to address is balancing this portfolio of our health system so that there is much greater emphasis placed on health protection, on making sure that we invest the same kind of intense resources into keeping people healthier or helping them return to a state of health and low vulnerability as we do to disease care and end of life care. " -Milstein B, Homer J. The dynamics of upstream and downstream: why is so hard for the health system to work upstream, and what can be done about it? CDC Futures Health Systems Work Group; Atlanta, GA; December 3, 2003. Milstein B, Homer J. The dynamics of upstream and downstream: why is so hard for the health system to work upstream, and what can be done about Gerberding JL. FY 2008 CDC Congressional Budget Hearing. Testimony before the Committee on Appropriations, it? CDC Futures Health Systems Workgroup; and Related Agencies, United States House of Subcommittee on Labor, Health and Human Services, Education Atlanta, GA; 2003. Gerberding JL. CDC's futures initiative. Atlanta, GA: Public Health Training Network; April 12, 2004. Syndemics Prevention Network Representatives; Washington, DC; March 9, 2007. Homer JB, Hirsch GB. System dynamics modeling for public health: background and opportunities. American Journal of Public Health 2006; 96(3): 452 -458. Julie Gerberding

Understanding Health as Public Work - Citizen Involvement in Public Life Society's Health Response General Protection Targeted Protection Primary Prevention - Tertiary Prevention Secondary Prevention Demand for response Becoming safer and healthier Safer Healthier People Becoming vulnerable Vulnerable People Adverse Living Conditions Fraction of Adversity, Vulnerability and Affliction Borne by Disadvantaged Sub-Groups (Inequity) Syndemics Prevention Network Becoming afflicted Afflicted without Complications Developing complications Afflicted with Complications Dying from complications Vulnerable and Afflicted People Social Division Public Strength

Evaluating Dynamic, Democratic Policies Public Work - Citizen Involvement in Public Life Society's Health Response General Protection Targeted Protection Primary Prevention Secondary Prevention Tertiary Prevention Demand for response Becoming safer and healthier Safer Healthier People Becoming vulnerable Vulnerable People Adverse Living Conditions Fraction of Adversity, Vulnerability and Affliction Borne by Disadvantaged Sub-Groups (Inequity) Becoming afflicted Afflicted without Complications Developing complications Afflicted with Complications Dying from complications Vulnerable and Afflicted People Social Division How can we learn about the consequences of alternative policies in a system of this kind? Syndemics Prevention Network Public Strength

What Affects the Balance of Upstream and Downstream Work? Upstream Prevention and Protection -----------------Total 3% Downstream Care and Management ----------------Total 97% Brown R, Elixhauser A, Corea J, Luce B, Sheingod S. National expenditures for health promotion and disease prevention activities in the United States. Washington, DC: Battelle; Medical Technology Assessment and Policy Research Center; 1991. Report No. : BHARC-013/91 -019. Syndemics Prevention Network

Balancing Two Major Areas of Emphasis Public Work Healthy Public Policy & Public Work Medical and Public Health Policy Society's Health Response General Protection Targeted Protection Primary Prevention Tertiary Prevention Secondary Prevention Demand for response Becoming safer and healthier Safer Healthier People Becoming vulnerable Vulnerable People Afflicted without Becoming Complications Developing Complications complications afflicted Dying from complications Adverse Living Conditions DEMOCRATIC SELF-GOVERNANCE World of Transforming… • Deprivation • Dependency • Violence • Disconnection • Environmental decay • Stress • Insecurity • Etc… Syndemics Prevention Network By Strengthening… • Leaders and institutions • Foresight and precaution • The meaning of work • Mutual accountability • Plurality • Democracy • Freedom • Etc… MANAGEMENT OF DISEASES AND RISKS World of Providing… • Education • Screening • Disease management • Pharmaceuticals • Clinical services • Physical and financial access • Etc… Milstein B. Hygeia's constellation: navigating health futures in a dynamic and democratic world. Doctoral dissertation. Cincinnati, OH: Union Institute and University. November, 2006.

Two Broad Types of Policy Upstream Type • Macro policy • System-wide scope Downstream • Micro policy • Sector-specific scope • Guaranteed living wage • Breast cancer screening • War and the preparation for war Examples • Educational testing • Regulation of “private” corporate • Housing vouchers behavior Procedures • “High politics” Syndemics Prevention Network • “Low politics” Crick BR. In defense of politics. 4 th ed Chicago, IL: University of Chicago Press, 1993. Walt G. Health policy: an introduction to process and power. Atlantic Highlands, NJ: Zed Books, 1994.

