Syndemics Prevention Network Prevention Impacts Simulation Model (PRISM) Core Contributors System Dynamics Modelers Jack Homer Kris Wile Economists Justin

Syndemics

Prevention Network

Prevention Impacts Simulation Model (PRISM)Core Contributors

System Dynamics Modelers• Jack Homer• Kris Wile

Economists• Justin Trogdon• Amanda Honeycutt

Project Coordinators• Bobby Milstein• Diane Orenstein

CDC partnered with the Austin (Travis County), Texas, Dept. of Health and Human Services. The model is calibrated to represent the overall US, but is informed by the experience and data

of the Austin team, which has been supported by the CDC’s “STEPS” program since 2004.`

CDC partnered with the Austin (Travis County), Texas, Dept. of Health and Human Services. The model is calibrated to represent the overall US, but is informed by the experience and data

of the Austin team, which has been supported by the CDC’s “STEPS” program since 2004.`

CDC & NIH Subject Matter ExpertsBishwa Adhikari, Nicole Blair, Kristen Betts, Peter Briss, David Buchner, Susan Carlson, Michele Casper, Tom Chapel, Janet Collins, Lawton Cooper, Michael Dalmat, Alyssa Easton, Joyce Essien, Roseanne Farris, Larry Fine, Janet Fulton, Deb Galuska, Kathy Gallagher, Judy Hannon, Jan Jernigan, Darwin Labarthe, Deb Lubar, Patty Mabry, Ann Malarcher, Michele Maynard, Marilyn Metzler, Rob Merritt, Latetia Moore, Barbara Park, Terry Pechacek, Catherine Rasberry, Michael Schooley, Nancy Williams, Nancy Watkins, Howell Wechsler

External Subject Matter ExpertsCynthia Batcher, Margaret Casey, Phil Huang, Kristen Lich, Karina Loyo, David Matchar, Ella Pugo, John Robitscher, Rick Schwertfeger, Adolpho Valadez

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Prevention Impacts Simulation Model (PRISM)• Represents multiple interacting risks and interventions for heart

disease, stroke, and related chronic diseases: medical, behavioral, social, environmental

• Begun in 2007 (now version 2i) and it remains a work-in-progress

• Engaged subject matter experts from 12 organizations (N~30), and 100s of policy officials, including a deep collaboration with local leaders in Austin, Texas

• Integrates best available information in a single testable model to support prospective planning and evaluation

• Explores the likely effects of “local interventions” (i.e., changes in local options/exposures/services that affect behavior and/or health status)

– To what extent might adverse events and costs be reduced?

– How can policymakers balance interventions for best effect with limited resources?

References: Homer J, Milstein B, Wile K, Trogdon J, Huang P, Labarthe D, Orenstein D. Simulating and evaluating local interventions to improve cardiovascular health. Preventing Chronic Disease, 2009 (in press).

Homer J, Milstein B, Wile K, Pratibhu P, Farris R, Orenstein D. Modeling the local dynamics of cardiovascular health: risk factors, context, and capacity. Preventing Chronic Disease 2008;5(2). Available at <http://www.cdc.gov/pcd/issues/2008/apr/07_0230.htm

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Tobacco

Air Pollution

Stress

Healthy Food

Sodium

Trans fat

PhysicalActivity

WeightLoss

MentalHealthServices

PrimaryCare

Emergency & Rehab Care

BloodPressure

Cholesterol

ObesityHeart Disease & Stroke

Cancer

Health CareCost

Diabetes

The Popular (and Professional) View of Chronic Disease Challenges is Largely One Headline after Another

Alcohol

Sleep Arthritis

JunkFood

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PRISM Situates Multiple Medical, Behavioral, and Environmental Factors into a Single Set of Causal Pathways

Cardiovascularevents

Air pollutionexposure(PM 2.5)

Use of qualitypreventive care

SmokingObesity

-Hypertension-High cholesterol

-Diabetes

Uncontrolledchronic disorders

Secondhandsmoke

Heart-unhealthy diet

Physicalinactivity

Distress

Excesscalorie diet

CVD deaths,disability,and costs

Excesssodium diet

Chronic Disorders

Trans fatconsumption

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PRISM Situates Multiple Medical, Behavioral, and Environmental Factors into a Single Set of Causal Pathways




