healthbound a simulation model (and interactive game) for exploring u.s. health system change...
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HealthBound A Simulation Model (and Interactive Game) for
Exploring U.S. Health System Change
Workshop on Modeling for Public Health Practice and PolicyCoordinating Center for Health PromotionWestin Buckhead Hotel, Atlanta, Georgia
August 21, 2009
…In support of Healthiest Nation
Bobby Milstein, PhD, MPHCenters for Disease Control
Jack Homer, PhDHomer Consulting
Gary Hirsch, MSIndependent [email protected]
The name “HealthBound” is used courtesy of Associates & Wilson, Inc.
The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
Poised for Transformation…• America has a national health
shortage: we pay the most for health care, yet suffer comparatively poor health, especially among the disadvantaged
• High cost of poor health drives personal bankruptcy and business failure
• Over 75% think the current system needs fundamental change
• Analyses that focus narrowly on parts of the system, without examining connections, often miss the potential for policy resistance
Commission to Build a Healthier America. America is not getting good value for its health dollar. Princeton, NJ: Robert Wood Johnson Foundation 2008. Nolte E, McKee CM. Measuring the health of nations: updating an earlier analysis. Health Affairs 2008; 27(1):58-71.Blendon RJ, Altman DE, Deane C, Benson JM, Brodie M, Buhr T. Health care in the 2008 presidential primaries. NEJM 2008;358(4):414-422. White House. Americans speak on health reform: report on health care community discussions. Washington, DC: HealthReform.gov; March, 2009. <http://www.healthreform.gov/reports/hccd/>Altman DE, Levitt L. The sad history of health care cost containment as told in one chart. Health Affairs 2002;Web Exclusive:hlthaff.w2.83.
Exploratory Insight Goal SettingLeadership Development
Selected CDC Models of Health System DynamicsAcross a Continuum of Purposes
Centers for Disease Control and Prevention. Dynamic models. Syndemics Prevention Network, 2009. Available at http://www2.cdc.gov/syndemics/models.htm
Homer J, Hirsch G, Milstein B. Chronic illness in a complex health economy: the perils and promises of downstream and upstream reforms. System Dynamics Review 2007;23(2/3):313–343.
Causal diagrams with practical definitions of states, rates, and
interventions
Inflationary trends and self-sustaining tendencies of the
downstream healthcare industry
Diabetes Action Labs
Upstream-Downstream
Dynamics
Obesity Overthe Lifecourse
Fetal & Infant Health
Neighborhood Transformation
Game
National Health Economics & Reform
Syndemics
Local Context of Chronic Disease Prevention and
Control
HealthBoundGame
Important Structures
EmpiricalData
Creative policies for moving out of an entrenched and unhealthy state
Experiential learning to devise strategies, interpret dynamics, and weigh tradeoffs
• Cognitive and experiential learning for health leaders• Four simultaneous goals: save lives, improve health,
achieve health equity, and lower health care cost• Intervene without expense, risk, or delay• Not a prediction, but a way for diverse stakeholders
to explore how the health system can change
HealthBound
HealthBound is a Simplified Health System to be Explored Through Game-based Learning
Milstein B, Homer J, Hirsch G. The "HealthBound" policy simulation game: an adventure in US health reform. International System Dynamics Conference; Albuquerque, NM; July 26-30, 2009.
HealthBound Presents a Navigational ChallengeGet Out of a Deadly, Unhealthy, Inequitable, and Costly Predicament
Starting Values for Mortality, Morbidity, Inequity, Cost (~2003)
Death rate per thousand
Unhealthy days per capitaHealth inequity indexHealthcare spend per capita
8 6
0.2 7,000
4 3
0.1 5,000
0 0 0
3,000
-5 0 5 10 15 20 25
How far can you move
the system?
Deaths
Unhealthy Days
Health Inequity
Healthcare costs
Modeling for Learning and Acting
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.
