Conclusions
In the past decade, I’ve seen a growing awareness about systems
and complexity thinking and the development of “user-friendly”
systems science tools. But I’ve also noticed a strong bias toward the
reductionist science tools as “real” or rigorous science. Although
many people in healthcare are now recognizing systems science concepts,
they tend to treat it as a soft science, not as valuable or valid as a
rigorous prospective RCTs. However, the systems science paradigm
provides a much more complete description of how our world really
functions and so the tools are much more valuable to apply for true
learning and improvement in healthcare.
The tools of systems science such as CQI, non-linear analytics and
team-based patient care coordination and management have the potential
to focus on the goal of improving the value of care for our patients.
That also will improve the value for all the parts of our system that
contribute to that value and reduce harm and waste. This will take
effort at the level of each local environment and in the context of each
definable patient care process.
We are going through a paradigm shift in the scientific understanding of
our world, from the machine as a metaphor for human beings to an
understanding that we are complex, adaptive and dynamic systems –
imperfect and nonlinear, but able to adapt in many various ways. We
can’t change the fact that the pace of change and complexity in our
world, like the expansion of our universe, is increasing at an
accelerating rate. But we can learn to apply the science of systems so
that we can learn to improve the value care for patients and our
system-as-a-whole. This will allow us to transform our global healthcare
system to one that is sustainable, and I believe this can lead to a
better world.
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