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Mergers, Acquisitions, And Partnerships
Dramatically Reducing IT Consolidation Expenses
With a Data Operating System
Dale Sanders
September 2017
Thanks, Rus Tabet, for graphic
• I work for Health Catalyst and the technology we produce is related
to the concepts that I advocate in this lecture
• The technology strategies and concepts advocated herein, I would
also follow myself, if I were still an operational healthcare CIO
Disclosure
One of our Four Operating Principles
• Digitizing healthcare… EHRs we’re just beginning
• Mergers, Acquisitions, and Partnerships and IT
strategy
• What’s a Data Operating System and what role
does it play in M&A?
Today’s Story
1. For better or worse, faster or slower, your company runs at the
speed of software now
2. Everything you want and need to do is either helped or hindered
by software and data
3. All C-levels now need to be a little bit Chief Information
Officer and Chief Digital Officer
Advice to C-levels About a Digital Health Future
Thank you, Russel Reynolds Associates for the graphic
• The world’s largest taxi company… owns no taxis
• The world’s largest voice/video communications companies… own no telco
• The most popular media company… owns no content
• The largest lodging company… owns no property
• The world’s most valuable retailer… owns no inventory
• The world’s largest software vendors… don’t write the apps
Digital Disruption is Already Happening
Thanks for the inspiration, Ron Kalifa of Worldpay; and IBM
The world’s largest and most successful healthcare and
health management companies,
will own no hospitals
In the Digital Future of Healthcare…
The Parallels Between Health and Car Maintenance
An ounce of prevention is worth a pound of cure
• Every 10 hours, Tesla collects 1 million miles of
driving data
• 25Gbytes per car per hour
• We collect 100Mbytes per patient per year, on
average
• “We can fix problems in your car and make it
safer, long before you know you need it.”
• ”10,000 fatalities and 500,000 injuries per year
will be prevented.”
• Ram Ramachander, Chief Commercial Officer, Social
Innovation Business at Hitachi
80% of Factors Affecting Health Outcomes Fall Outside Traditional Healthcare Delivery
The Breadth of the Human Health Data Ecosystem
What data do we need for research, personalized care, and community health?
And, by the way, we have barely
any data on healthy patients
Humans Gravitate Towards Freedom of Choice
6 billion smart phones by 2020 in a world population of 8 billion
10
Evolution of Healthcare IT
In The Meantime, This Is What’s Possible…
• 103 applications on my iPhone
• 89 different vendors
• They build on a common platform with open
software standards
• I wouldn’t expect nor hope for a single
vendor to meet all my needs
Mergers, Acquisitions, &
Partnerships
And the IT strategies that help or hurt
• It’s not over…
• 11 straight quarters of more than 200 M&As in healthcare,
totaling $49.6B
• PwC
• “Top performers across all industries focus first on data
integration and have a plan to do so within six months post-
merger.”
• “40% of M&A value in healthcare is directly tied to IT strategy.”
• McKinsey
Mergers, Acquisitions, Partnerships
14
• Your new company is not integrated until your data is integrated
• HIE’s are not sufficient for data integration… not even close
• Ripping and replacing EMRs and ERP systems with a single, common vendor
is not an affordable or timely strategy
• M&A strategy in the digital world is more about data acquisition than
bricks & mortar acquisition– but that’s not happening in healthcare
Sanders’ Assertions
IT Integration vs. The Technology Stack
Computing Infrastructure, e.g., severs, networks, data centers, storage
Databases and Operating Systems, e.g.
Oracle, SQL, MySQL, Hadoop, Spark, iOS, Android, Linux, Windows
Data Content
Software Applications, e.g. EHR, HR, Finance, Email, Web, etc.
The data content layer is the
only layer in the stack that
can be “peeled” away without
impacting the other layers
There is a tendency to
start here in healthcare
• Economies of scale… more efficient through consolidation of
shared services and other infrastructure
• Combining scarce resources
• Move into complementary markets, by geography or product
• Reduce risk through larger populations and revenue
• Improve an underperforming organization or asset and thus
increase revenue
Common Motives Behind M&As in Healthcare
17
• There generally isn’t one, other than the hope of administrative
savings through IT consolidation
• The strategic value of data acquisition is still largely ignored
What’s the IT Strategy in Healthcare M&A?
18
IT Strategies that Drive M&A Success
• The acquirer gets its own IT house in-order, first
• Many develop a “Services Oriented Architecture” anticipating the need to be flexible and
adaptable
• IT leaders are heavily involved in the due diligence prior to acquisition
• Forecasts of revenue growth and cost synergies are driven by financial rules of thumb,
ignoring the challenges of integrating the business and clinical functions that IT enables
• Carefully plan post-merger integration, during due diligence, and factor those into the
overall acquisition costs
• A data integration plan within 6 months post-merger
• Not a systems or application integration plan
10-15% cost savings from a successful IT integration strategy
19
• The prevailing solution: Rip and replace
• You’ll be finished in 3-4 years, if you’re lucky, and be 74% over-schedule,
59% over-budget, and deliver 56% less value than predicted*
• In the meantime…
ERP, EHR, and Other Systems Consolidation
*McKinsey, 2012; Standish, 2013
Costs to Rip & Replace... Just for EHRs
These are my personally calculated numbers, based on first-hand
experience…
• $13K, minimum, per employee
• $41K, minimum, per physician
• Hundreds of millions of $$ is common
That’s one of dozens of application software systems in today’s healthcare systems
21
“Will you ever consolidate to a single EHR?”
