Build vs. Buy a Healthcare Enterprise Data Warehouse: Which is Best for You?

© 2013 Health Catalyst
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Enterprise Data Warehousing in Healthcare
Build vs Buy considerations
www.healthcatalyst.com

Context for this topic
Assess Design Implement Test Deploy
“Do we have the tools to
use data to transform care
delivery and streamline
operations?”
“Assessment of our current
state indicates we need a
different future state. What
should that look like?”
“Key to our future state will
be an Enterprise Data
Warehouse (EDW) to
integrate data from multiple
sources and facilitate Triple
Aim reporting. Make it so.”
“We will test our EDW to
ensure it is meeting our
expectations.”
“We will roll out our EDW
and analytic applications to
a broad group of users,
including clinicians, leaders,
and administrators.”
Decision
Should we build this EDW from
scratch, or partner with a vendor
to deliver this capability for the
organization. Are those my only
options?
1
Proprietary and Confidential
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Agenda
● Examine the options
– Building an EDW
– Buying an EDW
– Hybrid solution
● Other Considerations
● About Health Catalyst
● Questions

Poll Question
4

Building an EDW
5

What is an EDW?
Metadata, Security, and Auditing
Common, Linkable
Identifiers
Financial
SourceMarts
Administrative
SourceMarts
Departmental
SourceMarts
Patient
SourceMarts
EMR
SourceMarts
HR
SourceMart
Hospital Operations
Primary Care
Asthma
FINANCIALSOURCES
(e.g. EPSi, Peoplesoft, Lawson)
ADMINISTRATIVE SOURCES
(e.g. API Time Tracking)
EMR SOURCE
(e.g. Epic, Cerner)
DEPARTMENTAL SOURCES
(e.g. Apollo)
PATIENTSATISFACTION
SOURCES
(e.g. NRC Picker, Press Ganey)
Human Resources
(e.g. PeopleSoft)

Why choose to build an EDW?
Benefits of a data warehouse:
● Performance
● Integration
● Ease of use
Historically
● Dearth of proven solutions for healthcare
● Pioneers had to demonstrate value prior to funding

Considerations: building an EDW
Worst case scenario: project failure
● 50% of data warehouse projects fail
Common among unsuccessful EDW builds:
● A solid business imperative is missing
● Executive sponsorship and engagement is missing
● Frontline users are not involved from start to finish
Ongoing success is elusive
● Most healthcare IT groups not prepared to function like a
software company
● Limited opportunities to learn lessons before funding is
cut

Pros/Cons: Building an EDW
Pros
● Building it yourself means infinite customization
● Getting “something” built yourself may be “good enough”
(for now)
● Pride of authorship
Cons
● Staffing
● Shortage of qualified resources
● Re-learning lessons
● “Skunkworks” projects can be culturally divisive
● Project management challenges

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Buying an EDW
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10

Why might someone buy an EDW?
Developing well-engineered, custom software may
not be your core competency
Market offerings for healthcare data warehousing
solutions are better than 10 years ago
Support and maintenance agreement help ensure
long term success

Considerations: Buying an EDW
Many of the same risks with any vendor relationship
Evaluating an analytics vendor
● Completeness of vision
● Culture and values
● Total cost
● Ability to execute
– Where else have they had success?
– Will their approach work for my organization?
– Do they have expert resources?
More information:
● How to evaluate a clinical analytics vendor

Pros/Cons: Buying an EDW
Pros
● Shortest time to value
● Real world experience: what works best in practice
● An infusion of help
● Lower total cost of ownership
Cons
● Initial cost
● Knowledge transfer
● Tradeoff between “perfect” and “extremely good”

Poll Question
14

Hybrid Build and Buy
15

Buying AND Building an EDW
In practice, more like “Buy and Extend”
● Leverage a vendor partner for some components
● Develop, using internal resources, others
Examples:
● Select a vendor to:
– Implement the data warehouse
– Integrate several high priority data sources
● Leverage internal resources to:
– Integrate additional data sources
– Develop additional analytic applications
– Integrate data from the warehouse into operational processes

Why choose to build AND buy?
Best of both worlds
● Rapid implementation
● As customizable as a purely “build” solution
● Higher potential for return on investment
Mitigates risk
● Benefit from the lessons your vendor has learned
● Infusion of resources to help deploy and train