Defining Keywords • Political The action of diverse people negotiating their differences for common governance, from the Greek, politikos, “of the citizen” • Partisan Fervent, sometimes militant support for a party, cause, faction, person, or idea, from Middle French, part, “faction” Crick BR. In defense of politics. 4 th ed Chicago, IL: University of Chicago Press, 1993. Syndemics Prevention Network Boyte HC. Everyday politics: reconnecting citizens and public life. Philadelphia, PA: University of Pennsylvania Press, 2004.

Two Policy Orientations for Health Action Healthy Public Policy Medical and Public Health Policy Concerned chiefly with assuring safer, healthier conditions for all Concerned chiefly with preventing and alleviating affliction, managing complications, and delaying premature death or disability Relies heavily on multiple, small-scale, local solutions, with low technology Relies heavily on specific high-technology solutions, widely applied Combines analyses into a broad systems view, transcending sector boundaries Confines analyses to the health sector Future-oriented (reacting to long-term dynamics) Present-oriented (reacting to immediate events) Questions the givens, focuses on plausible outcomes Accepts the givens, focuses on probable outcomes Evaluated first through simulation, then through implementation Evaluated through implementation Main resources are citizen leadership and broadbased public work (including that of professionals) Main resources are money, professional expertise, and technology (often excluding citizen leadership) Syndemics Prevention Network Adapted from: Hancock T. Beyond health care: from public health policy to healthy public policy. Can J Public Health 1985; 76 Suppl 1: 9 -11.

Two Policy Orientations for Health Action Healthy Public Policy Medical and Public Health Policy Concerned chiefly with assuring safer, healthier conditions for all Concerned chiefly with preventing and alleviating affliction, managing complications, and delaying premature death or disability Relies heavily on multiple, small-scale, local solutions, with low technology Relies heavily on specific high-technology solutions, widely applied Combines analyses into a broad systems view, transcending sector boundaries Confines analyses to the health sector Future-oriented (reacting to long-term dynamics) Present-oriented (reacting to immediate events) Questions the givens, focuses on plausible outcomes Accepts the givens, focuses on probable outcomes Evaluated first through simulation, then through implementation Evaluated through implementation Main resources are citizen leadership and broadbased public work (including that of professionals) Main resources are money, professional expertise, and technology (often excluding citizen leadership) Syndemics Prevention Network Adapted from: Hancock T. Beyond health care: from public health policy to healthy public policy. Can J Public Health 1985; 76 Suppl 1: 9 -11.

Two Policy Orientations for Health Action Healthy Public Policy Medical and Public Health Policy Concerned chiefly with assuring safer, healthier conditions and reducing vulnerability for all Concerned chiefly with preventing and alleviating affliction, managing complications, and delaying premature death or disability Relies heavily on multiple, small-scale, local solutions, with low technology Relies heavily on specific high-technology solutions, widely applied Combines analyses into a broad systems view, transcending sector boundaries Confines analyses to the health sector Future-oriented (concerned with long-term dynamics) Present-oriented (reacting to immediate events) Questions the givens, focuses on plausible outcomes Accepts the givens, focuses on probable outcomes Evaluated first through simulation, then through implementation Evaluated through implementation Main resources are citizen leadership and broadbased public work (including that of professionals) Main resources are money, professional expertise, and technology (often excluding citizen leadership) Syndemics Prevention Network Adapted from: Hancock T. Beyond health care: from public health policy to healthy public policy. Can J Public Health 1985; 76 Suppl 1: 9 -11.

Looking Backward Retrospective Policy Evaluation Syndemics Prevention Network

Adult Per Capita Cigarette Consumption and Major Smoking and Health Events United States, 1900 -1998 5, 000 1 st Surgeon General’s Report Broadcast Ad Ban Federal Cigarette Tax Doubles Number of Cigarettes 4, 000 3, 000 2, 000 Health promotion does not seek to control for secular trends. It tries to create them! -- Marshall Kreuter Nonsmokers 1 st Smoking. Cancer Concern Rights Movement Begins 1, 000 0 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 Syndemics Prevention Network U. S. Department of Health and Human Services. Reducing tobacco use: a report of the Surgeon General. Atlanta, GA: U. S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health; 2000. Available at .

Tracking Statewide Tobacco Control Efforts Syndemics Prevention Network California Department of Health Services. California tobacco control update: the social norm change approach. Sacramento, CA: Tobacco Control Section, California Department of Health Services 2006. .

What was Happening in California? Comprehensive policy featuring… • • Chronic disease programs to reduce the burden of tobacco-related diseases • School-based efforts • Enforcement • Counter-marketing • Cessation programs • Surveillance and evaluation • Syndemics Community programs to reduce tobacco use • Prevention Network Statewide focus Administration and management

What was Happening in California? The Comprehensiveness Imperative • Interventions by themselves ineffective when taken to scale • In trying to isolate the essential components of tobacco control programs that made them effective, none could be shown to stand alone • Any combination of methods was more effective than the individual methods • The more components, the more effective • The more components, the better coverage Syndemics Prevention Network Green LW. A federal agency's journey from bootstrap epidemiology to evidence-based practice to practice-based evidence. 4 th Annual CDC Evaluation Summer Institute; Atlanta, GA: Centers for Disease Control and Prevention; June 10, 2004. Available at .

