Data Management and Healthcare: Why Databases and EMRs Don't Make the Cut on Their Own

© 2014 Health Catalyst
www.healthcatalyst.com
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www.healthcatalyst.comProprietary. Feel free to share but we would appreciate a Health Catalyst citation.
Data Management and Healthcare: Why Databases
and EMRs Don’t Make the Cut on Their Own
By Dr. David Burton.

The Myth of Stand-alone EHR
Facing the most sweeping
payment transformation in history,
healthcare systems are struggling
to figure out how the shift to a
value-based model will impact their
operations and bottom line.
They know an EHR by itself isn’t
going to be enough to make the
transition to the new model of care
delivery and are now looking to
additional data management and
healthcare analytics solutions.

Simultaneously, they must also address complementary but
competing priorities, such as:
• Emerging shared-risk payment models such as Accountable Care
Organizations (ACOs), patient-centered medical homes, and bundled
payments
• The deployment or upgrade of an EHR to capture documentation data
electronically and qualify for Meaningful Use incentives
• New reimbursement carrots and sticks tied to quality and efficiency outcomes
• Transitioning to a patient-centered care model
• A shortage of qualified health information technology professionals
• Overall industry consolidation

This has strained internal
resources and left many health
systems working to stay ahead of
regulatory timetables.
Unfortunately, this management-
by-crisis approach has led to a
focus on tactical point solutions
designed to address immediate
needs at the expense of an
integrated, strategic plan to
address both immediate and
long-term needs.

Analytics packages offered by their
EHR vendor and their existing
business intelligence/analytics
tools are not up to the task of
supporting the transformation
currently underway.
New technologies, such as
adaptive, late-binding data
warehouses, are providing new
data management and healthcare
analytics solutions that can identify
opportunities to improve clinical
effectiveness, cost effectiveness,
and safety.

Benefits of Data Management
Health Catalyst deploys a
unique Late-Binding™ Data
Warehouse that enables
healthcare organizations to
automate extraction,
aggregation, and integration
of clinical, financial, costing,
administrative, patient
experience, and other
relevant data and apply
advanced analytics to
organize and measure
clinical, patient safety, cost
and patient satisfaction
processes and outcomes.
Data Acquisition and Storage
Source Mart Designer IDEA
Source Marts:
EMR, Patient,
Billing, Costing,
General Ledger,
Patient satisfaction
Source Marts:
Clinic EMR,
Professional,
Billing, Time Card,
HR, AR, Supply
Chain, Claims
Source Marts:
Additional
Source Marts
as necessary
Catalyst Analytics
Platform
Atlas
EDW Console
Security and Auditing
Meta-Data Engine
Advanced Analytics
Data Marts
Content Repositories
SAM Designer
Late BindingTM Data Warehouse

Without an agile, adaptable
data warehouse, health
systems and their clinicians
are unable to integrate
clinical data with financial,
standard costing, and patient
satisfaction data located in
disparate transactional
systems, each of which often
has its own unique system
for identifying patients and
providers.

An adaptive data warehouse
enables organizations to become
data-driven enterprises capable
of analyzing data to identify
opportunities for improvement.
This can be done by department,
by procedure, by disease or
condition, by service line, by
physician, or any other category
for which data is captured
electronically.

The Healthcare Analytics Adoption
Model describes a wide variety of
increasingly sophisticated and
useful types of analytic capabilities
that each organization can produce
over time, but only with the caveat
of first starting with the foundational
element of the EDW.

Healthcare: Efficiency & Effectiveness
To succeed in the future, hospitals
must demonstrate quantitatively
that they operate more effectively,
more efficiently, and more safely.
Hospitals must identify and reduce
waste in three categories:
• Waste due to variation in the
care that is ordered
• Waste due to variation in how
efficiently that care is delivered
• Waste due to variation in care
delivery that cause preventable
complications

According to a 2012 report from
the Institute of Medicine,
approximately 30 percent of U.S.
healthcare spending in 2009 was
wasteful, including unnecessary
services, medical errors, poor care
coordination, excessive
administrative costs, fraud, and
other problems.

