Healthcare Informatics Ready to Unleash a New Wave of Advanced Analytics

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Healthcare Informatics: Ready to Unleash
a New Wave of Advanced Analytics?
By Steve Barlow, Senior Vice President and Co-Founder

Informatics Metaphor
Look no further than the last scene
of Raiders of the Lost Ark to
comprehend the current state of
healthcare informatics. Specifically
when Indiana Jones is being told
the government has top men
working on discovering the secrets
of the Ark of the Covenant, when in
fact it is being slowly wheeled into a
dark, gigantic warehouse amid what
looks to be thousands of other such
treasures.
They don’t know what
they’ve got there!”
– Indiana Jones
‘‘

Healthcare Informatics Challenge
Much like Indy’s Ark of the
Covenant, massive amounts of
powerful data sits in storage
unused.
Health systems have done a
great job of acquiring data,
especially over the last few years
since electronic health records
(EHRs) became widespread. But
for the most part, the data just
sits in a dark warehouse without
creating value for those who
store it.
Fortunately, today’s healthcare
executives understand the value
of their data and the importance of
making it readily available for
analysis to drive organizational
change, lower costs and improve
patient care.

Triple Aim
•Improving the individual experience of care
•Improving the health of populations
•Reducing the per capita cost of care for populations
Healthcare Informatics Challenge
By extracting the insights of the stored data,
health systems will be able to
reduce outcome variations and raise
the level of quality and patient
satisfaction while driving down
the cost of care, the goal of the
Institute for Healthcare
Improvement’s Triple Aim.
SOURCE: IHI TRIPLE AIM
Triple Aim
• Improving the individual experience of care
• Improving the health of populations
• Reducing the per capita cost of care for populations

The Birth of Healthcare Informatics
Over the past three decades,
visionaries saw a need and
opportunity for technology and
information to support the decision-
making process in delivering
improved patient care.
Pioneers at informatics think tanks,
such as the University of Utah,
Indiana University, Columbia, and
others, have made significant
breakthroughs in terms of using
data to understand and manage
populations.

Healthcare’s Current
“Recreational” Data Situation
Healthcare’s current data situation is
still fairly reactive and historical,
however. Brent James at
Intermountain Healthcare calls it
“recreational data collection,” i.e.,
collecting data for its own sake — the
way some people collect coins or
stamps. Or the way Indy collects
ancient relics to display in a museum.

Moving from Data Acquisition to
Data Extraction
The next frontier is moving from data
acquisition to data extraction. This new
phase will make it possible for analysts
to extract the data out of the EHR, and
combine it with data from other systems
to provide proactive care to populations
of patients.
Health systems will need a significant
change in strategy to succeed. Budgets
must balance between data capture and
storage, and data extraction and
analysis.

Using the Data
It is important to understand that
health systems need more than
clinical data for decision-making
because this type of data doesn’t
provide enough information to
answer every quality improvement
or patient care question.
Health systems also need to
analyze financial data, quality
data, pharmacy data, and other
factors that can affect the quality
and cost of care.

Using the Data
By connecting all of the various
types of healthcare data, it will
then be possible to answer
questions such as these:
Which hip prosthetic delivers the best outcomes, both
from a cost and a quality of life standpoint?
How can we find and eliminate variations in care
delivery in order to improve outcomes and lower costs?
Why did this population of patients, treated at this hospital,
have better quality and financial outcomes than those
patients at other hospitals?

Using the Data
Understanding the entire picture of
patient care is best accomplished by
aggregating data from the individual
source systems into a Late-Binding™
electronic data warehouse (EDW).
Informatics analysts can use powerful
analytics applications to make new
knowledge discoveries to support
clinical decisions and adherence to
standards across patient populations.

Using the Data
A good example is the accepted
standard of not performing elective
inductions on pregnant mothers
before 39 weeks.
Most healthcare organizations
understand the value of this
standard in reducing risks to the
mother, the newborn, and the
provider, and have rules in place to
support it.
Yet when we analyze the EHR data
for our clients, we often discover
that 15 percent of the time they are
not adhering to the standard.

Determining Which Data is Useful
One of the best ways to decide which
data is useful is by looking at which
data is being used and which is not. If
no one is looking at the report or
using the data why bother keeping
it?
Because that’s the way it’s always
been done is not a good reason.
Instead, health systems should focus
their data capture on the information
that assists clinical decisions at the
point of care.

Placing Effort Where the Greatest
Value Lays
The best way to launch a quality
initiative is to start where the changes
will do the most good. In selecting a
clinical process for quality
improvement, choose the process with
high volumes that will result in greatest
ROI.
For example, efforts and resources to
focus on hand procedures is nearly the
same as focusing on patients with
congestive heart failure (CHF).
However, the volumes will be much
higher with CHF patients, thus a higher
ROI.

Looking Ahead
The Rise of the Healthcare Consumer
The day is coming when consumers
shop for providers and procedures,
such as hip replacements or even open
heart surgery, the same way they shop
for cars — armed with a printout and
consumer reviews.
To survive and thrive in this new world
of healthcare informatics, providers will
need to move from collecting data to
analyzing it for critical insights, and from
there to knowledge and finally wisdom
— the classic maturation cycle of data.

More about this topic
Unlocking the Power of Data at Texas Children’s Hospital
An article from Healthcare Informatics
Healthcare Data Analytics Can Prevent Early-Term Deliveries
An article from Healthcare Informatics
Building a High-quality Cancer Care Delivery System
A health system case study on using analytics to address rising cancer
care costs

Other Clinical Quality Improvement Resources
Click to read additional information at www.healthcatalyst.com
Steve Barlow is a co-founder of Health Catalyst and former CEO of the
company. He oversees all development activities for Health Catalyst's suite
of products and services. Mr. Barlow is a founding member and former chair
of the Healthcare Data Warehousing Association.
He began his career in healthcare over 18 years ago at Intermountain Healthcare,
and acted as a member of the team that led Intermountain's nationally recognized
improvements in quality of care delivery and reductions in cost. Mr. Barlow holds a
BS from the University of Utah in health education and promotion.
More by this author:
What Is the Best Healthcare Data Warehouse Model? Comparing Enterprise Data
Models, Independent Data Marts, and Late-Binding™ Solutions
6 Reasons Why Healthcare Data Warehouses Fail
The Best Data Architecture: Know When to Bind Your Healthcare Data

Healthcare Informatics Ready to Unleash a New Wave of Advanced Analytics

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Healthcare Informatics Ready to Unleash a New Wave of Advanced Analytics