SmokingObesity


-Diabetes


Secondhandsmoke


Physicalinactivity

Distress

Excesscalorie diet


Excesssodium diet

Chronic Disorders

Other deaths and costsattributable to risk factors,

and costs of risk factormanagement

Total consequencecosts


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Weight lossservices for obese

JUNK FOODTax, restrict sales/mktg,

counter-marketing

Sodium in food

Trans fatIn food

HEART-HEALTHYFOOD

Access, promotionCardiovascular

events



SmokingObesity


-Diabetes


Secondhandsmoke


Physicalinactivity

PHYSICAL ACTIVITYAccess, promotion,

social support,school recs, childcare recs

Distress

Help servicesfor distress

Excesscalorie diet


Excesssodium diet

Reduce airpollution

Chronic Disorders




Quality of acuteand rehab care

Quality and use ofpreventive care


Local Context for TobaccoLocal Context for DietLocal Context for Physical ActivityLocal Context for Air PollutionLocal Context for Health Care ServicesLocal Context for Weight Loss ServicesLocal Context for Mental Health Services

PRISM Also Includes Frontiers for Social Action

Tax, restrict sales/mktg,counter-marketing,

quit services

TOBACCOBan smoking in

public places

Primary Information Sources• Census

– Population, deaths, births, net immigration

• American Heart Association & NIH statistical reports

– Cardiovascular events, deaths, and prevalence

• National Health and Nutrition Examination Survey (NHANES)

– Risk factor prevalence by age and sex

– Diagnosis and control of hypertension, high cholesterol, and diabetes

• Medical Examination Panel (MEPS), National Health Interview (NHIS), Behavioral Risk Factor Surveillance System (BRFSS), Youth Risk Behavior Survey (YRBS)

– Medical and productivity costs attributable to risk factors

– Prevalence of distress in non-CVD and post-CVD populations

– Primary care utilization

– Extent of physical activity

• Research literature

– CVD risk calculator (Framingham)

– Relative risks from secondhand smoke, air pollution, obesity, poor diet, inactivity, distress

– Quality of diet (USDA Healthy Eating Index)

– Medical and productivity costs of cardiovascular events

– Effect sizes of behavioral interventions

• Expert judgment

– Effect sizes of behavioral interventions

Uncertainties are assessed through sensitivity testing

Uncertainties are assessed through sensitivity testing

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Mapping Information SourcesPhysical Activity Pathway







Ban smoking inpublic places

SmokingObesity


-Diabetes


Secondhandsmoke

Junk food options (N=3):Tax, restrict sales/mktg,

counter-market

Physical activity options (N=5):Access, promotion, social

support, school requirements,childcare requirements


Physicalinactivity

Distress


Sodium in food

Trans fat infood

Excesscalorie diet


Excesssodium diet

Reduce airpollution

Tobacco options (N=4):Tax, restrict sales/mktg,

counter-market, quitservices

Chronic Disorders





Heart-healthy foodoptions (N=2):

Access, promotion

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Prevention Network









SmokingObesity


-Diabetes


Secondhandsmoke


counter-market




Physicalinactivity

Distress


Sodium in food

Trans fat infood

Excesscalorie diet


Excesssodium diet

Reduce airpollution



Chronic Disorders






Access, promotion

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Prevention Network








SmokingObesity


-Diabetes


Secondhandsmoke


counter-market




Physicalinactivity

Distress


Sodium in food

Trans fat infood

Excesscalorie diet


Excesssodium diet

Reduce airpollution



Chronic Disorders






Access, promotion


Physical Inactivity Prevalence52% - 65% (by age)

• NHANES, BRFSS, & YRBS • Troiano RP, et al. Med Sci Sports Ex 2008;

40(1):181-188.