Now that public and private
payers are reducing payments
or refusing to pay for poor-
quality care, including care that
is defective or unsafe, waste is
becoming a financial drain on
bottom lines.
The Centers for Medicare and
Medicaid Services (CMS)
recently withheld a percentage
of Medicare payments to almost
1,500 hospitals because of high
rates of patients readmitted
within 30 days of being treated.

CMS expanded the list of
preventable hospital-acquired
conditions it won’t pay for from
nine to eleven.
Those hospital-acquired
conditions include, for example,
pressure ulcers; injuries caused
by falls; central-line and urinary
catheter-associated infections;
and surgical infections resulting
from artery bypass grafts, bariatric
surgery for obesity, and certain
orthopedic procedures.

Clearly, the new CMS reimburse-
ment policies and other industry
quality measures linked to
payment are pressuring hospital
bottom lines more than ever.
This is where data management
and an advanced healthcare-
specific analytics platform can
support process improvements to
reduce errors and unnecessary
use of high-cost services.

Data management and healthcare
analytics solutions uncover waste
tied to excessive diagnostics and
procedures ordered to minimize
exposure to malpractice.
Mining data for information can
ensure more effective and safer
patient care at a lower cost using
clinical analytics not available from
an EHR alone — precisely the role
of data management and
healthcare analytics.

More about this topic
Late-Binding Data Warehouse: The Fastest Growing Trend in Healthcare Analytics
(a free, on-demand webinar, transcript, and slides)
Dale Sanders, Senior Vice President
New Report Covers Major Shift From EMRs to Data Management and Healthcare Analytics
Gartner
Building a Data Warehousing and Analytics Strategy
(a free, on-demand webinar, transcript, and slides)
Eric Just, Vice President of Technology, and Mike Doyle, Vice President
Health Information Technology: Why Point Solutions Strike Out
Ken Trowbridge, Vice President
The Late-Binding Data Warehouse Explained (white paper)
Dale Sanders, Senior Vice President, Strategy

For more information:

Other Clinical Quality Improvement Resources
Click to read additional information at www.healthcatalyst.com
Dr. David A Burton is former Executive Chairman and CEO of Health Catalyst, and
currently serves as a Senior Vice President, future product strategy. As a senior leader
of the Health Catalyst team, Dr. Burton has been instrumental in helping define and
design all elements of the Health Catalyst strategy, including our future product
roadmaps, our advanced deployment and operational processes engaging executives and
clinicians in data-driven improvement methodologies, and our content strategy for integrating
best practice and evidence-based guidelines into our product categories. Previously, Dr. Burton
was as a Senior Vice President of Intermountain Healthcare, where he served in a variety of
executive positions for 23 years and co-developed Intermountain's Clinical Integration strategy,
including advocacy of the EDW, which supported it. Dr. Burton is the former founding Executive
Vice President of Intermountain's managed care plans (now known as SelectHealth), which
currently provide insurance coverage to approximately 600,000 members. He holds an MD from
Columbia University College of Physicians and Surgeons and did his residency training at
Massachusetts General Hospital in internal medicine. He was a charter member of the American
College of Emergency Physicians and was Board Certified in Emergency Medicine. He practiced
emergency medicine and was president of a single-specialty group of 20 emergency care
physicians before joining the executive team at Intermountain. He holds an MD from Columbia
University College of Physicians and Surgeons and did his residency training at Massachusetts
General Hospital in internal medicine. He was a charter member of the American College of
Emergency Physicians and was Board Certified in Emergency Medicine. He practiced
emergency medicine and was president of a single-specialty group of 20 emergency care
physicians before joining the executive team at Intermountain.

Data Management and Healthcare: Why Databases and EMRs Don't Make the Cut on Their Own

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Data Management and Healthcare: Why Databases and EMRs Don't Make the Cut on Their Own