Overview of system dynamics simulation modeling
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Overview of System Dynamics Simulation Modeling. Bobby Milstein Syndemics Prevention Network Centers for Disease Control and Prevention Atlanta, Georgia [email protected] Systems Thinking and Modeling Workshop Office of Disease Prevention and Health Promotion Bethesda, MD May 8, 2006.

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Overview of system dynamics simulation modeling

Overview of System Dynamics Simulation Modeling

Bobby Milstein

Syndemics Prevention NetworkCenters for Disease Control and PreventionAtlanta, Georgia

[email protected]

Systems Thinking and Modeling Workshop

Office of Disease Prevention and Health Promotion

Bethesda, MD

May 8, 2006


Research imperatives for protecting health

Research Imperatives for Protecting Health

Typical Current StateStatic view of problems that are studied in isolation

Proposed Future StateDynamic systems and syndemic approaches

"Currently, application of complex systems theories or syndemic science to health protection challenges is in its infancy.“

-- Julie Gerberding

Gerberding JL. Protecting health: the new research imperative. Journal of the American Medical Association 2005;294(11):1403-1406.


Overview of system dynamics simulation modeling

AJPH Systems Issue

Science Seminars and Professional Development Efforts

CDC Evaluation Framework Recommends Logic Models

ODPHP Modelers Meeting

SD Emerges as a Promising Methodology

System Change Initiatives Encounter Limitations of Logic Models and Conventional Planning/Evaluation Methods

Syndemics Modeling

Neighborhood Assistance Game

Diabetes Action Labs*

Fetal & Infant Health Goal-Setting

Obesity Overthe Lifecourse*

Upstream-Downstream Investments

Hypertension

Prevention & Control *

Milestones in the Recent Use of System Dynamics Modeling at CDC

1999

2000

2001

2002

2003

2004

2005

2006

* Dedicated multi-year budget


System dynamics was designed to address problems marked by dynamic complexity

System Dynamics Was Designed to Address Problems Marked By Dynamic Complexity

Origins

  • Jay Forrester, MIT (from late 1950s)

  • Public policy applications starting late 1960s

Good at Capturing

  • Differences between short- and long-term consequences of an action

  • Time delays (e.g., transitions, detection, response)

  • Accumulations (e.g., prevalence, capacity)

  • Behavioral feedback (e.g., actions trigger reactions)

  • Nonlinear causal relationships (e.g., effect of X on Y is not constant)

  • Differences or inconsistencies in goals/values among stakeholders

Sterman JD. Business dynamics: systems thinking and modeling for a complex world. Boston, MA: Irwin McGraw-Hill, 2000.

Homer JB, Hirsch GB. System dynamics modeling for public health: background and opportunities. American Journal of Public Health 2006;96(3):452-458.


Overview of system dynamics simulation modeling

Understanding Dynamic Complexity

From a Very Particular Distance

“{System dynamics studies problems} from ‘a very particular distance', not so close as to be concerned with the action of a single individual, but not so far away as to be ignorant of the internal pressures in the system.”

-- George Richardson

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 <http://www.sustainabilityinstitute.org/pubs/Leverage_Points.pdf>.

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.


Tools for policy analysis

Tools for Policy Analysis

Events

Time Series Models

Describe trends

  • Increasing:

  • Depth of causal theory

  • Degrees of uncertainty

  • Robustness for longer-term projection

  • Value for developing policy insights

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


How many triangles do you see

How Many Triangles Do You See?

Wickelgren I. How the brain 'sees' borders. Science 1992;256(5063):1520-1521.


Boundary critique

Boundary Critique

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 critique1

Boundary Critique

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


Health system dynamics

Public

Work

Society's Health

Response

Tertiary

General

Targeted

Primary

Secondary

Prevention

Protection

Protection

Prevention

Prevention

Demand for

response

Becoming safer

and healthier

Safer

Afflicted

Afflicted with

Vulnerable

Healthier

without

Complications

People

People

Developing

Becoming

Becoming

Complications

complications

vulnerable

afflicted

Dying from

complications

Adverse Living

Conditions

Health System Dynamics

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.

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.

Homer JB, Hirsch GB. System dynamics modeling for public health: background and opportunities. American Journal of Public Health 2006;96(3):452-458.


Understanding health as public work

Citizen Involvement

in Public Life

Public

Strength

-

Vulnerable and

Afflicted People

Fraction of Adversity,

Social Division

Vulnerability and Affliction

Borne by Disadvantaged

Sub-Groups (Inequity)

Understanding Health as Public Work

Public Work

-

Society's Health

Response

Tertiary

General

Targeted

Primary

Secondary

Prevention

Protection

Protection

Prevention

Prevention

Demand for

response

Becoming safer

and healthier

-

Safer

Afflicted

Afflicted with

Vulnerable

Healthier

without

Complications

People

People

Developing

Becoming

Becoming

Complications

complications

vulnerable

afflicted

Dying from

complications

Adverse Living

Conditions


Testing dynamic hypotheses

Public Work

Citizen Involvement

-

in Public Life

Public

Society's Health

Strength

Response

-

Tertiary

General

Targeted

Primary

Secondary

Prevention

Protection

Protection

Prevention

Prevention

Demand for

response

Becoming safer

and healthier

-

Safer

Afflicted

Afflicted with

Vulnerable

Healthier

without

Complications

People

People

Developing

Becoming

Becoming

Complications

complications

vulnerable

afflicted

Dying from

complications

Adverse Living

Conditions

Vulnerable and

Afflicted People

Fraction of Adversity,

Social Division

Vulnerability and Affliction

Borne by Disadvantaged

Sub-Groups (Inequity)

Testing Dynamic Hypotheses

-- How can we learn about the consequences of actions in a system of this kind?-- Could the behavior of this system be analyzed using conventional epidemoiological methods (e.g., logistic or multi-level regression)?


