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© 2014 Health Catalyst
www.healthcatalyst.com
Proprietary and Confidential
© 2014 Health Catalyst
www.healthcatalyst.comProprietary and Confidential
6 Reasons Healthcare Data Warehouses Fail
By Steve Barlow
© 2014 Health Catalyst
www.healthcatalyst.com
Proprietary and Confidential
The Failure/Success Imperative
2
It’s no secret that the failure rate
of data warehouses is high.
Gartner once estimated as many
as 50 percent of data warehouse
projects would have only limited
acceptance or fail entirely. So
what’s the difference between
success and failure for an EDW?
Health Catalyst has pinpointed
six missteps many failed data
projects have in common
© 2014 Health Catalyst
www.healthcatalyst.com
Proprietary and Confidential
No solid business imperative
3
Success requires a clear understanding
of your financial and clinical needs and
how you expect a data warehouse to
address them – defined with input from a
team of business and clinical staff who
will be using the information every day to
make decisions.
Six Reasons
EDW
PROJECTS
FAIL
1
© 2014 Health Catalyst
www.healthcatalyst.com
Proprietary and Confidential
Executive engagement is
weak or non-existent
4
Senior leaders throughout the
organization including clinical,
finance, quality, strategy and
administration should steer the
project from day one through
deployment.
The governing body needs
to be fully engaged in approving
the budget, technical team,
vendor partner, and priorities.
Six Reasons
EDW
PROJECTS
FAIL
2
© 2014 Health Catalyst
www.healthcatalyst.com
Proprietary and Confidential
Frontline healthcare staff not
involved from start to finish
5
Who better understands information needs and clinical
processes than the frontline information consumer?
Multidisciplinary, frontline teams—clinicians, technologists,
analysts and quality personnel—should be involved
throughout design and deployment.
Six Reasons
EDW
PROJECTS
FAIL
3
© 2014 Health Catalyst
www.healthcatalyst.com
Proprietary and Confidential
Boil-the-ocean syndrome
takes over
6
Trying to be all things to all people
spells disaster. You simply can’t
deliver value quickly if you’re
bent on ―boiling the ocean‖
—identifying every possible piece
of data just in case it might be
needed at some time in the future.
Taking an iterative approach—
choosing one clinical area at a
time to focus on and gradually
improving quality and cost—is
what pays off in both the short and
long run.
Six Reasons
EDW
PROJECTS
FAIL
4
© 2014 Health Catalyst
www.healthcatalyst.com
Proprietary and Confidential
The ideal trumps reality
7
Without consideration of current data capabilities, organizations
will start from scratch, defining every possible future data
requirement. They fail to understand what will be involved in
obtaining that data. Without balancing the ideal with reality
the road to failure looms large.
Instead, organizations should take a pragmatic approach and
work with data already available and add more when feasible.
Six Reasons
EDW
PROJECTS
FAIL
5
© 2014 Health Catalyst
www.healthcatalyst.com
Proprietary and Confidential
Worrying about governance
perfection immobilizes the project
8
When it comes to governance, too often ―perfect‖ is the enemy
of progress. Believing you must have all the decisions wrapped
up before you start can immobilize a project. It’s more efficient
to put governance further down the development path.
Once you have data to govern and react to, the data
governance and prioritization process will accelerate.
Six Reasons
EDW
PROJECTS
FAIL
6
© 2014 Health Catalyst
www.healthcatalyst.com
Proprietary and Confidential
Other Clinical Quality Improvement Resources
Click to read additional information at www.healthcatalyst.com
What is the Best Healthcare Data Warehouse Model? Comparing
Enterprise Data Models, Independent Data Marts, and Late-Binding
(TM) Solutions (Also by Steve Barlow)
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.

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Six Reasons Why Healthcare Data Warehouses Fail

  • 1. © 2014 Health Catalyst www.healthcatalyst.com Proprietary and Confidential © 2014 Health Catalyst www.healthcatalyst.comProprietary and Confidential 6 Reasons Healthcare Data Warehouses Fail By Steve Barlow
  • 2. © 2014 Health Catalyst www.healthcatalyst.com Proprietary and Confidential The Failure/Success Imperative 2 It’s no secret that the failure rate of data warehouses is high. Gartner once estimated as many as 50 percent of data warehouse projects would have only limited acceptance or fail entirely. So what’s the difference between success and failure for an EDW? Health Catalyst has pinpointed six missteps many failed data projects have in common
  • 3. © 2014 Health Catalyst www.healthcatalyst.com Proprietary and Confidential No solid business imperative 3 Success requires a clear understanding of your financial and clinical needs and how you expect a data warehouse to address them – defined with input from a team of business and clinical staff who will be using the information every day to make decisions. Six Reasons EDW PROJECTS FAIL 1
  • 4. © 2014 Health Catalyst www.healthcatalyst.com Proprietary and Confidential Executive engagement is weak or non-existent 4 Senior leaders throughout the organization including clinical, finance, quality, strategy and administration should steer the project from day one through deployment. The governing body needs to be fully engaged in approving the budget, technical team, vendor partner, and priorities. Six Reasons EDW PROJECTS FAIL 2
  • 5. © 2014 Health Catalyst www.healthcatalyst.com Proprietary and Confidential Frontline healthcare staff not involved from start to finish 5 Who better understands information needs and clinical processes than the frontline information consumer? Multidisciplinary, frontline teams—clinicians, technologists, analysts and quality personnel—should be involved throughout design and deployment. Six Reasons EDW PROJECTS FAIL 3
  • 6. © 2014 Health Catalyst www.healthcatalyst.com Proprietary and Confidential Boil-the-ocean syndrome takes over 6 Trying to be all things to all people spells disaster. You simply can’t deliver value quickly if you’re bent on ―boiling the ocean‖ —identifying every possible piece of data just in case it might be needed at some time in the future. Taking an iterative approach— choosing one clinical area at a time to focus on and gradually improving quality and cost—is what pays off in both the short and long run. Six Reasons EDW PROJECTS FAIL 4
  • 7. © 2014 Health Catalyst www.healthcatalyst.com Proprietary and Confidential The ideal trumps reality 7 Without consideration of current data capabilities, organizations will start from scratch, defining every possible future data requirement. They fail to understand what will be involved in obtaining that data. Without balancing the ideal with reality the road to failure looms large. Instead, organizations should take a pragmatic approach and work with data already available and add more when feasible. Six Reasons EDW PROJECTS FAIL 5
  • 8. © 2014 Health Catalyst www.healthcatalyst.com Proprietary and Confidential Worrying about governance perfection immobilizes the project 8 When it comes to governance, too often ―perfect‖ is the enemy of progress. Believing you must have all the decisions wrapped up before you start can immobilize a project. It’s more efficient to put governance further down the development path. Once you have data to govern and react to, the data governance and prioritization process will accelerate. Six Reasons EDW PROJECTS FAIL 6
  • 9. © 2014 Health Catalyst www.healthcatalyst.com Proprietary and Confidential Other Clinical Quality Improvement Resources Click to read additional information at www.healthcatalyst.com What is the Best Healthcare Data Warehouse Model? Comparing Enterprise Data Models, Independent Data Marts, and Late-Binding (TM) Solutions (Also by Steve Barlow) 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.