Syndemics Prevention Network Edinburgh Evaluation Summer School Edinburgh, Scotland June 6, 2007 Exploring the Dynamic and Democratic Dimensions of Health.

Syndemics Prevention Network Edinburgh Evaluation Summer School Edinburgh, Scotland June 6, 2007 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 Policy Evaluation

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

Syndemics Prevention Network Picture a Neighborhood Where… Conditions are not supportive of healthy living 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 More could be done through better local organizing and with effective assistance from outside allies (e.g., philanthropy, government) James Nachtwey in Sachs J. How to end poverty. Time Magazine 2005 March 14. 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 0 10 20 30 40 19801990200020102020203020402050 Million people Historical Data Markov Model 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. 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. Markov Forecasting Model Trend is not destiny! How? Why? Where? Who? What?

Syndemics Prevention Network 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 A Field in Transition

Syndemics Prevention Network Left Unexamined… Singular “program” as the unit of inquiry (N=1 organizational depth) Dynamic aspects of program effectiveness (e.g., better-before-worse patterns of change) 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) 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. Framework for Program Evaluation “Both a synthesis of existing evaluation practices and a standard for further improvement.”

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

Syndemics Prevention Network Locating categorical disease or risk prevention programs within a broader system of health protection Constructing credible knowledge without comparison/control groups 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 Defining standards and values for judgment Others… Serious Challenges for Planners and Evaluators

Syndemics Prevention Network 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 Questions and Discussion Throughout

Syndemics Prevention Network Defining Keywords 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. Bennett T, Grossberg L, Morris M. New keywords: a revised vocabulary of culture and society. Malden, MA: Blackwell Pub., 2005. Scriven M. Evaluation thesaurus. 4th ed Newbury Park, CA: Sage Publications, 1991. Policy evaluation is… 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 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

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

Syndemics Prevention Network Defining Keywords Walt G. Health policy: an introduction to process and power. Atlantic Highlands, NJ: Zed Books, 1994. Ignatieff M. The grey empitness inside John Major. The Observer 1992 November 15; 25. “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 Artist: Boyce Watt 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

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

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 Robustness for longer- term projection Value for developing policy insights Degrees of uncertainty Increasing: Depth of causal theory Robustness for longer- term projection Value for developing policy insights Degrees of uncertainty Dynamic Simulation Models Anticipate new trends, learn about policy consequences, and set justifiable goals Tools for Policy Planning & Evaluation

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

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

Syndemics Prevention Network Public Health Work Literally Involves Redirecting the Course of Change 600 500 400 200 100 50 195019601970198019901995 Age-adjusted Death Rate per 100,000 Population 1955196519751985 300 700 Peak Rate Rate if trend continued Year Actual and Expected Death Rates for Coronary Heart Disease, 1950–1998 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. 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 Actual Rate Overall Decline is Linked to… Reduced smoking Changes in diet Better diagnosis and treatment More heath services utilization Overall Decline is Linked to… Reduced smoking Changes in diet Better diagnosis and treatment More heath services utilization 684,000 fewer deaths in 1998 alone

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. One Observer's View…

Syndemics Prevention Network Immense Challenges Ahead 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. CNN. Sarajevo baby to be honored as 6 billionth person on Earth. CNN, 1999. Accessed July 5, 2003 at. World Population Growth

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

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

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

Syndemics Prevention Network Summers J. Soho: a history of London's most colourful neighborhood. Bloomsbury, London, 1989. p. 117. Broad Street, One Year Later John Snow Heroic Success or Cautionary Tale? “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."

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

Syndemics Prevention Network Piecemeal approaches Failure to address root problems Inattention to the larger political and economic system Heirich M. Rethinking health care: innovation and change in America. Boulder, CO: Westview Press, 1999. Crafting Health Policies that will Succeed in a Large, Dynamic System Efforts to reform health care policy have been ineffective because of “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 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. 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 McGraw-Hill, 2000.