U. S. Policy Response to Concerns About Elevated Blood Lead Levels 110 17 Predicted blood lead 16 100 15 14 Mean blood lead levels ( g/d. L) 90 80 Gasoline lead 13 12 Lead used in gasoline Intervention Effect: 70 Blood lead fell 10 times (thousands more than predicted! of tons) 60 11 50 10 Observed blood lead 9 40 30 1975 1976 1977 1978 1979 Year Syndemics Prevention Network Data: National Health and Nutrition Examination Survey II 1980 1981

Continuing Effects and Further Actions Blood Lead Levels in the U. S. Population, 1976– 1999 lead paint ban 1976 20 18 can solder phase-out begins 1978 Blood Lead Levels (mg/d. L) 16 unleaded gasoline introduced 1979 14 12 10 8 lead & copper rule 1991 6 can solder ends 1992 4 2 leaded gas ends 1996 2. 7 2. 0 0 1974 1976 1978 1980 1984 1986 Year Syndemics Prevention Network. Data 1982 Source: NHANES II, III, 99+ 1988 1990 1992 1994 1996 1998 2000

Lead-Based Paint in Housing • 24 million housing units (25% of the nation’s housing) have significant lead-based paint hazards • 1. 2 million homes with significant lead-based paint hazards housed low income families with children under the age of 6 Syndemics Prevention Network Source: National Lead-Based Paint Survey (1998 -2000)

Navigational Ventures Finland’s North Karelia Project Puska P. The North Karelia Project: 20 year results and experiences. Helsinki: National Public Health Institute, 1995. Syndemics Prevention Network National Public Health Institute. North Karelia international visitor's programme. National Public Health Institute, 2003. Available at .

Focusing the Intervention Policy A: Focus on High Risk Individuals Policy B: Focus on Risk Conditions for All Syndemics Prevention Network Puska P. The North Karelia Project: 20 year results and experiences. Helsinki: National Public Health Institute, 1995

Broad Intervention Policy North Karelia Project Individual Effort Disease Burden Public Work Syndemics Prevention Network

Directing Change North Karelia Project Selected Action Strategies • Medical services, if necessary • Newspaper coverage: articles, editorials, letters • TV time: highly rated 30 -45 minute shows (no PSAs) • Housewives’ organization: cooking and dietary choices • Opinion leaders: role models, support groups, public action • Tax shifting: tobacco, butter, milk • Economic Renewal – Decline of dairy – Rise of berry – Rise of vegetable oil and rapeseed oil – Rise of healthier breads, cheeses, sausages, etc Puska P. The North Karelia Project : 20 year results and experiences. Helsinki: National Public Health Institute, 1995. Syndemics Prevention Network

Transforming All Dimensions of the System Efforts to Fight Afflictions Efforts to Build Power Health Power to Act Living Conditions Efforts to Improve Adverse Living Conditions Syndemics Prevention Network

Directing Change North Karelia Project Efforts to Fight Afflictions (design/deliver) • Screening • Education • Risk reduction counseling • Medical/pharmaceutical treatment • Disease self-management Syndemics Prevention Network

Directing Change North Karelia Project Efforts to Improve Adverse Living Conditions (develop/promote) • Tobacco legislation • Food-labeling requirements • Margarines and oils • Low-fat milk • Low-fat, low-salt, high-fiber bread • Vegetable-containing sausage (with mushrooms) • Berry farming and consumption • Community competitions, morale, and social norms • State welfare system (at the national, regional, sub-regional, and local levels) Syndemics Prevention Network

Building Power North Karelia Project Health Professionals • Physicians • Health Educators • Psychologists • Epidemiologists • Sociologists • Hospital administrators • Pharmaceutical manufacturers • Nurses • Rehabilitation therapists Syndemics Prevention Network Other Citizens • Bakers • Farmers • Grocers • Food scientists, manufacturers • Restaurant owners • Housewives • Entertainers • Entrepreneurs • Journalists, media professionals • Teachers • School administrators • Elected representatives

Charting Progress North Karelia Project Syndemics Prevention Network Vartiainen E, Puska P, Pekkanen J, Toumilehto J, Jousilahti P. Changes in risk factors explain changes in mortality from ischaemic heart disease in Finland. British Medical Journal 1994; 309(6946): 23 -27.