Learning in and about dynamic systems

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

Benefits of Simulation/Game-based Learning

  • Formal means of evaluating options

  • Experimental control of conditions

  • Compressed time

  • Complete, undistorted results

  • Actions can be stopped or reversed

  • Visceral engagement and learning

  • Tests for extreme conditions

  • Early warning of unintended effects

  • Opportunity to assemble stronger support

Dynamic 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.


System dynamics modeling supports navigational policy dialogues

Historical

Markov Forecasting Model

Data

Simulation Experiments

in

Action Labs

System Dynamics Modeling SupportsNavigational Policy Dialogues

Prevalence of Diagnosed Diabetes, US

40

Where?

30

What?

Million people

20

How?

  • Markov Model Constants

  • Incidence rates (%/yr)

  • Death rates (%/yr)

  • Diagnosed fractions

  • (Based on year 2000 data, per demographic segment)

10

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 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.


Simulations for learning in dynamic systems

Dynamic Hypothesis (Causal Structure)

Plausible Futures (Policy Experiments)

Deaths per Population

0.0035

0.003

Mixed

Base

0.0025

Upstream

0.002

Downstream

0.0015

1980

1990

2000

2010

2020

2030

2040

2050

Time (Year)

Blue: Base run; Red: Clinical mgmt up from 66% to 90%;

Green: Caloric intake down 4% (99 Kcal/day);

Black: Clin mgmt up to 80% & Intake down 2.5% (62 Kcal/day)

Simulations for Learning in Dynamic Systems

“All models are wrong. Some are useful.”

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 2006;96(3):505-514.

Sterman JD. All models are wrong: reflections on becoming a systems scientist. System Dynamics Review 2002;18(4):501-531.


Overview of system dynamics simulation modeling

What?

Where?

Prevalence of Obese Adults, United States

Why?

How?

Who?

2020

2010

Data Source: NHANES

“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.”

Simulation ExperimentsOpen a Third Branch of Science

“The complexity of our mental models vastly exceeds our ability to understand their implications without simulation."

-- John Sterman

-- 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. <http://www.pscs.umich.edu/pub/papers/AdvancingArtofSim.pdf>.

Sterman JD. Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston, MA: Irwin McGraw-Hill, 2000.


Questioning the character of public health work

SYSTEMS THINKING & MODELING (understanding change)

SOCIAL NAVIGATION

(governing movement)

  • What causes population health problems?

  • How are efforts to protect the public’s health organized?

  • How and when do health systems change (or resist change)?

Directing Change

  • Who does the work?

  • By what means?

  • According to whose values?

Charting Progress

  • How are conditions changing?

  • In which directions?

PUBLIC HEALTH(setting direction)

What are health leaderstrying to accomplish?

Questioning the Character of Public Health Work

PUBLIC HEALTH WORK

InnovativeHealth Ventures


Extras

EXTRAS


Potential users and uses of health sd simulation models

Potential Users and Uses of Health SD Simulation Models

  • Planners/Evaluators/Media: Chart Progress Toward Goals

    • Define a “status quo” future

    • Define alternative futures based on policy scenarios

    • Define types of information to be routinely collected

    • Track and interpret trajectories of change

    • Estimate how strong interventions must be to make a difference

  • Researchers: Better Measurement and New Knowledge

    • Integrate diverse data sources into a single analytic environment

    • Infer properties of unmeasured or poorly measured parameters

    • Analyze historical drivers of change

    • Locate areas of uncertainty to be addressed in new research

  • Policy Makers: Convene Multistakeholder Action Labs

    • Understand how a dynamically complex system functions

    • Discover short- and long-term consequences of alternative policies

    • Prepare for difficult patterns of change (e.g., worse-before-better)

    • Consider the cost effectiveness of alternative policies

    • Explore ways of combining and aligning policies for better results

    • Increase policy-makers’ motivation to act differently

  • Others…


Overview of system dynamics simulation modeling

Possible Roles for System Dynamics in Public Health

SD is especially well-suited for studying…

  • Individual diseases and risk factorsExamining momentum and setting justifiable goals

  • Life course dynamics Following health trajectories across life stages

  • Mutually reinforcing afflictions (syndemics)Exploring interactions among related afflictions, adverse living conditions, and the public’s capacity to address them both

  • Capacities of the health protection system Understanding how ambitious health ventures may be configured without overwhelming/depleting capacity--perhaps even strengthening it

  • Value trade-offs Analyzing phenomena like the imbalance of upstream-downstream effort, growth of the uninsured, rising costs, declining quality, entrenched inequalities

  • Organizational managementLinking balanced scorecards to a dynamic understanding of processes

  • Group model building and scenario planningBringing more structure, evidence, and insight to public dialogue and judgment


Steps for developing dynamic policy models

Learn About Policy Consequences

Test proposed policies, searching for ones that best govern change

Convert the Map Into a Simulation ModelFormally quantify the hypothesis using allavailable evidence

Create a Dynamic HypothesisIdentify and map the main causal forces that create the problem

Choose AmongPlausible FuturesDiscuss values and

consider trade-offs

Run Simulation ExperimentsCompare model’s behavior to expectations and/or data to build confidence in the model

Enact PoliciesBuild power and organize actors to establish chosen policies

Steps for Developing Dynamic Policy Models

Identify a Persistent ProblemGraph its behavior over time


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