Syndemics Prevention Network Changing Views of Population Health What Accounts for Poor Population Health? God’s will Humors, miasma, ether Poor living conditions, immorality (e.g., ?) Single disease, single cause (e.g., ?) Single disease, multiple causes (e.g., ?) 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., ?) 1880 1950 1960 1980 2000 1840 Milstein B. Hygeia's constellation: navigating health futures in a dynamic and democratic world [Doctoral Dissertation]. Cincinnati, OH: Union Institute & University; 2006. Richardson GP. Feedback thought in social science and systems theory. Philadelphia, PA: University of Pennsylvania Press, 1991.

Syndemics Prevention Network Placing Health in a Wider Set of Relationships Health Living Conditions Power to Act 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. “Health Policy” “Social Policy”

Syndemics Prevention Network Two Orientations Prospective Retrospective What have been the observed consequences of prior decisions? For whom? When? Why? At what cost? Recommendations to continue or change strategy 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?

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

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

Syndemics Prevention Network 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. 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.

Syndemics Prevention Network Dangers of Getting Too Specific Krug EG, World Health Organization. World report on violence and health. Geneva: World Health Organization, 2002. 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)

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

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

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

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

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

Syndemics Prevention Network Ulrich W. Boundary critique. In: Daellenbach HG, Flood RL, editors. The Informed Student Guide to Management Science. London: Thomson; 2002. p. 41-42.. 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_2000a.pdf 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

Syndemics Prevention Network 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.” Ulrich W. Reflective practice in the civil society: the contribution of critically systemic thinking. Reflective Practice 2000;1(2):247-268. -- Werner Ulrich

Syndemics Prevention Network “You Can Argue with Einstein” Yankelovich D. Coming to public judgment: making democracy work in a complex world. 1st ed Syracuse, NY: Syracuse University Press, 1991. p. 220. “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 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_2000a.pdf Boundary Critique

Syndemics Prevention Network Epi·demic The term epidemic is an ancient word signifying a kind of relationship wherein something unknown (or unknowable) is put upon the people 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“ Ever since then, the conditions that cause health problems have increasingly become matters of public concern and public work 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/vol12no06/05-1263.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/ Parkin J. Epidemiology; or the remote cause of epidemic diseases in the animal and the vegetable creation. London: J and A Churchill, 1873. A representation of the cholera epidemic of the nineteenth century. Source: NIH “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

Syndemics Prevention Network Syn·demic 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 Syndemic Events System Co-occurring * Includes several forms of connection or inter-connection such as synergy, intertwining, intersecting, and overlapping 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.

Syndemics Prevention Network 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 Workgroup; Atlanta, GA; 2003. Tertiary Prevention Secondary Prevention Primary Prevention Targeted Protection Society's Health Response Demand for response Public Work Safer Healthier People Becoming vulnerable Becoming safer and healthier Vulnerable People Becoming afflicted Afflicted without Complications Developing complications Afflicted with Complications Dying from complications Health System Dynamics Adverse Living Conditions General Protection 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. Gerberding JL. CDC's futures initiative. Atlanta, GA: Public Health Training Network; April 12, 2004. Gerberding JL. FY 2008 CDC Congressional Budget Hearing. Testimony before the Committee on Appropriations, Subcommittee on Labor, Health and Human Services, Education and Related Agencies, United States House of 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. “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." -- Julie Gerberding

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

Syndemics Prevention Network Evaluating Dynamic, Democratic Policies How can we learn about the consequences of alternative policies in a system of this kind?

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

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

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

Syndemics Prevention Network Healthy Public PolicyMedical 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 broad- based public work (including that of professionals) Main resources are money, professional expertise, and technology (often excluding citizen leadership) Two Policy Orientations for Health Action 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.

Syndemics Prevention Network Healthy Public PolicyMedical 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 broad- based public work (including that of professionals) Main resources are money, professional expertise, and technology (often excluding citizen leadership) Two Policy Orientations for Health Action 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.

Syndemics Prevention Network Looking Backward Retrospective Policy Evaluation

Syndemics Prevention Network Adult Per Capita Cigarette Consumption and Major Smoking and Health Events United States, 1900-1998 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. 1st Surgeon General’s Report 1st Smoking- Cancer Concern Nonsmokers Rights Movement Begins Broadcast Ad Ban Federal Cigarette Tax Doubles 0 1,000 2,000 3,000 4,000 5,000 1900191019201930194019501960197019801990 Number of Cigarettes Health promotion does not seek to control for secular trends. It tries to create them! -- Marshall Kreuter Health promotion does not seek to control for secular trends. It tries to create them! -- Marshall Kreuter

Syndemics Prevention Network Tracking Statewide Tobacco Control Efforts 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..