Charting Progress North Karelia Project -49% -68% -73% -44% -71% Puska P. The North Karelia Project : 20 year results and experiences. Helsinki: National Public Health Institute, 1995. Syndemics Prevention Network National Public Health Institute. North Karelia international visitor's programme. National Public Health Institute, 2003. Accessed May 30, 2004 at .

Looking Forward Prospective Policy Evaluation Featuring Systems Thinking & Modeling Syndemics Prevention Network

Health System Dynamics Public Work Society's Health Response General Protection Targeted Protection Primary Prevention Demand for response Becoming safer and healthier Safer Healthier People Becoming vulnerable Tertiary Prevention Secondary Prevention Vulnerable People Becoming afflicted Afflicted without Complications Developing complications Afflicted with Complications Adverse Living Conditions Dying from complications “One major task that CDC is intending to address is balancing this portfolio of our health system so that there is much greater emphasis placed on health protection, on making sure that we invest the same kind of intense resources into keeping people healthier or helping them return to a state of health and low vulnerability as we do to disease care and end of life care. " -Milstein B, Homer J. The dynamics of upstream and downstream: why is so hard for the health system to work upstream, and what can be done about it? CDC Futures Health Systems Work Group; Atlanta, GA; December 3, 2003. Milstein B, Homer J. The dynamics of upstream and downstream: why is so hard for the health system to work upstream, and what can be done about Gerberding JL. FY 2008 CDC Congressional Budget Hearing. Testimony before the Committee on Appropriations, it? CDC Futures Health Systems Workgroup; and Related Agencies, United States House of Subcommittee on Labor, Health and Human Services, Education Atlanta, GA; 2003. Gerberding JL. CDC's futures initiative. Atlanta, GA: Public Health Training Network; April 12, 2004. Syndemics Prevention Network Representatives; Washington, DC; March 9, 2007. Homer JB, Hirsch GB. System dynamics modeling for public health: background and opportunities. American Journal of Public Health 2006; 96(3): 452 -458. Julie Gerberding

Seeing Beyond the Probable “Most organizations plan around what is most likely. In so doing they reinforce what is, even though they want something very different. ” -- Clement Bezold • 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. Syndemics Prevention Network

A “Bathtub” View of Chronic Illness Dynamics Low risk Bathtubs = Accumulations = Stocks; Drains & Faucets = Flows Risk onset Risk prevention High risk Illness onset Risk mgmt Mildly ill Complications onset Disease mgmt Severely ill Urgent & long-term care Syndemics Prevention Network Booth-Sweeney LB, Sterman JD. Bathtub dynamics: initial results of a systems thinking inventory. System Dynamics Review 2000; 16(4): 249 -286. Death

Re-Directing the Course of Change Questions Addressed by System Dynamics Modeling What? ? e her W Prevalence of Obese Adults, United States Simulation Experiments in Action Labs ? hy W Ho w? Wh o? 2010 Data Source: NHANES Syndemics Prevention Network 2020

Simulations for Learning in Dynamic Systems Multi-stakeholder Dialogue Dynamic Hypothesis (Causal Structure) Plausible Futures (Policy Experiments) Obese fraction of Adults (Ages 20 -74) Fraction of popn 20 -74 50% 40% 30% 20% 10% 0% 1970 1980 1990 2000 2010 2020 2030 2040 2050 Morecroft JDW, Sterman J. Modeling for learning organizations. Portland, OR: Productivity Press, 2000. Syndemics Prevention Network Sterman JD. Business dynamics: systems thinking and modeling for a complex world. Boston, MA: Irwin Mc. Graw-Hill, 2000.

A Model Is… An inexact representation of the real thing It helps us understand, explain, anticipate, and make decisions “All models are wrong, some are useful. ” Syndemics Prevention Network -- George Box

CDC Obesity Dynamics Modeling Project Contributors Project Coordinator • Bobby Milstein System Dynamics Consultants • Jack Homer • Gary Hirsch Core Design Team • Dave Buchner Time Series Analysts • Andy Dannenberg • Danika Parchment • Bill Dietz • Cynthia Ogden • Deb Galuska • Margaret Carroll • Larry Grummer-Strawn • Hatice Zahran • Anne Hadidx Workshop Participants • Robin Hamre • Atlanta, GA: May 17 -18 (N=47) • Laura Kettel-Khan • Lansing, MI: July 26 -27 (N=55) • Elizabeth Majestic • Jude Mc. Divitt • Cynthia Ogden • Michael Schooley Cover of "The Economist", Dec. 13 -19, 2003 Syndemics Prevention Network Homer J, Milstein B, Dietz W, Buchner D, Majestic D. Obesity population dynamics: exploring historical growth and plausible futures in the U. S. 24 th International Conference of the System Dynamics Society; Nijmegen, The Netherlands; July 26, 2006.

