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The Dynamics of Upstream and Downstream

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The Dynamics of Upstream and Downstream Why is it so hard for the public health system to work upstream, and what can be done about it? Bobby Milstein – PowerPoint PPT presentation

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Title: The Dynamics of Upstream and Downstream


1
The Dynamics of Upstream and Downstream
Why is it so hard for the public health system to
work upstream, and what can be done about it?
Bobby Milstein Syndemics Prevention Network,
CDC Bmilstein_at_cdc.gov http//www.cdc.gov/syndemics

Jack Homer Homer Consulting Jhomer_at_comcast.net htt
p//www.homerconsulting.com
  • CDC Futures Health Systems Workgroup
  • December 3, 2003

2
Public Health Effort Across the Chain
Upstream Prevention and Protection --------------
--------------------- Total ? 3
Downstream Care and Management ------------------
-------------- Total ? 97
3
The Simple Physics of Upstream and Downstream
4
Why focus on affliction?
5
Focusing on disease prevention and control has
led to major achievements
Actual and Expected Death Rates for Coronary
Heart Disease, 19501998
700
Rate if trend continued
600
500
Peak Rate
400
Age-adjusted Death Rate per 100,000 Population
300
200
Actual Rate
100
50
1950
1960
1970
1980
1990
1995
1955
1965
1975
1985
Year
Marks JS. The burden of chronic disease and the
future of public health. CDC Information Sharing
Meeting. Atlanta, GA National Center for Chronic
Disease Prevention and Health Promotion 2003.
6
But the pictures look different when we examine
peoples overall state of health or affliction
14 increase
Source Centers for Disease Control and
Prevention. Health-related quality of life
prevalence data. National Center for Chronic
Disease Prevention and Health Promotion, 2003.
Accessed March 21 at lthttp//apps.nccd.cdc.gov/HRQ
OL/gt.
7
Why Do We Do Public Health Work?What is the
System Organized to Do?
CDC Vision Mission Healthy people, in a
healthy world, through prevention To promote
health and quality of life by preventing and
controlling disease, injury, and disability
Institute of Medicine The purpose of public
health is to fulfill societys interest in
assuring the conditions in which people can be
healthy
How we reconcile these two frames of reference
will shape the possibilities for what we can
accomplish in leading health system change.A
systems approach understands that both
perspectives exist in a dynamic relationship with
each other.
8
When we attribute behavior to people rather than
system structure the focus of management becomes
scapegoating and blame rather than the design of
organizations in which ordinary people can
achieve extraordinary results.
Why Has it Been So Hardto Correct the Imbalance?
-- John Sterman
Sterman J. System dynamics modeling tools for
learning in a complex world. California
Management Review 200143(4)8-25.
9
What Kinds of Work Must the Public Health System
Perform?
more inter-organizationally complex, slower rate
of improvement
organizationally complex, faster rate of
improvement
FOR SELF INTEREST
FOR OTHERS IN NEED
10
Let me assure you, we will survive any crisis
that involves funding, political support,
popularity, or cyclic trends, but we can't
survive the internal crisis, if we become
provincial, focus totally on the short term, or
if we lose our philosophy of social justice.
-- Bill Foege
Foege WH. Public health moving from debt to
legacy. American Journal of Public Health
198777(10)1276-8.
11
Beyond the Obvious Morality of it, Why Place So
Much Emphasis on Social Justice?
12
What Drives Change Across the Chain?
13
Upstream and Downstream Work
14
Upstream and Downstream Work
15
Upstream and Downstream Work
16
Upstream and Downstream Work
17
Upstream and Downstream Work
18
Upstream and Downstream Work
19
Upstream and Downstream Work
20
Upstream and Downstream Work
Downstream lock-in Delay in upstream effort
guarantees continued growth in affliction, need
for downstream effort and, hence, dependency on
professionals, which further undermines upstream
effort, as does mounting social disparity.
21
Dynamic Models Let Us Search for Policies That
Leverage Public Work
  • Computer technology makes it feasible to put
    system maps in motion, to learn how health
    patterns change under different conditions, and
    to seriously evaluate or rehearse the long-term
    effects of response options they provide added
    foresight
  • Such models open new avenues for domestic and
    global problem solving, systems research,
    knowledge integration, game-based learning, as
    well as richer dialogue among stakeholders

Prototype of a health system simulation model
22
CDCs Strength Lies in Leading Public Work
  • CDCs credibility and effectiveness rest on more
    than scientific excellence
  • The agencys reputation also stems from the
    widespread perception that CDC is an organization
    of talented people working to protect us all a
    peoples institution
  • If CDC comes to be viewed primarily as a provider
    of products/services to customers in need, it
    could erode leadership potential for upstream
    action

23
SummaryWhy is it So Hard to Work Across the
Whole System?
  • Initial Observations
  • Upstream work requires more public concern, which
    is less a reaction to the prevalence of disease
    as to the spread of vulnerability and affliction
    that over many years threaten everybody (think of
    economic decline, inadequate education, unsafe
    housing, sprawl, racism, environmental decay,
    etc.)
  • Long before upstream threats become widely
    apparent, money and other resources have focused
    downstream (where professional expertise and the
    weight of scientific evidence lie)
  • Because of their role as providers of downstream
    services, health professionals do not respond to
    vulnerability and social disparity FOR ITS OWN
    SAKE, in the WAY that ordinary citizens often do
  • Upstream health action involves broad-based
    organizing it is politicalbut non-partisanand
    cannot be done by professionals alone.