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

Syndemics Prevention Network Green LW. A federal agency's journey from bootstrap epidemiology to evidence-based practice to practice-based evidence. 4th Annual CDC Evaluation Summer Institute; Atlanta, GA: Centers for Disease Control and Prevention; June 10, 2004. Available at. 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 What was Happening in California?

Syndemics Prevention Network Observed blood lead U.S. Policy Response to Concerns About Elevated Blood Lead Levels Year 1975197619771978197919801981 Mean blood lead levels (  g/dL) 9 10 11 12 13 14 15 16 17 Gasoline lead Predicted blood lead Data: National Health and Nutrition Examination Survey II Lead used in gasoline (thousands of tons) 30 40 50 60 70 80 90 100 110 Intervention Effect: Blood lead fell 10 times more than predicted!

Syndemics Prevention Network Continuing Effects and Further Actions Blood Lead Levels in the U.S. Population, 1976–1999 19741976197819801982198419861988199019921994199619982000 Year 18 2 4 6 8 10 12 14 16 Blood Lead Levels (mg/dL) 0 2.7 2.0 unleaded gasoline introduced 1979 unleaded gasoline introduced 1979 can solder phase-out begins 1978 can solder phase-out begins 1978 lead paint ban 1976 lead paint ban 1976 lead & copper rule 1991 lead & copper rule 1991 can solder ends 1992 can solder ends 1992 leaded gas ends 1996 leaded gas ends 1996 20 Data Source: NHANES II, III, 99+

Syndemics Prevention Network 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 Source: National Lead-Based Paint Survey (1998-2000)

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

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

Syndemics Prevention Network Broad Intervention Policy North Karelia Project Disease Burden Individual Effort 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 Health Living Conditions Power to Act Efforts to Fight Afflictions Efforts to Improve Adverse Living Conditions Efforts to Build Power

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

Syndemics Prevention Network 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) Directing Change North Karelia Project

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

Syndemics Prevention Network Charting Progress North Karelia Project 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.

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

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

Syndemics Prevention Network 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 Workgroup; Atlanta, GA; 2003. Tertiary Prevention Secondary Prevention Primary Prevention Targeted Protection Society's Health Response Demand for response Public Work Safer Healthier People Becoming vulnerable Becoming safer and healthier Vulnerable People Becoming afflicted Afflicted without Complications Developing complications Afflicted with Complications Dying from complications Health System Dynamics Adverse Living Conditions General Protection 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. Gerberding JL. CDC's futures initiative. Atlanta, GA: Public Health Training Network; April 12, 2004. Gerberding JL. FY 2008 CDC Congressional Budget Hearing. Testimony before the Committee on Appropriations, Subcommittee on Labor, Health and Human Services, Education and Related Agencies, United States House of 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. “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." -- Julie Gerberding

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.” -- Clement Bezold Seeing Beyond the Probable

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

Syndemics Prevention Network Re-Directing the Course of Change Questions Addressed by System Dynamics Modeling How? Where? Prevalence of Obese Adults, United States Why? Data Source: NHANES 2020 2010 Who? What? Simulation Experiments in Action Labs

Syndemics Prevention Network Simulations for Learning in Dynamic Systems 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 Dynamic Hypothesis (Causal Structure)Plausible Futures (Policy Experiments) Obese fraction of Adults (Ages 20-74) 0% 10% 20% 30% 40% 50% 197019801990200020102020203020402050 Fraction of popn 20-74

Syndemics Prevention Network 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.” -- George Box “All models are wrong, some are useful.” -- George Box

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

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

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

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

Syndemics Prevention Network Parameters (for each age range and sex) Cut-points for BMI categories (b c ) Median BMI within each BMI category (b m ) Median height (h m ) Assumption for the average number of kilocalories per kilogram of weight change (k) –Forbes’ empirical estimate of 8,050 kcal./kg –Implicitly takes into account the efficiency of weight deposition reflecting metabolic and other regulatory adjustments. –Glosses over known differences among individuals: starting weight, composition of diet, efficiency of weight deposition Translating Caloric Balance Changes (ΔK) into Flow Rate Changes (ΔF) Forbes GB. Human body composition: growth, aging, nutrition, and activity. Springer: Berlin, Heidelberg; 1987. Forbes GB. Deliberate overfeeding in women and men: Energy costs and composition of the weight gain. British Journal of Nutrition 56:1-9; 1986.