Obesity Prevalence Over the Decades Two Broad Phases Phase 2: More Detailed Drivers of Change Policy Drivers (Trends & Interventions Affecting Caloric Balance by Age, Sex, BMI Category, etc…) Phase 1: Calculating Obesity Dynamics Dynamic Population Weight Framework (BMI Surveillance, Demography, and Nutritional Science) Consequences Over Time Changing Prevalence of Four BMI Categories: 1970 -2050 Syndemics Prevention Network

Focus of Obesity Dynamics Simulation Model • Explore effects of new interventions affecting caloric balance (intake less expenditure) – What are the likely consequences? • How much impact on adult obesity? • How long will it take to see? • Should we target other subpopulations? (age, sex, weight category) • Consider two classes of interventions – Changes in food & activity environments – Weight loss/maintenance services for individuals • Additional intervention details (composition, coverage, efficacy, cost) left outside model boundary for now – Available data are inadequate to quantify impacts and cost-effectiveness – Could stakeholder Delphi help? Syndemics Prevention Network

Obesity Dynamics Over the Decades Dynamic Population Weight Framework Birth Immigration Yearly aging Population by Age (0 -99) and Sex Caloric Balance Flow-rates between BMI categories Not Overweight Moderately Obese Severely Obese Death Overweight and obesity prevalence Syndemics Prevention Network

Obesity Prevalence Over the Decades Dynamic Population Weight Framework Births Age 0 Not Overweight Moderately Obese Severely Obese Age 1 Not Overweight Moderately Obese Severely Obese Age 99 Not Overweight Moderately Obese Severely Obese No Change in BMI Category (maintenance flow) Increase in BMI Category (up-flow) Decline in BMI Category (down-flow) Syndemics Prevention Network Births

Information Sources Topic Area Data Source Prevalence of Overweight and Obesity BMI prevalence by sex and age (10 age ranges) National Health and Nutrition Examination Survey (1971 -2002) Translating Caloric Balances into BMI Flow-Rates BMI category cut-points for children and adolescents Median BMI within each BMI category Median height Average kilocalories per kilogram of weight change CDC Growth Charts National Health and Nutrition Examination Survey (1971 -2002) Forbes 1986 Estimating BMI Category Down-Flow Rates In adults: Self-reported 1 -year weight change by sex and age NHANES (2001 -2002) *indicates 7 -12% per year* In children: BMI category changes by grade and starting BMI Arkansas pre-K through 12 th grade assessment (2004 -2005) *indicates 15 -28% per year* Population Composition Population by sex and age Death rates by sex and age U. S. Census and Vital Statistics (1970 -2000 and projected) Birth and immigration rates Influence of BMI on Mortality Impact of BMI category on death rates by age Syndemics Prevention Network Flegal, Graubard, et al. 2005.

Reproducing Historical Trends One of 20 {sex, age} Subgroups: Females age 55 -64 (b) Obese fraction 80% Fraction of women age 55 -64 (a) Overweight fraction 60% 40% 20% 0% 1970 1975 1980 1985 NHANES 1990 1995 2000 50% 40% 30% 20% 10% 0% 1970 2005 1975 Simulated 1980 1985 NHANES 1990 1995 2000 Simulated Fraction of women age 55 -64 (c) Severely obese fraction 25% 20% 15% 10% 5% 0% 1970 1975 1980 1985 NHANES Syndemics Prevention Network 1990 1995 2000 2005 Simulated Note: S-shaped curves, with inflection in the 1990 s 2005

Obesity Dynamics Over the Decades Two Classes of Interventions Dynamic Population Weight Framework Birth Immigration Changes in the Physical and Social Environment Trends and Planned Interventions Yearly aging Population by Age (0 -99) and Sex Caloric Balance Flow-rates between BMI categories Not Overweight Moderately Obese Weight Loss/Maintenance Services for Individuals Death Overweight and obesity prevalence Syndemics Prevention Network Severely Obese

Assumptions for Future Scenarios Base Case • Caloric balances stay at 2000 values through 2050 Altering Food and Activity Environments • Reduce caloric balances to their 1970 values by 2015 • Focused on – ‘School Youth’: youth ages 6 -19 – ‘All Youth’: all youth ages 0 -19 – ‘School+Parents’: school youth plus their parents – ‘All Adults’: all adults ages 20+ – ‘All Ages’: all youth and adults Subsidized Weight Loss Programs for Obese Individuals • • Syndemics Prevention Network Net daily caloric reduction of program is 40 calories/day (translates to 1. 8 kg weight loss per year) Fully effective by 2010 and terminated by 2020

Alternative Futures Obesity in Adults (20 -74) Obese fraction of Adults (Ages 20 -74) Fraction of popn 20 -74 50% 40% 30% 20% 10% 0% 1970 1980 1990 Base School+Parents All. Ages+Wt. Loss Syndemics Prevention Network 2000 2010 2020 School. Youth All. Adults 2030 2040 All. Youth All. Ages 2050

