Applied Systems Thinking Prize Seminar

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Applied Systems Thinking PrizeSeminar
Understanding the Dynamic Dimensions of Health
Protection Policies
CDC-NIH System Dynamics Collaborative for
Disease Control and Prevention (SD-CDC
Team) Joyce Essien, Jack Homer, Gary Hirsch,
Andrew Jones, Doc Klein, Patty Mabry, Bobby
Milstein, Diane Orenstein, Kristina Wile
ASysT Prize Seminar Alexandria, VA July 25, 2008
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CDC-NIH System Dynamics Collaborative for
Disease Control and Prevention
Diane Orenstein
PattyMabry
BobbyMilstein
JoyceEssien
GaryHirsch
JackHomer
KristinaWile
AndrewJones
Kevin DocKlein
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Applied Systems Thinking (ASysT) Prize
The size of the problems addressed, combined with
the diversity of the SD-CDC team and their long
track record of practical engagements were
decisive factors in the selection. -- ASysT
Institute
Applied Systems Thinking Institute. CDC-NIH
System Dynamics Collaborative Wins 2008 ASysT
Prize. Arlington, VA July 9, 2008.
lthttp//www.anser.org/Content.aspx?mid302gt.
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Plan for Today

• SD-CDC Perspective and Portfolio
• System Dynamics (SD) Simulation Modeling
• Thematic Dialogues
• Overall health protection enterprise
• Chronic diseases
• Leadership, communication, training, funding,
  networking
• Reflection and Future Directions
• QA Along the Way

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Public Health Systems ScienceAddresses
Navigational Policy Question
Prevalence of Diagnosed Diabetes, US
40
Where?
30
Million people
20
What?
How?

• Markov Model Constants
• Incidence rates (/yr)
• Death rates (/yr)
• Diagnosed fractions
• (Based on year 2000 data, per demographic segment)

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Trend is not destiny!
Who?
Why?
0
1980
1990
2000
2010
2020
2030
2040
2050
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 20036155-164. 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 200696(3)488-494.
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Simulations for Learning in Dynamic Systems
The future is not to be predicted, but
created. -- Arthur C. Clarke
Multi-stakeholder Dialogue
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. Sterman JD.
Learning from evidence in a complex world.
American Journal of Public Health
200696(3)505-514. Sterman JD. All models are
wrong reflections on becoming a systems
scientist. System Dynamics Review
200218(4)501-531.
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Americans Views on the Health SystemPoised for
Significant Change?
Over 75 of Americans think the current system
needs fundamental change
Blendon RJ, Altman DE, Deane C, Benson JM, Brodie
M, Buhr T. Health care in the 2008 presidential
primaries. New England Journal of Medicine
2008358(4)414-422.
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Lessons from Previous Health Reform Ventures
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, Bruckman

• Prior efforts were largely disappointing because
  of
• Piecemeal approaches
• Complicated schemes that were opposed by special
  interests
• Assumption that healthcare dynamics are separate
  from other areas of public concern
• Conventional analytic methods make it difficult
  to
• Observe the health system as a large, dynamic
  enterprise
• Craft high-leverage strategies that can overcome
  policy resistance
• Been thinking of health and healthcare as nouns
  (i.e., commodities to be distributed), not as
  verbs (i.e., public work to be produced)

Heirich M. Rethinking health care innovation and
change in America. Boulder CO Westview Press,
1999. Kari NN, Boyte HC, Jennings B. Health as a
civic question. American Civic Forum, 1994.
Available at lthttp//www.cpn.org/topics/health/hea
lthquestion.htmlgt. Meadows DH, Richardson J,
Bruckmann G. Groping in the dark the first
decade of global modelling. New York, NY Wiley,
1982.
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Health Protection as a System
Becoming safer
and healthier
Safer
Afflicted
Afflicted with
Vulnerable
Healthier
without
People
Complications
People
Becoming
Becoming
Developing
Complications
complications
vulnerable
afflicted
Dying from
complications
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 200696(3)452-458.
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.
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CDC Leadership on Health System Transformation
Gerberding JL. CDC protecting people's health.
Director's Update Atlanta, GA July,
2007. Gerberding JL. Health protectionomics a
new science of people, policy, and politics.
Public Health Grand Rounds Washington, DC
George Washington University School of Public
Health and Health Services September 19, 2007.
Available at lthttp//www.kaisernetwork.org/health
_cast/hcast_index.cfm?displaydetailhc2349gt
Centers for Disease Control and Prevention.
Health system transformation Office of Strategy
and Innovation September 28, 2007.
lthttp//intradev.cdc.gov/od/osi/policy/healthSyste
ms_overview.htmgt.
Time 100 the people who shape our world. Time
Magazine 2004 April 26.
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The Promise of a Syndemic Orientation
You think you understand two because you
understand one and one. But you must also
understand and. -- Sufi Saying