Ulrich W. Critical heuristics of social planning: a new approach to practical philosophy. Bern: Haupt, 1983.
Planning & Evaluating Intervention Ventures
Dynamic Hypothesis (Causal Structure) Plausible Futures (Policy Experiments)
System Dynamics
The U.S. health system is dense
with diverse issues and opportunities
Healthier behaviorsHealthier behaviors
Adherence to care guidelines Adherence to
care guidelines
Insurance coverageInsurance coverage
Insurance overheadInsurance overhead
Socioeconomic disadvantage
Socioeconomic disadvantage
Provider capacityProvider capacity
Reimbursement rates
Reimbursement rates
Extent of care
Extent of care
Provider income
Provider income
Provider efficiencyProvider efficiency
Access to careAccess to care
ER useER use
Safer environments
Safer environments
Intervention capacity
Intervention capacity
Intervention Options
A Short Menu of Major Policy Proposals
Improve quality of care
Expand primary care supply
Simplify insurance
Change self pay fraction
Change reimbursement ratesExpand insurance coverage
Enable healthier behaviors
Build safer environments
Create pathways to advantage
Strengthen civic muscle
Improve primary care efficiency
Coordinate care
System Dynamics ModelingDynamic Modeling for Complex Policy Environments
Good at Capturing
• Differences between short- and long-term consequences, due to time delays and accumulations (e.g., prevalence, resources)
• Behavioral feedback (reactions by various actors)
• Nonlinear effects (e.g., “critical mass”, saturation)
• Differences in goals and values of various stakeholders
Origins • Jay Forrester, MIT, Industrial Dynamics, 1961
(“One of the seminal books of the last 20 years.”-- NY Times)
• Population health applications starting mid-1970s
Forrester JW. Industrial Dynamics. Cambridge, MA: MIT Press; 1961.
Sterman JD. Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston, MA: Irwin/McGraw-Hill; 2000.
Time Series Models
Describe trends
Multivariate Statistical 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
• Leverage for change
Increasing:
• Depth of causal theory
• Robustness for longer-term projection
• Value for developing policy insights
• Degrees of uncertainty
• Leverage for changeDynamic Simulation Models
Anticipate new trends, learn about policy
consequences, and set justifiable goals
Selected models for policy planning & evaluation
System Dynamics moves from behavior to structure by identifying accumulations and
feedback responses
Problem Situation
8
6
4
2
00 2 4 6 8 10 12 14 16 18 20
Seconds elapsed
Ou
nc
es
Water Level Over Time
System Behavior System Structure
System Dynamics Model Building & Use
• Map the forces that contribute to a problem
• Mathematically model those forces using the best information available
• Simulate “What if” scenarios of possible interventions
• Evaluate the model and test sensitivity to assess uncertainty and guide future research
• Convene “Action Labs” for model-supported planning by diverse stakeholders
1. Current water level = INTEG( Water flow , 0)2. Water flow = Water flow at full open * Faucet openness3. Water flow at full open = 1 ounce per second4. Faucet openness = MAX (0, MIN (Maximum faucet openness decision, Perceived water level gap / Water flow at full open ))5. Maximum faucet openness decision = 1 out of possible 16. Perceived water level gap = DELAY1I (Water level gap,Time to perceive water level gap, 0)7. Water level gap = Desired water level - Current water level8. Desired water level = 6 ounces9. Time to perceive water level gap = 1 secondFINAL TIME = 20 secondsINITIAL TIME = 0TIME STEP = 0.125 seconds
System Equations
8
6
4
2
00 2 4 6 8 10 12 14 16 18 20
Seconds elapsed
OuncesSystem Behavior
Target
Mapping, Modeling, and Testing
Problem Situation System Structure
Current waterlevel
Water flow
Desired water level
Water level gap
Perceived waterlevel gap
Time to perceivewater level gap
Faucet openness
Water flow atfull open
Maximum faucetopenness decision
System Model
Perc time Max open 1 1
1 0.50.5 1
What if…?