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SmokingObesity


-Diabetes


Secondhandsmoke


counter-market




Physicalinactivity

Distress


Sodium in food

Trans fat infood

Excesscalorie diet


Excesssodium diet

Reduce airpollution



Chronic Disorders






Access, promotion


Effective Interventions Increase PA by 40-55%

(by age and strategy)

• Kahn EB, et al. Am J Prev Med 2002; 22:S73-102.

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SmokingObesity


-Diabetes


Secondhandsmoke


counter-market




Physicalinactivity

Distress


Sodium in food

Trans fat infood

Excesscalorie diet


Excesssodium diet

Reduce airpollution



Chronic Disorders






Access, promotion


RR for obesity onset = 2.6

• Haapanen N, et al. Intl J Obesity 1997: 21:288-296

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SmokingObesity


-Diabetes


Secondhandsmoke


counter-market




Physicalinactivity

Distress


Sodium in food

Trans fat infood

Excesscalorie diet


Excesssodium diet

Reduce airpollution



Chronic Disorders






Access, promotion


RR for distress = 1.3

• Netz Y, Wu M-J, et al. Psyh Aging 2005; 20(2):272-284. .

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SmokingObesity


-Diabetes


Secondhandsmoke


counter-market




Physicalinactivity

Distress


Sodium in food

Trans fat infood

Excesscalorie diet


Excesssodium diet

Reduce airpollution



Chronic Disorders






Access, promotion


RR of inactivity if distressed: 1.6

• Whooley MA, et al. JAMA 2008; 300(20):2379-2388.

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Prevention Network








SmokingObesity


-Diabetes


Secondhandsmoke


counter-market




Physicalinactivity

Distress


Sodium in food

Trans fat infood

Excesscalorie diet


Excesssodium diet

Reduce airpollution



Chronic Disorders






Access, promotion


RR for High BP = 1.15RR for High Cholesterol = 1.4

RR for Diabetes = 1.4

• Ann Med 1991;23(3):319–327.• Intl J Epidemiology 1997; 26(4):739-747.

• Canadian Med Assoc J 2000;163(11):1435-1440.• Lancet 1991; 339:778-783.

• Arch Intern Med 2001; 161:1542-1548.

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Prevention Network








SmokingObesity


-Diabetes


Secondhandsmoke


counter-market




Physicalinactivity

Distress


Sodium in food

Trans fat infood

Excesscalorie diet


Excesssodium diet

Reduce airpollution



Chronic Disorders






Access, promotion


Modification of theFramingham Risk Calculator

• Ex Rev Pharm Out Res 2006;6(4):417-24.• Am Heart J 1991;121(1 Pt 2):293-8.

• Am Heart J 2007;153(5):722-31, 31 e1-8.• JAMA 2001;286(2):180-7.

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Base Case & Illustrative Intervention Scenarios

Base Case (a simple scenario for comparison)

• Assume no further changes in the contextual factors that affect risk factor prevalences

• Any changes in prevalences after 2004 are due to “inflow/outflow” adjustment process and population aging

• Result: Past trends level off after 2004, after which results reflect only slow adjustments in risk factors

– Increasing obesity, high BP, and diabetes

– Decreasing smoking

– Increases in risk factors and population aging lead to eventual rebound in attributable deaths

Example Intervention Scenarios (max plausible effects, sustained)

• Four clusters of interventions layered to show their partial contribution and combined effects

• Services (health care, weight loss, smoking quit, distress)+ Diet & Physical Activity+ Tobacco + Air Pollution & Sodium & Trans fat

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Illustrative Intervention Scenarios: Maximum Plausible StrengthIndividual Services + Diet & PA + Tobacco + Air Pollution & Sodium & Trans

fat

Work in Progress, Please do no cite or distribute.

Smoking Prevalence (Adults) Obesity Prevalence (Adults)

Cardiovascular Events per 1000(CHD, Stroke, CHF, PAD)

Deaths from All Risk Factors per 1,000

0.4

0.3

0.2

0.1

0

1990 2000 2010 2020 2030 2040

0.4

0.3

0.2

0.1

0

1990 2000 2010 2020 2030 2040

30

22.5

15

7.5

0

1990 2000 2010 2020 2030 2040

8

6

4

2

0

1990 2000 2010 2020 2030 2040

Draft Model Output Draft Model Output


**if all risk factors=0**

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Illustrative Intervention Scenarios: Maximum Plausible StrengthIndividual Services + Diet & PA + Tobacco + Air Pollution & Sodium & Trans

fat

Work in Progress, Please do no cite or distribute.

