Page 11 - Building Big Data Applications

Chapter 1 Big Data introduction 5

Healthcare example

Inthe pastfewyears,a significantdebatehasemergedaroundhealthcareanditscosts.There
are almost 80 million baby boomers approaching retirement, and economists forecast this
trendwilllikelybankruptMedicareandMedicaidinthenearfuture.Whilehealthcarereform
and its new laws have ignited a number of important changes, the core issues are not
resolved. It’s critical we fix our system now, or else our $2.6 trillion in annual healthcare
spending will grow to $4.6 trillion by 2020done-fifth of our gross domestic product.

Data-rich and information-poor

Healthcare has always been datarich. Medicine has developed so quickly in the past 30
years that along with preventive and diagnostic developments, we have generated a lot of
data: clinical trials, doctors’ notes, patient therapies, pharmacists’ notes, medical liter-
ature and, most importantly, structured analysis of the data sets in analytical models.
On the payer side, while insurance rates are skyrocketing, insurance companies are
trying hard to vie for wallet share. However, you cannot ignore the strong influence of
social media.
On the provider side, the small number of physicians and specialists available versus
the growing need for them is becoming a larger problem. Additionally, obtaining second
and third expert opinions for any situation to avoid medical malpractice lawsuits has
created a need for sharing knowledge and seeking advice. At the same time, however,
there are several laws being passed to protect patient privacy and data security.
On the therapy side, there are several smart machines capable of sending readings to
multiple receivers, including doctors’ mobile phones. We have become successful in
reducing or eliminating latencies and have many treatment alternatives, but we do not
know where best to apply them. Treatments that can work well for some, do not work
well for others. We do not have statistics that can point to successful interventions, show
which patients benefited from them, or predict how and where to apply them in a
suggestion or recommendation to a physician.
There is a lot of data available, but not all of it is being harnessed into powerful in-
formation. Clearly, healthcare remains one of our nation’s datarich, yet information-
poor industries. It is clear that we must start producing better information, at a faster
rate and on a larger scale.
Before cost reductions and meaningful improvements in outcomes can be delivered,
relevant information is necessary. The challenge is that while the data is available today,
the systems to harness it have not been available.

Big Data and healthcare

Big Data is information that is both traditionally available (doctors’ notes, clinical trials,
insurance claims data, and drug information), plus new data generated from social