Syndemics Prevention Network Information Sources Topic AreaData 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 CDC Growth Charts Median BMI within each BMI category National Health and Nutrition Examination Survey (1971-2002) Median height Average kilocalories per kilogram of weight change 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 U.S. Census and Vital Statistics (1970-2000 and projected) Death rates by sex and age Birth and immigration rates Influence of BMI on Mortality Impact of BMI category on death rates by ageFlegal, Graubard, et al. 2005.

Syndemics Prevention Network (a) Overweight fraction 0% 20% 40% 60% 80% 19701975198019851990199520002005 Fraction of women age 55-64 NHANESSimulated (b) Obese fraction 0% 10% 20% 30% 40% 50% 19701975198019851990199520002005 Fraction of women age 55-64 NHANESSimulated (c) Severely obese fraction 0% 5% 10% 15% 20% 25% 19701975198019851990199520002005 Fraction of women age 55-64 NHANESSimulated Reproducing Historical Trends One of 20 {sex, age} Subgroups: Females age 55-64 Note: S-shaped curves, with inflection in the 1990s

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

Syndemics Prevention Network 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 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

Syndemics Prevention Network Alternative Futures Obesity in Adults (20-74) Obese fraction of Adults (Ages 20-74) 0% 10% 20% 30% 40% 50% 197019801990200020102020203020402050 Fraction of popn 20-74 BaseSchoolYouthAllYouth School+ParentsAllAdultsAllAges AllAges+WtLoss

Syndemics Prevention Network 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 1990s –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. Kaufman FR. Diabesity: the obesity-diabetes epidemic that threatens America--and what we must do to stop it. New York, NY: Bantam Books, 2005.

Syndemics Prevention Network CDC Diabetes System Modeling Project Discovering Stock-Flow Dynamics Through Action Labs 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.

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

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

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

Syndemics Prevention Network 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 45 30 15 0 1980198419881992199620002004 Model NHIS Model Diagnosed fraction of diabetes popn 1 0.8 0.6 0.4 1980198419881992199620002004 NHANES III NH ’99 -’00 NH II Homer J. Reference guide for the CDC Diabetes System Model. Atlanta, GA: Division of Diabetes Translation, Centers for Disease Control and Prevention; August, 2006..

Syndemics Prevention Network Prevalence=92 AND RISING Although we expect obesity to increase little after 2006, diabetes keeps growing robustly for another 20-25 years Obese Fraction and Diabetes per Thousand 130 0.7 85 0.35 40 0 19801990200020102020203020402050 Time (Year) Diabetes Prevalence Obesity Prevalence Diabetes prevalence keeps growing after obesity stops WHY? With high (even if flat) onset, prevalence tub keeps filling until deaths (4-5%/yr)=onset Onset=6.3 per thou Estimated 2006 values Death=3.8 per thou Prevalence =92 / thou

Syndemics Prevention Network Unhealthy days impact of prevalence growth, as affected by diabetes management: Past and one possible future Unhealthy Days per Thou and Frac Managed Obese Fraction and Diabetes per Thousand 130 0.7 85 0.35 40 0 19801990200020102020203020402050 Time (Year) Diabetes Prevalence Obesity Prevalence 500 0.65 250 0 19801990200020102020203020402050 375 0.325 Unhealthy Days from Diabetes Managed fraction Diabetes prevalence keeps growing after obesity stops If disease management gains end, the burden grows

Syndemics Prevention Network Further Increases in Diabetes Management People with Diabetes per Thousand Adults 150 125 100 75 50 19801990200020102020203020402050 Monthly Unhealthy Days from Diabetes per Thou 500 450 400 350 300 250 19801990200020102020203020402050 Base Diab mgt Base More people living with diabetes Keeping the burden at bay for nine years longer Diab mgt 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? Diabetes mgmt does nothing to slow the growth of prevalence— in fact, it increases it. As soon as diabetes mgmt stops improving, unhealthy days start to grow as fast as prevalence.