• Studying innovations in public health work
• The word syndemic signals special concern for
  many kinds of relationships
• mutually reinforcing health problems
• health status and living conditions
• synergy/fragmentation in the health protection
  system (e.g., by issues, sectors, organizations,
  professionals and other citizens)

Citizen-ship
A syndemic orientation clarifies the dynamic and
democratic character of public health work

• It is one of a few approaches that explicitly
  includes within it our power to respond, along
  with an understanding of its changing pressures,
  constraints, and consequences

Milstein B. Hygeia's constellation navigating
health futures in a dynamic and democratic world.
Atlanta, GA Syndemics Prevention Network,
Centers for Disease Control and Prevention April
15, 2008. http//www.cdc.gov/syndemics/monograph/i
ndex.htm
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Changing (and Accumulating) Views of Population
HealthWhat Accounts for Poor Population Health?

• Gods will
• Humors, miasma, ether
• Poor living conditions, immorality (e.g.,
  sanitation)
• Single disease, single cause (e.g., germ theory)
• Single disease, multiple causes (e.g., heart
  disease)
• Single cause, multiple diseases (e.g., tobacco)
• Multiple causes, multiple diseases (but no
  feedback dynamics) (e.g., hierarchical modeling)
  
• Dynamic feedback among afflictions, living
  conditions, and public strength (e.g., syndemic
  orientation)

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.
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Tools for Policy Planning Evaluation
Events
Time Series Models Describe trends

• Increasing
• Depth of causal theory
• Robustness for longer-term projection
• Value for developing policy insights
• Degrees of uncertainty
• Leverage for change

Multivariate Stat Models Identify historical
trend drivers and correlates
Patterns
Dynamic Simulation Models Anticipate new
trends, learn about policy consequences, and set
justifiable goals
Structure
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CDCs Growing Portfolio of Health System
Dynamics Projects

• Selected Health Priority Areas
• Diabetes
• Obesity
• Infant health
• Cardiovascular health
• Syndemics
• Overall Health Protection Enterprise
• Neighborhood transformation
• National health economy
• Chronic illness dynamics
• Upstream-downstream investments
• Health protection game
• Communications, Training, Funding
• Publications, special issues, monographs
• Interactive workshops, symposia
• Funding announcements
• Website, listserv
• Professional network

Excludes large modeling ventures in the areas
of infectious disease, environmental health, and
emergency preparedness
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SD-CDC Team Publications2002-2008
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CDCs Growing Portfolio of Health System
Dynamics Projects

• Implementation
• Dynamic modeling (11 proj 3.5M 5 FTEs)
• Interactive workshops (100 events)
• Online symposia (5 events 10,000 viewers)
• Networking (700 members)
• Website (200 hits/months)
• AJPH themed issue (March 2006)
• SDR 50th anniversary issue (Fall, 2007)
• CDC monograph (Spring, 2008)
• Extramural funding (15M)
• Training institute (60 post-docs)
• Impacts
• Participant learning
• Changed priorities and considerations
• Confirmed findings
• Institutionalization
• Defining language
• Sparking interest and engagement
• Strategic direction

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Imperatives for Protecting Health
Typical Current StateStatic view of problems
that are studied in isolation
Proposed Future StateDynamic systems and
syndemic approaches
Dynamic systems and syndemic approaches are
imperatives for transforming health protection
research. -- Julie Gerberding CDC Director
Gerberding JL. Protecting health the new
research imperative. Journal of the American
Medical Association 2005294(11)1403-1406.