Forbs | By
Dan Riskin, MD
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Dan Riskin lecturing at FutureMed at Singularity University in 2011.
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Every 50 years, there is a revolution in healthcare based on the trends of
the era. In the 1870s, healthcare was revolutionized by the germ theory of
disease and promotion of public health efforts. In the 1920s, the discovery of
penicillin propelled forward the use of medication as treatment for disease. In
the 1970s, use of the randomized controlled trial (RCT) ushered in an era of
evidence-based medicine. As we approach the 2020’s, the trend toward big data,
tools and systemization of care will revolutionize the way hospitals and
physicians work and, most importantly, the way patients are treated.
Big data refers to a set of information and data so large and complex that
it becomes difficult to process using conventional database management tools.
At issue is how to access, distribute and utilize this vast amount of
“unstructured” data. For patients, clinicians and hospitals that have massive
amounts of clinical content in electronic health records (EHRs) that remains
unused, the implications can be rising mortality rates and out-of-control
medical costs.
Let’s consider the current vanguard of data-driven healthcare in hospitals.
At the best institutions, doctors and nurses are going room to room each day to
mark down which patients meet which quality metrics and whether they’re
addressed. The result is a manually-entered, cumbersome flow chart that
can, at best, address a handful of the hundreds of known quality measures and
use limited data to address these. With a condition like deep-vein thrombosis
for example, hospital staff relies on manual calculations to assess the risk of
a patient. The problem is, if not treated properly, mortality rates rise. The
real tragedy is that the information needed to properly assess the patient’s
risk and determine treatment is available in the clinician’s notes, but without
the proper tools the knowledge remains unavailable and hence, unused.
Today, the most formidable tools to effectively manage unstructured data
include natural language processing, ontologies and data mining, which together
support the effective use of unstructured data. Systemization of healthcare has
been slowly implemented over decades, but has rapidly accelerated with EHR
adoption and government mandates. Ultimately, the proper systems put into place
allow the knowledge learned from big data to be distributed and used.
So, if data flow tools to manipulate data exist, and systems to implement
process improvements are possible, how do these trends underlie a change in the
field of healthcare? Data-driven healthcare has become increasingly
well-defined and understood over recent years. It is the concept that large
record sets can assure that best treatment algorithms are applied and that
treatment algorithms are customized for individual patients. It means that
although modern medicine treats the 83 year-old diabetic patient with
hypertension similarly to the 45 year-old athlete with hypertension, based on
them being grouped together in the same clinical trial, in the future, care
will be personalized based on what worked best for millions of similar patients
previously. This level of customized care offers the promise of better and more
applicable care.
Financial outcomes are expected to improve as well. According to a 2011
report from McKinsey Global Institute, if health care in the US used big data
creatively and effectively to drive efficiency and quality, the potential value
from data in this sector could be more than $300 billion in value every year.
Two-thirds of this figure would influence national health care expenditures,
representing an 8 percent cost reduction.1
This is the future of healthcare: big data, robust tools and clear
processes for intervention. It represents an opportunity for innovators and
those that care about healthcare. It represents the potential for better
outcomes and lower mortality rates for patients. Brace for a revolution
in healthcare where we all have the opportunity to help and everyone has a
stake.
[1] McKinsey and Company, McKinsey Global Institute, “Big Data: The next
frontier for innovation, competition and productivity,” May, 2011.
About the author
Dan Riskin, MD, is a FutureMed faculty member at Singularity University. Dr. Riskin is the CEO of Health Fidelity, provider of a commercial-grade, cloud-based natural language processing
(NLP) service, and is also a Consulting Assistant Professor of Surgery at Stanford University.