Determining a model’s value…and the need for further improvement
MODEL STRUCTURE
MODEL BEHAVIOR
ROBUSTNESS
• Adequate boundary to address relevant questions
• Equations allow for extreme possibilities
• Plausible behavior even under extreme conditions
• Policy findings insensitive to uncertainties
REALISM
• Recognizable structures (transparency)
• Plausible input values
• Replicate history
• Plausible future behavior
USEFULNESS• Adequate structure and policy levers for intended audiences
• Unexpected, insightful results
• Quick testing turnaround
Forrester JW, Senge PM. Tests for building confidence in system dynamics models. In: Legasto A, Forrester JW, Lyneis JM, editors. System Dynamics. New York, NY: North-Holland; 1980. p. 209-228.
Sterman JD. Business dynamics: systems thinking and modeling for a complex world. Boston, MA: Irwin McGraw-Hill, 2000.
“All models are wrong. Some are useful.” -- George Box
Simulating Health System DynamicsIntegrating prior findings and estimates• On costs, prevalence, risk factors, disparities,
utilization, insurance, quality of care, etc. (8 databases and professional literature)
Using sound methodology• Reflecting real-world accumulations, resource
constraints, delays, behavioral feedback
Simplifying as appropriate• Three states of health:
Healthy, Asymptomatic disorder, Disease/injury
• Two SES categories: Advantaged, Disadvantaged (allowing study of disparities and equity)
• Some complicating trends not included in simplified game (e.g., aging, technology, economy); an extended model incorporates such factors
Overview of Model Structure
Many of the elements shown here are stratified in the model by socioeconomic status (advantaged vs. disadvantaged), including those related to behavioral risks, environmental hazards, health status, type and locus of care received, primary care providers, access, insurance coverage, and cost sharing.
Concept Proxy Initial Values (~2003) Sources
Advantaged & Disadvantaged
Prevalence Household income (< or ≥ $25,000)
Advantaged = 78.5% Disadvantaged = 21.5%
Census
Some key concepts and measures
• CDC/SD study of cardiovascular risk in Austin/Travis County, TX. See Homer J, Milstein B, Wile K, et al. Modeling the local dynamics of cardiovascular health. Preventing Chronic Disease 2008;5(2).
Concept Proxy Initial Values (~2003) Sources
Advantaged & Disadvantaged
Prevalence Household income (< or ≥ $25,000)
Advantaged = 78.5% Disadvantaged = 21.5%
Census
Disease & InjuryPrevalence
Adults: 22 specific conditions Kids: 12 specific conditions
Overall = 38% D/A Ratio = 1.60 (= 53.6%/33.5%)
NHIS JAMA
Asymptomatic Disorder Prevalence
High blood pressure High cholesterol Pre-diabetes
Overall = 51.5% D/A Ratio = 1.15
NHANES JAMA
Mortality Deaths per 1,000 Overall = 7.5 D/A Ratio = 1.80
Vital Statistics AJPH
Morbidity Unhealthy days per month per capita
Overall = 5.26 D/A Ratio = 1.78
BRFSS
Health Inequity Fraction of unhealthy days attributable to disadvantage
Attributable fraction = 14.3% (calculated)
Health Insurance Lack of insurance coverage Overall = 15.6% D/A Ratio = 1.82
Census
Sufficiency of Primary Care Providers
Number of PCPs per 10,000 Overall = 8.5 per 10,000 D/A Ratio = 0.76
AMA Austin Study*
Unhealthy Behavior Prevalence
Smoking Physical inactivity
Overall = 34% D/A Ratio = 1.67
BRFSS JAMA Austin Study*
Unsafe Environment Prevalence
Survey response: “My neighborhood is not safe”
Overall = 26% D/A Ratio = 2.5
BRFSS Austin Study*
Some key concepts and measures
• CDC/SD study of cardiovascular risk in Austin/Travis County, TX. See Homer J, Milstein B, Wile K, et al. Modeling the local dynamics of cardiovascular health. Preventing Chronic Disease 2008;5(2).