U. S. policy discourse is primarily focused on: • Prevention among school-aged youth • Medical treatment for the severely obese Syndemics Prevention Network

Findings & Limitations • This model improves our understanding of obesity dynamics and supports pragmatic planning and evaluation – Traces plausible impacts of intervention and addresses questions of whom to target, by how much, and by when – Inflection point in obesity probably occurred during the 1990 s – Impacts of changing environments on adult obesity take decades to play out fully: “Carryover effect” – Youth interventions have only small impact on overall adult obesity (assuming adult habits are determined primarily by adult environment) – Effective weight-loss for the obese could greatly accelerate progress— but is there a realistic alternative to risky bariatric surgery? • But it has limitations related to its narrow scope – Does not indicate exact nature of trends and interventions affecting caloric intake, nor cost-effectiveness nor likely socio-political responses (reinforcing or resistant) of interventions – Concentrating on detailed life stage data came at expense of a broader analysis of trends, interventions, and feedback effects Syndemics Prevention Network

Mokdad AH, Bowman BA, Ford ES, Vinicor F, Marks JS, Koplan JP. The continuing epidemics of obesity and diabetes in the United States. Journal of the American Medical Association 2001; 286(10): 1195 -200. Syndemics Prevention Network Kaufman FR. Diabesity: the obesity-diabetes epidemic that threatens America--and what we must do to stop it. New York, NY: Bantam Books, 2005.

CDC Diabetes System Modeling Project Discovering Stock-Flow Dynamics Through Action Labs Syndemics Prevention Network Jones AP, Homer JB, Murphy DL, Essien JDK, Milstein B, Seville DA. Understanding diabetes population dynamics through simulation modeling and experimentation. American Journal of Public Health 2006; 96(3): 488 -494.

Project Background • Diabetes programs face tough challenges and questions – Pressure for results on disease burden, not just behavioral change – Diabetes Prevention Program indicates primary prevention is possible, but may be difficult and costly – What is achievable on a population level? – How should funds be allocated? • Standard epidemiological models rarely address such policy questions • Starting Fall 2003, CDC initiates System Dynamics modeling project • Starting Spring 2005, some states join as collaborators in further developing and using the SD model Syndemics Prevention Network

Overview of Diabetes Stock-and-Flow Model Burden of Diabetes Total Prevalence (people with diabetes) People with Normal Blood Sugar Levels Prediabetes Onset e People with Prediabetes Recovering from Prediabetes d Obesity in the General Population People with Diagnosis Undiagnosed b Diabetes People with Diagnosed Diabetes Prediabetes Detection & Management Diabetes Detection Volume Syndemics Deaths a Deaths Inflow Prevention Network Unhealthy Days (per person with diabetes) Developing Diabetes Onset c Costs (per person with diabetes) Outflow Diabetes Management

Overview of Diabetes Stock-and-Flow Model This larger view takes us beyond standard epidemiological models and most intervention programs People with Normal Blood Sugar Levels Pre. Diabetes Onset e Total Prevalence (people with diabetes) People with Prediabetes Diabetes Onset c Costs (per person with diabetes) Unhealthy Days (per person with diabetes) Developing Recovering from Pre. Diabetes d Obesity in the General Population Burden of Diabetes People with Diagnosis Undiagnosed b Diabetes People with Diagnosed Diabetes Deaths a Deaths Prediabetes Detection & Management Diabetes Detection Diabetes Management Standard boundary Inflow Volume Syndemics Prevention Network Outflow

Using Available Data to Ground the Model Information Sources Data • Population growth and death rates U. S. Census • Fractions elderly, black, hispanic • Health insurance coverage National Health Interview Survey National Health and Nutrition Examination Survey Behavioral Risk Factor Surveillance System Professional Literature Syndemics Prevention Network • Diabetes prevalence • Diabetes detection • Prediabetes prevalence • Obesity prevalence • Eye exam and foot exam • Taking diabetes medications • Unhealthy days (HRQOL) • Effects of risk factors and mgmt on onset, complications, and costs • Direct and indirect costs of diabetes

One way we establish the model’s value is by looking at its ability to reproduce historical data (2 variables out of 10 such comparisons) Diagnosed diabetes per thousand total popn 60 Diagnosed fraction of diabetes popn 1 Model 45 NHIS 0. 8 Model 30 0. 6 15 0 1984 1988 1992 1996 2000 NH II 0. 4 2004 1980 1984 NHANES III 1988 1992 Syndemics Homer J. Reference guide for the CDC Diabetes System Model. Atlanta, GA: Division of Diabetes Translation, Centers for Prevention; August, 2006. <. Prevention Network Disease Control and 1996 NH ’ 99 -’ 00 2004

