odphp overview of system dynamics (milstein, v5 as delivered)

7/23/2019 ODPHP Overview of System Dynamics (Milstein, V5 as Delivered)

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Syndemics

Prevention Network

Overview of

System Dynamics Simulation Modeling

Systems Thinking and Modeling Workshop

Office of Disease Prevention and Health Promotion

Bethesda MDMay ! "##$

Bo%%y Milstein

Syndemics Prevention Network

Centers for Disease Control and Prevention

Atlanta, Georgia

[email protected]


2/21

Syndemics

Prevention Network

&esearch 'mperatives for Protecting Health

Gerberding JL. Protecting health: the new research imperative.

Journal of the American Medical Association 200!2"#$%%&:%#0'(%#0).

Typical Current State

Static view of problems tat arest!died in isolation

Proposed Future State

Dynamic systems and syndemicapproaces

()urrently application of comple*

systems theories or syndemic science

to health protection challengesis in its infancy+,

-- .ulie /er%erding


3/21

Syndemics

Prevention Network

0111 "### "##0 "##" "##2 "##3 "##4

System )hange 'nitiatives 5ncounter

6imitations of 6ogic Models and

)onventional Planning75valuation Methods

Dia%etes

8ction 6a%s9

ODPHP

Modelers

Meeting

:pstream-Downstream

'nvestments

O%esity Over

the 6ifecourse9

;etal < 'nfant

Health /oal-Setting

Milestones in the &ecent :se of

System Dynamics Modeling at )D)

8.PH

Systems'ssue

"##$

)D) 5valuation

;ramework

&ecommends

6ogic Models

SD 5merges as a

Promising Methodology

=eigh%orhood

8ssistance

/ame

Hypertension

Prevention

- Depth of causal theory

- Degrees of uncertainty

- &o%ustness for longer-term pro?ection

- @alue for developing

policy insightsDynamic Simulation Models

Anticipate new trends learn

about polic, conseuencesand set Custifiable goals

Tools for Policy 8nalysis


7/21

Syndemics

Prevention Network

;icelgren 7. 8ow the brain DseesD borders. 5cience %""2!2)$0)'&:%20(%2%.

How Many Triangles Do Aou See


8/21

Syndemics

Prevention Network

Blrich ;. =eflective practice in the civil societ,: the contribution of criticall, s,stemic thining.

=eflective Practice 2000!%$2&:2#>(2)9. http:44www.geocities.com4csh@[email protected]

Boundary )ritiCue


9/21

Syndemics

Prevention Network

Blrich ;. =eflective practice in the civil societ,: the contribution of criticall, s,stemic thining. =eflective

Practice 2000!%$2&:2#>(2)9. http:44www.geocities.com4csh@[email protected]

Boundary )ritiCue


10/21

Syndemics

Prevention Network

Milstein B Homer .+ The dynamics of upstream and downstream: why is

so hard for the health system to work upstream, and what can be done

about it?)D) ;utures Health Systems Workgroup 8tlanta /8 "##2+

TertiaryPreention

SecondaryPreention

PrimaryPreention

Tar!etedProtection

SocietyEs Health&esponse

Demand forresponse

Pu%licWork

SaferHealthierPeople 1ecoming

vulnerable

1ecoming saferand healthier

@ulnera%lePeople 1ecoming

afflicted

8fflictedwithout

)omplications +evelopingcomplications

8fflicted with)omplications

+,ing from

complications

Health System Dynamics

8dverse 6iving)onditions

"eneralProtection

Milstein 1 8omer J. /he d,namics of upstream and downstream: wh, is so hard for the health s,stem to wor

upstream and what can be done about itE


11/21

Syndemics

Prevention Network

:nderstanding Health as Pu%lic Work

SaferHealthier

People

@ulnera%le

People

8fflictedwithout

)omplications

8fflicted with

)omplications1ecomingvulnerable


1ecomingafflicted

+evelopingcomplications

+,ing fromcomplications

8dverse 6iving

)onditions

SocietyEs Health

&esponse

Demand forresponse

"eneralProtection

Tar!etedProtection

PrimaryPreention

SecondaryPreention

TertiaryPreention

(

Pu%lic Work

(

Fulnerable andAfflicted People

raction of Adversit,

Fulnerabilit, and Affliction

1orne b, +isadvantaged

5ub(Groups $7neuit,&

Pu%lic

Strength

(

Citi#en $nolementin Public %ife

SocialDiision


12/21

Syndemics

Prevention Network

Testing Dynamic Hypotheses

-- How can we learn a%out the conseCuences of actions in a system of this kind

-- )ould the %ehavior of this system %e analyFed using conventional epidemoiological methods

Ge+g+ logistic or multi-level regression

SaferHealthierPeople

@ulnera%lePeople

8fflictedwithout

)omplications

8fflicted with)omplications1ecoming

vulnerable


1ecomingafflicted

+evelopingcomplications

+,ing fromcomplications

8dverse 6iving)onditions

SocietyEs Health&esponse

Demand forresponse

"eneralProtection

Tar!etedProtection

PrimaryPreention

SecondaryPreention

TertiaryPreention

(

Pu%lic Work(

Fulnerable andAfflicted People

raction of Adversit,Fulnerabilit, and Affliction1orne b, +isadvantaged

5ub(Groups $7neuit,&

Pu%licStrength

(

Citi#en $nolementin Public %ife

Social

Diision


13/21

Syndemics

Prevention Network

6earning 'n and 8%out Dynamic Systems

Benefits of Simulation7/ame-%ased 6earning

- ormal means of evaluating options

- 6perimental control of conditions

-


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SyndemicsPrevention Network

System Dynamics Modeling Supports

=avigational Policy Dialogues

Prevalence of Diagnosed Dia%etes :S

0

%0

20

'0

#0

%"90 %""0 2000 20%0 2020 20'0 20#0 200

Millionpeople

8istorical

+ata

Marov Model


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Simulations for 6earning in Dynamic Systems

Morecroft J+; 5terman J. Modeling for learning organiKations. Portland H=: Productivit, Press 2000.