Years of Life Lost from Attributable Deaths

Consequence Costs per Capita(medical costs + productivity)

30 M

22.5 M

15 M

7.5 M

0

1990 2000 2010 2020 2030 2040

6,000

4,500

3,000

1,500

01990 2000 2010 2020 2030 2040

**if all risk factors=0**


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Example of Sensitivity TestingEstimated impacts of a 15-component intervention,

with uncertainty ranges

1990 2000 2010 2020 2030 2040

Total Consequence Costs per capita (2005 dollars per year)

3,000

2,000

0

1,000

Combined 15 interventionswith range of uncertainty

Base Case

Costs if all risk factors = 0

1990 2000 2010 2020 2030 2040

Deaths from CVD per 1000

4

2

0

Combined 15 interventionswith range of uncertainty

Base Case

Deaths if all risk factors = 0

Homer J, Milstein B, Wile K, Trogdon J, Huang P, Labarthe D, Orenstein D. Simulating and evaluating local interventions to improve cardiovascular health. Preventing Chronic Disease, 2009 (in press).

Model Output (v2008)Model Output (v2008)

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How are Practitioners Using PRISM?

A Few Local Versions

• Re-calibrate to areas with different demographics, histories, and current conditions

Planning• Engage a wider circle of stakeholders

• Situate silos within a system

• Prioritize interventions (given tradeoffs/synergies)

• Set plausible short- and long-term goals

Evaluating

• Trace intervention effects through direct, secondary, and summary measures

• Extend the time horizon for evaluative inquiry

• Establish novel referents for comparison (self-referential counter-factuals)

Users (~500)Customized Versions

• East Austin, Texas

• Mississippi Delta

• New Zealand Ministry of Health

• U.S. economic stimulus health initiative

Nat’l & State Stakeholders

• CDC Staff

• National Association of Chronic Disease Directors

• Directors of Public Health Education

• National Institutes of Health (NHLBI, OBSSR)

Users (~500)Customized Versions

• East Austin, Texas

• Mississippi Delta

• New Zealand Ministry of Health

• U.S. economic stimulus health initiative

Nat’l & State Stakeholders

• CDC Staff

• National Association of Chronic Disease Directors

• Directors of Public Health Education

• National Institutes of Health (NHLBI, OBSSR)

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Conversations Around the Model

Other health

priorities

Available information

Health inequities

Local interventionopportunities and costs

Communitythemes and strengths

Political willStakeholder

relationships

• What’s in the model does not define what’s in the room

• Simulations intentionally raise questions to spark broader thinking and judgment

• Narrower boundaries tend to be more empirically grounded

• Wider boundaries may legitimize “invisible” processes

• Boundary judgments follow from the intended purpose and users

SYSTEMDYNAMICS MODEL

STRATEGICPRIORITIES



Quality of acute andrehab care for

cardiovascular events


Use of weightloss services

by obese

Use of help servicesfor distress

Bans on smokingin public places

SmokingObesity


-Diabetes


Secondhandsmoke

Junk foodinterventions

(N=4)

Physical activityinterventions

(N=6)


Physicalinactivity Distress

Efforts to promoteprovision and use of

quality preventive care

Sodiumreduction

Trans fatreduction

Excesscalorie diet

Fruit &vegetable

interventions(N=3)


Excesssodium diet

Air pollutionreduction

Tobaccointerventions

(N=4)

Chronic Disorders




Researchagenda

Interactive ModelingBuilds Foresight, Experience, and Motivation to Act

Experiential Learning“Wayfinding”

Expert Recommendations

http://www.cdc.gov/index.htm

Documents

Syndemics Prevention Network Prevention Impacts Simulation Model (PRISM) Core Contributors System Dynamics Modelers Jack Homer Kris Wile Economists Justin