Although we expect obesity to increase little after 2006, diabetes keeps growing robustly for another 20 -25 years Obese Fraction and Diabetes per Thousand Onset=6. 3 per thou 130 0. 7 Diabetes Prevalence Estimated 2006 values Prevalence=92 Prevalence AND /RISING =92 thou 85 0. 35 Obesity Prevalence 40 0 1980 1990 2000 Death=3. 8 per thou 2010 2020 Time (Year) 2030 2040 2050 Diabetes prevalence keeps With high (even if flat) onset, growing after obesity stops prevalence tub keeps filling until deaths (4 -5%/yr)=onset WHY? Syndemics Prevention Network

Unhealthy days impact of prevalence growth, as affected by diabetes management: Past and one possible future Obese Fraction and Diabetes per Thousand Unhealthy Days per Thou and Frac Managed 500 0. 65 130 0. 7 Diabetes Prevalence Managed fraction 375 0. 325 85 0. 35 Obesity Prevalence 40 0 1980 1990 2000 Unhealthy Days from Diabetes 2010 2020 Time (Year) 2030 2040 2050 Diabetes prevalence keeps growing after obesity stops Syndemics Prevention Network 250 0 1980 1990 2000 2010 2020 2030 2040 2050 If disease management gains end, the burden grows

Further Increases in Diabetes Management Increase fraction of diagnosed diabetes getting managed from 58% to 80% by 2015. (No change in the mix of conventional and intensive. ) What do you think will happen? People with Diabetes per Thousand Adults 150 Monthly Unhealthy Days from Diabetes per Thou 500 Diab mgt 125 Base 450 Diabetes mgmt does nothing to Base slow the growth of prevalence— 400 in fact, it increases it. As soon as diabetes mgmt stops improving, 350 unhealthy days start to grow as fast as 300 prevalence. 100 75 50 1980 1990 2000 2010 2020 2030 2040 More people living with diabetes Syndemics Prevention Network 2050 250 1980 1990 2000 2010 Diab mgt 2020 2030 2040 Keeping the burden at bay for nine years longer 2050

Managing Prediabetes AND Reducing Obesity What do you think will happen if, in addition to Pre. D mgmt, obesity is reduced moderately by 2030? What if it is reduced even more? Monthly Unhealthy Days from Diabetes per Thou People with Diabetes per Thousand Adults 150 500 Base 125 450 Pre. D mgmt 400 100 Pre. D & Ob 25% 350 Pre. D & Ob 18% 75 Pre. D & Ob 18% 300 50 1980 1990 2000 2010 2020 2030 2040 250 2050 1980 The more you reduce obesity, the sooner you stop the growth in diabetes—and the more you bring it down Syndemics Prevention Network 1990 2000 2010 2020 2030 2040 … Same with the burden of diabetes 2050

Intervening Effectively Upstream AND Downstream With pure upstream intervention, burden still grows for many years before turning around. What do you think will happen if we add the prior diabetes mgmt intervention on top of the Pre. D+Ob 25 one? People with Diabetes per Thousand Adults Monthly Unhealthy Days from Diabetes per Thou 150 500 Base 450 125 Base 100 Pre. D mgmt 400 All 3 Pre. D mgmt Pred & Ob 25% Pre. D & Ob 25% 350 75 All 3 -Pre. D & Ob 25% & Diab mgmt 300 50 1980 1990 Syndemics Prevention Network 2000 2010 2020 2030 2040 250 2050 1980 1990 2000 2010 2020 2030 With a combination of effective upstream and downstream interventions we could hold the burden of diabetes nearly flat through 2050! 2040 2050

Healthy People 2010 Diabetes Objectives: What Can We Accomplish? Baseline Reduce Diabetes–related Deaths Among Diagnosed (5 -6) Increase Diabetes Diagnosis (5 -4) Reduce New Cases of Diabetes (5 -2) Reduce Prevalence of Diagnosed Diabetes (5 -3) 8. 8 per 1, 000 68% 3. 5 per 1, 000 40 per 1, 000 HP 2010 Target Percent Change 7. 8 -11% 80% +18% 2. 5 -29% 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/Volume 1/05 Diabetes. htm Syndemics Prevention Network

History and Futures for Diabetes Prevalence Reported Trends, HP Objectives, and Simulation Results Simulated Reported I Meet Detection Objective (5 -4) Does this imply failure of the national policy? Or a problem in the goal-setting process itself? F G H Status Quo Meet Onset Objective (5 -2) D B C A HP 2000 Objective E Syndemics Prevention Network HP 2010 Objective (5 -3) Milstein B, Jones A, Homer J, Murphy D, Essien J, Seville D. Charting plausible futures for diabetes prevalence: a role for system dynamics simulation modeling. Preventing Chronic Disease 2007 (in press).