24
"The people's health...is a concern of the people
themselves. They must want health. They must
struggle for it and plan for it. Physicians are
merely experts whose advice is sought in drawing
up plans and whose cooperation is needed in
carrying them out. No plan, however well devised
and well intentioned, will succeed if it is
imposed on the people. The war against disease
and for health cannot be fought by physicians
alone. It is a people's war in which the entire
population must be mobilized permanently."
Sigerist, HE. Health. Journal of Public Health
Policy., 1996 17(2) 204-234.
25
Prototype of a Dynamic Simulation Model
26
Steps For Putting the Map in Motion
  • Start with an explicit dynamic hypothesis (i.e.,
    what causal forces are at work?)
  • Convert that hypothesis into a formal computer
    model (i.e., by writing a system of differential
    equations and calibrating it based on all
    available data areas of uncertainty are noted
    and become the focus for sensitivity analysis)
  • Use the computer model to conduct controlled
    simulation studies, with the goal of learning how
    the system behaves and how to govern its
    evolution over time
  • Iteratively repeat the process, creating better
    hypotheses, better models, and better policy
    insight

27
Building a Dynamic Hypothesis
Note for this initial model, the system being
modeled includes only a subset of the dynamics
that were identified in the conceptual map.
28
Could the behavior of this system be modeled
using conventional epidemoiological methods
(e.g., logistic or multi-level regression)?
29
Writing Differential Equations
Active Equations   (01) Afflicted Afflicted
without Complications Afflicted with
Complications (02) Afflicted with
Complications INTEG( Affliction progression -
Death from Complications , 0) (03) Afflicted
without Complications INTEG( Affliction
incidence - Affliction progression , 0)
(04) Affliction incidence Vulnerable Popn
Affliction incidence rate baseline Primary
prevention effect on incidence
(05) Affliction incidence rate baseline
0.05 (06) Affliction progression Afflicted
without Complications Affliction progression
rate baseline Secondary prevention effect on
progression (07) Affliction progression rate
baseline 0.1 (08) Complicated afflicted
percent of popn 100 Afflicted with
Complications / Total popn (09) Complicated
afflicted percent required to elicit maximum PH
response 20 (10) Complicated percent of
afflicted 100 ZIDZ ( Afflicted with
Complications , Afflicted ) (11) Complications
death rate baseline 0.1
30
Writing Differential Equations
(12) Death from Complications Afflicted with
Complications Complications death rate baseline
Tertiary prevention effect on complications
(13) General Popn INTEG( Net increase in
genl popn Vulnerability reduction -
Vulnerability onset , Total popn initial ( 100
- Vulnerable percent initial ) / 100)
(14) General protection effect from max PHR
0.5 (15) General protection effect on
vulnerability onset 1 - ( 1 - General
protection effect from max PHR ) Public health
response / 100 (16) Net increase in genl popn
Death from Complications ( 1 - Vulnerable
percent of nonafflicted / 100) (17) Net
increase in vulnerable popn Death from
Complications Vulnerable percent of
nonafflicted / 100 (18) Nonafflicted General
Popn Vulnerable Popn (19) Primary prevention
effect from max PHR 0.5 (20) Primary
prevention effect on incidence 1 - ( 1 -
Primary prevention effect from max PHR ) Public
health response / 100 (21) Public health
response DELAY1I ( 100 MIN ( 1, Complicated
afflicted percent of popn / Complicated
afflicted percent required to elicit maximum PH
response ) , Time for public health to respond to
affliction prevalence , 0)
31
Writing Differential Equations
(22) Secondary prevention effect from max PHR
0.5 (23) Secondary prevention effect on
progression 1 - ( 1 - Secondary prevention
effect from max PHR ) Public health response /
100 (24) Targeted protection effect from max
PHR 2 (25) Targeted protection effect on
vulnerability reduction 1 ( Targeted
protection effect from max PHR - 1) Public
health response / 100 (26) Tertiary prevention
effect from max PHR 0.5 (27) Tertiary
prevention effect on complications 1 - ( 1 -
Tertiary prevention effect from max PHR )
Public health response / 100 (28) Time for
public health to respond to affliction prevalence
2 (29) Total popn Nonafflicted Afflicted
(30) Total popn initial 100000 (31) Vulnera
bility onset General Popn Vulnerability onset
