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Health IT and Medical Science
Most of those who are deeply involved in healthcare IT have chosen this field as a
mission or vocation, rather than merely a career. Many health IT professionals have
historically taken substantial pay cuts compared with IT professionals in other areas
(although this is improving now). Many of us work in this industry because we lost a
loved one to a simple medical error, or some other failure of the healthcare delivery
system. For many of us, this is our life’s passion. To us, “reducing the costs and im-
proving the quality of healthcare” is a dry and frail description of our ambition for
health IT. To paraphrase Steve Jobs, we want to make a dent in the human condition.
Before we can talk about what that next stage will be like, we should acknowledge that
it will not be anything like past medical advances. Pasteur’s microorganism model of
disease, Darwin’s theory of evolution, Florence Nightingale’s redefinition of nursing,
Roentgen’s X-ray, or perhaps even the discovery of DNA by Watson and Crick are
examples of game-changing insights. These are classic examples of massive improve-
ments in healthcare delivery that come from a new fundamental insight. The improve-
ments to healthcare that happen because of computerization will not be a revolution,
but an evolution.
Fundamental to the ambitions in the health IT community is a humble acknowledg-
ment that these huge game-changing insights are rare. We can expect fewer and fewer
of them as the science of medicine progresses. Instead, medicine must now begin the
difficult work of chronicling the immense complexity of a single cell’s DNA, proteins
and other structures, and how that cell cooperates with other cells in the human or-
ganism. We can no longer expect that individual insights will leap medical science
forward, but instead the medical community will make hundreds of thousands of small
incremental advances on tens of thousands of diseases.
If we hope to continue the rate of improvement in healthcare we must find a way to
coordinate the contributions of countless clinicians, researchers, and patients. To make
any sense out of the genotype, we must have a understanding of phenotype —the
manifest characteristics of individuals, such as their age, weight, medical symptoms,
mental status, and many other measurable traits —than is several orders of magnitude
deeper than it is today. We must be able to gather and parse a hundred times more data
about each patient than we do today, and we must be able to compare that rich data
among millions of patients. Today, the sciences and the software that support clinical
trials, genomics, and standard clinical operations are separate and distinct, with infre-
quent overlap. Tomorrow, these disciplines will merge into a single enormous effort to
improve healthcare. Science on this scale is impossible without mass high-quality com-
puterization. There is no reason why all of this cannot be accomplished while respecting
patient privacy and other basic notions of human dignity.
We hope to use technology to improve every aspect of healthcare. We hope to create
information systems that help to turn medicine into a higher art and a higher science.
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