Three Intervention ScenariosExpand Insurance CoverageReduces the uninsured fraction by 90%
Improve Quality of Care Raises provider adherence to guidelines for preventive, chronic and urgent care (eliminating non-adherence by 50%)Implementation Cost = $10k/MD/yr.; $500k/hospital/yr. Expand Primary Care SupplyRaises the number of primary care providers per capita to the Disadvantaged by 60% over 15 yearsImplementation Cost = $300k/additional MD Improve Primary Care EfficiencyRaises the fraction of primary care offices that run efficiently (eliminating inefficiency by 90%)Implementation Cost = $10k/MD/yr. Enable Healthier BehaviorsIncreases the fraction with healthier behavior (eliminating unhealthy behavior by 40% over 15 years)Implementation Cost = $2,000 per person helped Build Safer EnvironmentsIncreases the fraction living in safer environments(eliminating unsafe environments by 50% over 15 years)Implementation Cost = $500 per person helped
Capacity
Protection
Coverage & Quality
Simulated Results: Morbidity Average Unhealthy Days per Month
6
5
4
3
-5 0 5 10 15 20 25Year
Coverage + Quality + Capacity
Coverage + Quality + Capacity + Protect
Days per month (average over entire population)
Coverage + Quality
Simulated Results: Health Inequity Index Fraction of Morbidity Attributable to Disadvantage
Health Inequity Index (Fraction)
0.2
0.15
0.1
0.05
0
-5 0 5 10 15 20 25Year
Coverage + Quality
Coverage + Quality + Capacity
Coverage + Quality + Capacity + Protect
600
300
0
-300
-600
-5 0 5 10 15 20 25Year
Simulated Results: Total CostsHealth Care Costs + Intervention Program Costs
Dollars per capita per year
Coverage + Quality
Coverage + Quality + Capacity
Coverage + Quality + Capacity + Protect
8,000
6,000
4,000
2,000
0
-5 0 5 10 15 20 25Year
Simulated Results: Net Social BenefitNet Benefit = QALYs*$75k – Total Costs
Coverage + Quality
Coverage + Quality + Capacity
Coverage + Quality + Capacity + Protect
Dollars per capita per year
Some Policy InsightsValue Tradeoffs Come to the Foreground
• Expanded coverage and higher quality of care may improve health but, if done alone, would likely raise costs and worsen equity
• Additional primary care supply and greater efficiency could eliminate current shortages (esp. for the poor), reducing costs and improving equity
• Upstream health protection (behavioral + environmental remedies) could reduce costs, elevate health, and improve equity, with an initial investment and a time delay, but the benefits would grow over time
Milstein B, Homer J, Hirsch G. Are coverage and quality enough? A dynamic systems approach to health policy. AJPH (under review).
“Winning” Involves Not Just Posting High Scores, But Understanding How and Why You Got Them
Scorecard
ProgressReport
Results in Context
CompareRuns
HealthBound
HealthBound
HealthBound
HealthBound
Why a Game?To Build Foresight, Experience, and Motivation to Act
Experiential LearningExpert Recommendations
Who Has Been Playing? (N~500)
• Federal, state, local health officials
• Public health leadership institutes
• Citizen organizations
• Labor unions
• University faculty and students
• Think tanks
• Philanthropists
Who Has Been Playing? (N~500)
• Federal, state, local health officials
• Public health leadership institutes
• Citizen organizations
• Labor unions
• University faculty and students
• Think tanks
• Philanthropists
Development & Dissemination Plan
Engage stakeholders
Iterative modeling and game design (v4)
Documentation, publication, scientific vetting
Convene early adopters
• Enhance the game interface
• Enable open access
• Train facilitators
• Convene “signature” gaming events
• Support self-play and interaction
• Provide links to intervention resources
• Expand co-sponsors