Syndemics Prevention Network Managing Prediabetes AND Reducing Obesity The more you reduce obesity, the sooner you stop the growth in diabetes—and the more you bring it down … Same with the burden of diabetes People with Diabetes per Thousand Adults 150 125 100 75 50 19801990200020102020203020402050 Monthly Unhealthy Days from Diabetes per Thou 500 450 400 350 300 250 19801990200020102020203020402050 Base PreD mgmt PreD & Ob 25% PreD & Ob 18% Base PreD mgmt PreD & Ob 18% PreD & Ob 25% What do you think will happen if, in addition to PreD mgmt, obesity is reduced moderately by 2030? What if it is reduced even more?

Syndemics Prevention Network Intervening Effectively Upstream AND Downstream People with Diabetes per Thousand Adults 150 125 100 75 50 19801990200020102020203020402050 Monthly Unhealthy Days from Diabetes per Thou 500 450 400 350 300 250 19801990200020102020203020402050 Base PreD mgmt Base PreD & Ob 25% Pred & Ob 25% All 3 -- PreD & Ob 25% & Diab mgmt All 3 With a combination of effective upstream and downstream interventions we could hold the burden of diabetes nearly flat through 2050! 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 PreD+Ob25 one?

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

Syndemics Prevention Network ReportedSimulated Status Quo Meet Detection Objective (5-4) Meet Onset Objective (5-2) HP 2010 Objective (5-3) HP 2000 Objective History and Futures for Diabetes Prevalence Reported Trends, HP Objectives, and Simulation Results A B C D E F G H I 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). Does this imply failure of the national policy? Or a problem in the goal-setting process itself?

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 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).

Syndemics Prevention Network 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 A valuable model is one that can help us understand and anticipate better than we do with the unaided mind How Should We Value Simulation Studies? Artist: Rene Magritte Sterman JD. All models are wrong: reflections on becoming a systems scientist. System Dynamics Review 2002;18(4):501-531. 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. “All models are wrong, some are useful.” -- George Box

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

Syndemics Prevention Network But We Can Create Virtual Worlds for Learning Sterman J. 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

Syndemics Prevention Network Learning In and About Dynamic Systems Benefits of Simulation Formal means of evaluating options Experimental control of conditions Compressed time Complete, undistorted results Actions can be stopped or reversed Tests for extreme conditions Early warning of unintended effects Opportunity to assemble stronger support Visceral engagement and learning 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

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?

Syndemics Prevention Network An Alternative Philosophical Tradition Shook J. The pragmatism cybrary. 2006. Available at. Addams J. Democracy and social ethics. Urbana, IL: University of Illinois Press, 2002. West C. The American evasion of philosophy: a genealogy of pragmatism. Madison, WI: University of Wisconsin Press, 1989. "Grant an idea or belief to be true…what concrete difference will its being true make in anyone's actual life? -- William James 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?” Positivism Begins with a theory about the world Learning through observation and falsification Asks, “Is this theory true?” 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

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. Milstein B. Hygeia's constellation: navigating health futures in a dynamic and democratic world. Doctoral dissertation. Cincinnati, OH: Union Institute and University. November, 2006. Where we want to go? How do we prepare to get there? Where do you want your children to live? Where you do want to live?

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. Milstein B. Hygeia's constellation: navigating health futures in a dynamic and democratic world. Doctoral dissertation. Cincinnati, OH: Union Institute and University. November, 2006.

Syndemics Prevention Network Edinburgh Evaluation Summer School Edinburgh, Scotland June 6, 2007 Exploring the Dynamic and Democratic Dimensions of Health.

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Syndemics Prevention Network Edinburgh Evaluation Summer School Edinburgh, Scotland June 6, 2007 Exploring the Dynamic and Democratic Dimensions of Health.

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