Other considerations
Potential pitfalls for any data warehouse project
● “Boil-the-ocean syndrome”
● Seeking governance “perfection”
● Rigid architecture
Insights
● Original article
● Comparing data warehouse architectures for Healthcare
Other Resources
● Healthcare Data WarehousingAssociation (HDWA)
● The Data Warehousing Institute (TDWI)
● Health Catalyst Knowledge Center

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About Health Catalyst
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Health Catalyst Profile
Integrated Delivery Systems
Community Hospitals
Academic Medical Centers
Children’s Hospitals
Patients
Impacted
Hospitals
& Clinics
25M 1400
Founded 2008
Employees 140
HQ Salt Lake City, UT

What does Health Catalyst offer?
Late-Binding™
Data Warehouse Platform
Data Warehouse, Architecture, Metadata
Management, Security, and Auditing
Analytic Applications
Key Process Analysis,
Dashboards, Advanced Analytics
Services
Installation Services,
Clinical Improvement Services
Integrates
Disparate Data
Apply Evidence
and Standardize
Change Process
and Behavior

Application Families

Reduce Healthcare Labor Costs by
using an EDW and Analytics
“The work our organization is doing with the Health Catalyst team pushes the envelope of what it
means to have near real-time data at our fingertips to make operational decisions. Their technology
and processes put us on track to understand the potential upstream and downstream financial
impact of even the smallest decision.”
~ Director Clinical Planning and Financial Management
Objective
• Manage labor costs by
allocating resources
appropriately to the
demand for services
• Eliminate the need to
manually pull and
consolidate reports on a
monthly basis for a 3rd
party point solution
• Enable business and unit
managers to better track
and manage
performance by providing
more timely information
Health Catalyst Solution
• Late-Binding™ Data
Warehouse
• Labor Productivity
AdvancedApplication
Module
• Installation Services
• Improvement Services
Results to date
• Estimated 2% reduction
in total salaries and
benefits to date
• 66% percent increase in
the speed of data
availability
• Estimated NPV of $425K
over a 4-year period from
automated data
integration
• 500% increase in the
number of managers
using data to drive
decisions

How to Reduce Heart Failure
Readmissions
• Late-BindingTM data
warehouse that enables
faster time-to-value
• Integration of clinical,
patient satisfaction and
financial data to establish
baseline, ongoing and
balance measures
• Discovery, Foundational
andAdvanced HF
applications including
cohort finder, registry and
evidence- based clinical
content
• Healthcare analytic
visualization including
gauges and trend lines
for at-a-glance view
• Seasonally adjusted rate
reduction of 21% in 30-
day and 14% in 90-day
readmissions
• 2X increase in the
number of phone calls
made to patients within
48 hours of discharge
• Average of 63 % increase
in physician medication
reconciliation within 48
hours of discharge
• Follow-up appointment
intervention baseline and
balance measures
established
“Our data is now accessible to stakeholders throughout the organization, including clinical teams
who can use it to drive improvements in care processes, care quality and patient outcomes”
~ Director of Clinical & BusinessAnalytics
Objective Health Catalyst Solution Results to date
• Define Heart Failure (HF)
baseline measures for 30
and 90-day readmissions
rates
• Implement evidence-
based practice
interventions to drive HF
readmission rate
reductions
• Establish balance metrics
including ED visits,
observation days and
patient satisfaction
• Develop sustaining
processes for evaluating
readmission rates to
ensure continuous
process improvement

Questions and Answers
Additional Information
• See us at HIMSS 2014 booth #6076
• Call 801.708.6800 to request a
meeting
• Listen to two clients speak:
– “Improving Outcomes with an
Innovative Approach to
Population Health Analytics”
» Stanford Hospital & Clinics
» Yohan Vetteth, Pravene Nath, MD
» Date/Time: Thursday, 2/27, 12 PM
» Location: Room 304A, Session #229
– “Blending Clinical and Financial
Data to Drive the Value
Equation”
» Texas Children’s Hospital
» Charles Macias, MD
» Date/Time: Wednesday, 2/26, 1 PM
» Location: Room 304A, Session #191
• Follow us on Twitter
– @healthcatalyst
Explore our site: www.healthcatalyst.com

Build vs. Buy a Healthcare Enterprise Data Warehouse: Which is Best for You?

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Build vs. Buy a Healthcare Enterprise Data Warehouse: Which is Best for You?