Prof Don de Savigny_What are Health Systems

Report
IAPB 9th General Assembly
Eye Health: Everyone’s Business
Hyderabad, India
September 17-20, 2012
What are Health Systems?
And why should we engage?
Prof. Don de Savigny
Health Systems Research
Department of Epidemiology and Public Health
[email protected]
Health System Conceptual Foundations
2000
2007
2008
2009
Health systems for eye health: Everyone’s business
Health systems
“All
organizations, people and action whose primary intent is
to promote, restore or maintain health”
WHO, 2007
Key social goal…
Improve health by
average level of population health
health inequities
Basic health system framework
INPUTS & PROCESSES
IMPACTS
OUTPUTS
Governance
Service delivery
Finances
•
•
•
•
•
•
•
Human resources
Medicines,
technologies &
infrastructure
efficiency
access
availability
affordability
acceptability
quality
safety
OUTCOMES
Increased
•
effective coverage
•
responsiveness
Information
•
•
OTHER DETERMINANTS OF HEALTH
(Economic, Social, Political, Environmental)
Modified from: WHO Everybody’s business, 2008 & Health Metrics Network Framework, 2008
Improved
•
survival
•
nutrition
•
equity
Reduced
•
morbidity
•
impoverishment
due to health
expenditures
Health systems
A tightly inter-woven framework of building block sub-systems
“What happens in
the spaces between
the sub-systems is
as important as what
goes on within them;
and is usually
neglected”.
Source: de Savigny and Adam (2009)
System = Whole
A system is:
any collection of related parts
that interact
in an organized way
for a purpose
Characteristics of all complex systems
And ….
• nest sub-systems within them
• but are part of larger systems
Example of non-linearity & perverse effects
1. Reimbursement for
severe malaria set too high
4. Lag in procurement
of 3rd line drugs for
malaria
3. Health Information
system records a rise in
severe malaria
= Reduced access
to correct malaria
treatment and
higher OOP
2. Providers capture more
profit by diagnosing more
severe malaria
5. Drug stock-outs at
health facility; Quality
drops
Systems thinking
Systems thinking gives deeper insights into:

how a system works,

why it has problems,

how it can be improved
Graphic adapted from Ahn A.C. et al. PLoS Med 3:956-960 (2006).
Systems thinking involves shifting attention…
 from the parts to the whole,
 from objects to relationships,
 from structures to processes,
 from hierarchies to networks,
 from the rational to the intuitive,
 from analysis to synthesis,
 from linear to non-linear thinking.
Adapted from Fritjof Capra
System thinking skills
Usual approach
Systems thinking approach
Static thinking
Dynamic thinking
focus on events
focus on patterns of behaviour
System thinking skills
Usual approach
Systems thinking approach
Static thinking
Dynamic thinking
focus on events
Systems as effect
behaviour as externally driven
focus on patterns of behaviour
Systems as cause
responsibility for behaviour from
internal actors and rules
System thinking skills
Usual approach
Systems thinking approach
Static thinking
Dynamic thinking
focus on events
Systems as effect
behaviour as externally driven
Tree-by-tree thinking
knowledge from understanding details
focus on patterns of behaviour
Systems as cause
responsibility for behaviour from
internal actors and rules
Forest-thinking
knowledge from understanding
contexts of relationships
System thinking skills
Usual approach
Systems thinking approach
Static thinking
Dynamic thinking
focus on events
Systems as effect
behaviour as externally driven
Tree-by-tree thinking
knowledge from understanding details
Factors thinking
concentrating on factors that influence
or correlate
focus on patterns of behaviour
Systems as cause
responsibility for behaviour from
internal actors and rules
Forest-thinking
knowledge from understanding
contexts of relationships
Operational thinking
concentrating on how behaviour is
generated
System thinking skills
Usual approach
Systems thinking approach
Static thinking
Dynamic thinking
focus on events
Systems as effect
behaviour as externally driven
Tree-by-tree thinking
knowledge from understanding details
Factors thinking
concentrating on factors that influence
or correlate
Linear thinking
view causality running in one direction
focus on patterns of behaviour
Systems as cause
responsibility for behaviour from
internal actors and rules
Forest-thinking
knowledge from understanding
contexts of relationships
Operational thinking
concentrating on how behaviour is
generated
Loop thinking
View causality as an on-going process
with feedback influencing causes
System phenomena:
Feed back loops
When the outcome of a
system process is the input in
the same system
Explains:
- vicious circles,
- stock and flow problems,
- price & demand modulation,
- and why standardized approaches
continue to serve the same
populations but fail to reach the poor.
Adapted from: Paina & Peters (2012)
System phenomena:
Path dependence
Different, non-reversible
processes from similar starting
points.
Outcomes sensitive to initial
conditions and choices along the
way.
Why solutions that work in one
country may not work in another.
Adapted from: Paina & Peters (2012)
System phenomena:
Emergent behaviour
Spontaneous creation of order
when smaller entities jointly
contribute to organized behaviour
as a collective where the whole is
greater and more complex than the
sum of the parts.
Adapted from: Paina & Peters (2012)
Social Network
Analysis
Disappearance of a
broker resulted in 179
dropped ties across
districts.
2006
SNA software allows
quantitative analysis of
network density,
distance, centrality,
information flows.
Blanchet and James (2012)
2010
System phenomena:
Scale free networks
Networks dominated by few
focal points or hubs with
unlimited connections follow
power-law distributions
Adapted from: Paina & Peters (2012)
Explains disproportionate
effects of influencing hub
individuals
Systems thinking
Pushing harder and harder on familiar solutions,
while fundamental problems persist or worsen,
is a reliable indicator of non-systems thinking –
the "what we need here is a bigger hammer" syndrome
Peter Senge, 1990
Leverage points when intervening in a system
(in increasing order of effectiveness)
9. Constants, parameters, numbers, subsidies
8. Regulating negative feedback loops
7. Driving positive feedback loops
6. Material flows
5. Information flows
4. Rules of the system (incentives, constraints)
3. Distribution of power over the rules of the system
2. Goals of the system
1. The mindset or paradigm out of which the system -- its goals, power
structure, rules, culture arises.
Modified from Donella Meadows
Small changes can produce big results !
-- but points of highest leverage are least obvious
There are no rules for finding tipping points, but there are ways of thinking that
make it more likely.
Learning to look system-wide and see underlying processes, approaches and
contexts rather than "events" is a starting point...
“Systems Thinking” is the language and
“Systems Science” is the discipline
Approaching 2020 will benefit from
increasingly sophisticated approaches to
tipping points in complex adaptive
health systems

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