rate baseline General protection effect on
vulnerability onset (32) Vulnerability onset
rate baseline 0.05
32
Writing Differential Equations
(33) Vulnerability reduction Vulnerable Popn
Vulnerability reduction rate baseline
Targeted protection effect on vulnerability
reduction (34) Vulnerability reduction rate
baseline 0.07 (35) Vulnerable percent initial
10 (36) Vulnerable percent of nonafflicted
100 Vulnerable Popn / Nonafflicted
(37) Vulnerable Popn INTEG( Net increase in
vulnerable popn Vulnerability onset -
Affliction incidence - Vulnerability reduction
, Total popn initial Vulnerable percent initial
/ 100)
33
Developing Assumptions For Response Scenarios
Parameter Assumption
Population Characteristics Population Characteristics
Total population initially 100,000
Percent afflicted initially 0
Percent vulnerable initially 10
34
Developing Assumptions For Response Scenarios
Parameter Assumption
Baseline Epidemiological Characteristics Baseline Epidemiological Characteristics
Vulnerability onset rate ( per year among general pop) 5
Vulnerability reduction rate ( per year among vulnerable) 7
Affliction incidence rate ( per year among vulnerable) 5
Affliction progression rate ( per year among afflicted without complications) 10
Complications death rate ( per year among afflicted with complications) 10
35
Developing Assumptions For Response Scenarios
Parameter Assumption
Public Health System Characteristics Public Health System Characteristics
Complicated affliction prevalence required to elicit maximum public health response (lower prevalence elicits proportionally smaller response) 20
Time for organizing a public health response to complicated affliction prevalence 2 years
36
Making Decisions About How to Respond
Parameter Assumption
Effect of Public Health Responses Effect of Public Health Responses
Tertiary prevention effect on deaths from complications ?
Secondary prevention effect on affliction progression ?
Primary prevention effect on affliction incidence ?
Targeted protection effect on vulnerability reduction ?
General protection effect on vulnerability onset ?
37
Developing a Scenario-based Research Design
Response Scenario Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on 40-Year Simulation Results 40-Year Simulation Results 40-Year Simulation Results
Response Scenario Deaths Affliction Progress Affliction Incidence Vulnerable Reduction Vulnerable Onset Percent Afflicted w/ Complication (T0 0) Percent Vulnerable (T0 10) PH Response (T0 0)
No Response 1 1 1 1 1
Prev 3 0.5 1 1 1 1
Prev 23 0.5 0.5 1 1 1
Prev 123 0.5 0.5 0.5 1 1
Prev 123 Prot 2 0.5 0.5 0.5 2 1
Prev 123 Prot 12 0.5 0.5 0.5 2 0.5
38
Putting the System in Motion
39
Interpreting Behavior Over Time
40
Interpreting Behavior Over Time
Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on 40-Year Simulation Results 40-Year Simulation Results 40-Year Simulation Results
Deaths Affliction Progress Affliction Incidence Vulnerable Reduction Vulnerable Onset Percent Afflicted w/ Complication (T0 0) Percent Vulnerable (T0 10) PH Response (T0 0)
No Response 1 1 1 1 1 11
Prev 3 0.5 1 1 1 1 14
Prev 23 0.5 0.5 1 1 1 12
Prev 123 0.5 0.5 0.5 1 1 11
Prev 123 Prot 2 0.5 0.5 0.5 2 1 10
Prev 123 Prot 12 0.5 0.5 0.5 2 0.5 9
41
Interpreting Behavior Over Time
42
Interpreting Behavior Over Time
Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on 40-Year Simulation Results 40-Year Simulation Results 40-Year Simulation Results
Deaths Affliction Progress Affliction Incidence Vulnerable Reduction Vulnerable Onset Percent Afflicted w/ Complication (T0 0) Percent Vulnerable (T0 10) PH Response (T0 0)
No Response 1 1 1 1 1 11 25
Prev 3 0.5 1 1 1 1 14 24
Prev 23 0.5 0.5 1 1 1 12 24
Prev 123 0.5 0.5 0.5 1 1 11 26
Prev 123 Prot 2 0.5 0.5 0.5 2 1 10 22
Prev 123 Prot 12 0.5 0.5 0.5 2 0.5 9 19
43
Interpreting Behavior Over Time
44
Interpreting Behavior Over Time
Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on Effect of Public Health Response on 40-Year Simulation Results 40-Year Simulation Results 40-Year Simulation Results
Deaths Affliction Progress Affliction Incidence Vulnerable Reduction Vulnerable Onset Percent Afflicted w/ Complication (T0 0) Percent Vulnerable (T0 10) PH Response (T0 0)
No Response 1 1 1 1 1 11 25 0
Prev 3 0.5 1 1 1 1 14 24 69
Prev 23 0.5 0.5 1 1 1 12 24 60
Prev 123 0.5 0.5 0.5 1 1 11 26 53
Prev 123 Prot 2 0.5 0.5 0.5 2 1 10 22 50
Prev 123 Prot 12 0.5 0.5 0.5 2 0.5 9 19 47
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