5terman J+. 1usiness d,namics: s,stems thining and modeling for a comple6 world. 1oston MA: 7rwin McGraw(8ill 2000.

5terman J+. Learning from evidence in a comple6 world. American Journal of Public 8ealth 200)!")$'&:0(%#.

5terman J+. All models are wrong: reflections on becoming a s,stems scientist. 5,stem +,namics =eview 2002!%9$#&:0%('%.

Multi-stakeholder

Dialogue

Dynamic Hypothesis G)ausal Structure Plausi%le ;utures GPolicy 5*periments

Deaths per Population

0.00'

0.00'

0.002

0.002

0.00%%"90 %""0 2000 20%0 2020 20'0 20#0 200

/ime $ear&

Blue> Base run &ed> )linical mgmt up from $$J to 1#J

/reen> )aloric intake down 3J G11 Kcal7dayBlack> )lin mgmt up to !#J < 'ntake down "+4J G$" Kcal7day

1ase

+own

stream

Bpstream

Mi6ed

$All models are wrong. Some are !sef!l.)


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5imulation is a third wa, of doing science.

Lie deduction it starts with a set of e6plicit

assumptions. 1ut unlie deduction it does not

prove theorems. 7nstead a simulation generates

data that can be anal,Ked inductivel,. Bnlie t,pical

induction however the simulated data comes from

a rigorousl, specified set of rules rather than direct

measurement of the real world. ;hile induction can

be used to find patterns in data and deduction can

be used to find conseuences of assumptionssimulation modeling can be used as an aid to

intuition.N

-- &o%ert 8*elrod

A6elrod =. Advancing the art of simulation in the social sciences. 7n: . p. 2%(#0. ?http:44www.pscs.umich.edu4pub4papers4AdvancingArtof5im.pdf.

5terman J+. !siness Dynamics- Systems 4inking and 5odeling for a Comple;orld. 1oston MA: 7rwin McGraw(8ill 2000.

Simulation 5*periments

Open a Third Branch of Science

$4e compleity of o!r mental models vastly eceeds o!r ability

to !nderstand teir implications wito!t sim!lation.2

33 *on Sterman

How?

Where?

Prevalence of O%ese 8dults :nited States

Why?

+ata 5ource: 38A35"#"#"#0#

Who?

What?


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Luestioning the )haracter of Pu%lic Health Work

P:B6') H586TH WO&K

'nnovative

Health

@entures

SAST5MS

TH'=K'=/ < MOD56'=/Gunderstanding change

-What causes population

health pro%lems

-How are efforts to protect

the pu%lics health organiFed

-How and when do health

systems change Gor resistchange

P:B6') H586TH

Gsetting direction

What are health leaders

trying to accomplish

SO)'86 =8@'/8T'O=Ggoverning movement

Directing )hange

)harting Progress

-Who does the work

-By what means

-8ccording to whose values

-How are conditions changing

-'n which directions


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Potential :sers and :ses of

Health SD Simulation Models

- Planners75valuators7Media> )hart Progress Toward /oals

O +efine a status uoN futureO +efine alternative futures based on polic, scenariosO +efine t,pes of information to be routinel, collectedO /rac and interpret traCectories of changeO stimate how strong interventions must be to mae a difference

- &esearchers> Better Measurement and =ew Knowledge

O 7ntegrate diverse data sources into a single anal,tic environmentO 7nfer properties of unmeasured or poorl, measured parametersO Anal,Ke historical drivers of changeO Locate areas of uncertaint, to be addressed in new research

- Policy Makers> )onvene Multistakeholder 8ction 6a%sO Bnderstand how a d,namicall, comple6 s,stem functionsO +iscover short( and long(term conseuences of alternative policiesO Prepare for difficult patterns of change $e.g. worse(before(better&O


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Possi%le &oles for System Dynamics in Pu%lic Health

SD is especially well&suited for studyin!'

- 'ndividual diseases and risk factors

6amining moment!m and setting 7!stifiable goals

- 6ife course dynamics

8ollowing ealt tra7ectories across life stages

- Mutually reinforcing afflictions Gsyndemics

6ploring interactions among related afflictions, adverse living conditions,

and te p!blic9s capacity to address tem bot- )apacities of the health protection system

:nderstanding ow ambitio!s ealt vent!res may be config!red wito!t

overwelming;depleting capacity33peraps even strengtening it

- @alue trade-offs

Analyinking balanced scorecards to a dynamic !nderstanding of processes

- /roup model %uilding and scenario planning

ringing more str!ct!re, evidence, and insigt to p!blic dialog!e and 7!dgment


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Steps for Developing Dynamic Policy Models

5nact Policies1uild power and

organiKe actors to

establish chosen policies

5nact Policies1uild power and

organiKe actors to

establish chosen policies

)hoose 8mongPlausi%le ;utures

+iscuss values and

consider trade(offs

)hoose 8mongPlausi%le ;utures

+iscuss values and

consider trade(offs

6earn 8%out Policy

)onseCuences

/est proposed policies

searching for ones that best

govern change

6earn 8%out Policy

)onseCuences

/est proposed policiessearching for ones that best

govern change

&un Simulation

5*periments

odphp overview of system dynamics (milstein, v5 as delivered)

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