Connecting the Objectives Population Flows and Dynamic Accounting 101 People without Diabetes The targeted 29% reduction in diagnosed onset can only slow the growth in prevalence Initial Onset People with Undiagnosed Diabetes With a diagnosed onset flow of 1. 1 mill/yr Diagnosed As would stepped-up detection effort Onset People with Diagnosed Diabetes Reduced death would add further to prevalence It is impossible for any policy to reduce prevalence 38% by 2010! Syndemics Prevention Network Dying from Diabetes Complications And a death flow of 0. 5 mill/yr (4%/yr rate) Milstein B, Jones A, Homer J, Murphy D, Essien J, Seville D. Charting plausible futures for diabetes prevalence: a role for system dynamics simulation modeling. Preventing Chronic Disease 2007 (in press).

How Should We Value Simulation Studies? • All models, including simulations, are incomplete and imprecise • But some are better than others and capture more important aspects of the real world’s dynamic complexity “All models are wrong, some are useful. ” -- George Box • A valuable model is one that can help us understand anticipate better than we do with the unaided mind Artist: Rene Magritte Sterman JD. All models are wrong: reflections on becoming a systems scientist. System Dynamics Review 2002; 18(4): 501 -531. Syndemics Prevention Network Meadows DH, Richardson J, Bruckmann G. Groping in the dark: the first decade of global modelling. New York, NY: Wiley, 1982. Forrester JW. Counterintuitive behavior of social systems. Technology Review 1971; 73(3): 53 -68.

Barriers to Learning in Dynamic Systems Syndemics Prevention Network Sterman J. Business dynamics: systems thinking and modeling for a complex world. Boston, MA: Irwin Mc. Graw-Hill, 2000.

But We Can Create Virtual Worlds for Learning “In [dynamically complex] circumstances simulation becomes the only reliable way to test a hypothesis and evaluate the likely effects of policies. " -- John Sterman Syndemics Prevention Network Sterman J. Business dynamics: systems thinking and modeling for a complex world. Boston, MA: Irwin Mc. Graw-Hill, 2000.

Learning In and About Dynamic Systems “In [dynamically complex] circumstances simulation becomes the only reliable way to test a hypothesis and evaluate the likely effects of policies. " -- John Sterman Complexity Hinders Benefits of Simulation • • Formal means of evaluating options • Experimental control of conditions • Generation of evidence (by eroding the conditions for experimentation) Compressed time Acting upon evidence (by including the behaviors of other powerful actors) • Actions can be stopped or reversed • Tests for extreme conditions • Early warning of unintended effects • Opportunity to assemble stronger support • • Learning from evidence • (by demanding new heuristics for interpretation) • Visceral engagement and learning Complete, undistorted results Sterman JD. Learning from evidence in a complex world. American Journal of Public Health (in press). Syndemics Prevention Network Sterman JD. Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston, MA: Irwin Mc. Graw-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 What? e? her W Prevalence of Obese Adults, United States ? hy W Ho w? Wh Data Source: NHANES o? 2010 2020 “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 Syndemics Prevention Network 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 Mc. Graw-Hill, 2000.

An Alternative Philosophical Tradition "Grant an idea or belief to be true…what concrete difference will its being true make in anyone's actual life? -- William James Positivism • Begins with a theory about the world • Learning through observation and falsification • Asks, “Is this theory true? ” Pragmatism • Begins with a response to a perplexity or injustice in the world • Learning through action and reflection • Asks, “How does this work make a difference? ” We are not talking about theories to explain, but conceptual, methodological, and moral orientations: the frames of reference that shape how we think, how we act, how we learn, and what we value Shook J. The pragmatism cybrary. 2006. Available at . Addams J. Democracy and social ethics. Urbana, IL: University of Illinois Press, 2002. Syndemics Prevention Network West C. The American evasion of philosophy: a genealogy of pragmatism. Madison, WI: University of Wisconsin Press, 1989.

A Navigational View of Public Health Work Where we want to go? How do we prepare to get there? Where you do want to live? Where do you want your children to live? Thompson N. Reflections on voyaging and home. Polynesian Voyaging Society, 2001. Accessed July 18 at . Syndemics Prevention Network Milstein B. Hygeia's constellation: navigating health futures in a dynamic and democratic world. Doctoral dissertation. Cincinnati, OH: Union Institute and University. November, 2006.

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 N. Reflections on voyaging and home. Polynesian Voyaging Society, 2001. Accessed July 18 at . Syndemics Prevention Network Milstein B. Hygeia's constellation: navigating health futures in a dynamic and democratic world. Doctoral dissertation. Cincinnati, OH: Union Institute and University. November, 2006.