“Oh no, I can’t imagine. We’ve looked at it a few times, but the total
costs are in the billions, and for what? Minor incremental value? We’re
using our data warehouse and building a software services layer to tie
them together until there are better options.”
--C-level at the largest for-profit health system in the U.S.
22
• The demand for EHRs
was stretched by
federal incentives.
That’s over.
• The underlying
software and
database technology
of EHRs was
commoditized a long
time ago.
• We can stretch the
lifecycle and value of
EHRs with DOS and
open APIs, e.g. FHIR.
You Can Extend the Life of Existing EHRs With a Good Data Strategy
So, What’s a Data
Operating System?
Back to the Technology Stack
25
Cloud Computing, e.g.
Amazon, Microsoft, Google
Databases and Operating Systems, e.g.
Oracle, SQL, MySQL, Hadoop, Spark, iOS, Android, Linux, Windows
Domain-Specific Data Content, e.g. Health and Healthcare
Software Development Environments, e.g.,
Git, Eclipse, Angular, D3, Mono, Node, Python, R
Amazing capability
Amazing capability
This is the layer of the
Data Operating System
Amazing capability
• Sitting on top of a cloud-based, lake of data
• All of the healthcare and health-related data in your
organization; publicly available health data; and the data of
your health system partners
• >100 different, disparate sources of data, integrated and
bound together in logical groupings
• 100 terabytes of data, and more
• Organized and optimized for software developers to
leverage that data content so they don’t have to
reinvent the wheel
• And the applications they write are contributing data back to
the DOS, enhancing its data content
• Dozens or hundreds of applications of your choice,
meeting your specific needs
Imagine Your Smart Phone…
Using Related Concepts…
DOS is a combination of the following,
but enabled by modern technology,
designs, and software…
1. HIE
2. Clinical Data Repository
3. Enterprise Data Warehouse
DOS is a platform of constantly updated raw and organized
data, from multiple transaction systems, within a domain
such as healthcare, that enables rapid development and
changes to the software applications built upon it.
27
DOS is a Hybrid Architecture
Gartner: Hybrid Transactional/Analytical Processing (HTAP)
“Because traditional data warehouse practices will be outdated by the end of 2018,
data warehouse solution architects must evolve toward a broader data management
solution for analytics.”
29
1. Reusable clinical and business logic: Registries, value sets, and other data logic lies on top of the raw data and
can be accessed, reused, and updated through open APIs, enabling 3rd party application development.
2. Streaming data: Near or real-time data streaming from the source all the way to the expression of that data through
the DOS, that can support transaction-level exchange of data or analytic processing.
3. Integrates structured and unstructured data: Integrates text and structured data in the same environment.
Eventually, incorporates images, too.
4. Closed loop capability: The methods for expressing the knowledge in the DOS include the ability to deliver that
knowledge at the point of decision making, including back into the workflow of source systems, such as an EHR.
5. Microservices architecture: In addition to abstracted data logic, open microservices APIs exist for DOS operations
such as authorization, identity management, data pipeline management, and DevOps telemetry. These
microservices also enable third party applications to be built on the DOS.
6. Machine Learning: The DOS natively runs machine learning models and enables rapid development and utilization
of ML models, embedded in all applications.
7. Agnostic data lake: Some or all of the DOS can be deployed over the top of any healthcare data lake. The
reusable forms of logic must support different computation engines; e.g. SQL, Spark SQL, SQL on Hadoop, et al.
Seven Attributes of a Data Operating System
DOS Can Bridge the Data and Applications
Health Catalyst Applications
Client-Built
Applications
Registry
Builder
Leading
Wisely
Care
Management
CAFÉ
Benchmarks
ACO
Financials
Choosing
Wisely
Patient
Safety
Measure
Library
Patient
Engagement
Catalyst Analytics Platform
Data Ingest Data ExportData Pipelines
Source
Connectors
Hadoop/
Spark
Data Lake
Fabric Real-Time Services
Real-Time
Processing
HL7
Real-Time
Streaming
Machine
Learning
Pipelines
Marketplace
Atlas and more …SAMD & SMD
Fabric Application Services
Registries Terminology
& Groupers
FHIREHR
Integration
Security, Identity
& Compliance
Patient & Provider
Matching
Measures
Fabric Data Services
Data
Governance
Pattern
Recognition
NLP
Data QualityMetadata
Standard
Data Models
ML Models
3rd Party Apps
Reusable
Content
Data Operating Systems, and their recent
predecessors, Enterprise Data Warehouses, cost a
fraction of ripping and replacing EHRs, ERPs, and
other applications
• ~$3M-$5M to install and deploy in a few months
• ~$2M-$3M per year to operate and evolve
• ~$340 per employee vs. $13,000 per employee
for an EHR
What About the Costs?
31
Between 2001 and 2009, they implemented similar concepts to DOS as well
as a “DevOps” culture in software development.
The results in their software were dramatic…
Related Impact at Amazon
• The digital future of healthcare is about data that
persists for a patient’s lifetime, but applications that
last for months or, at most, a few years
• It’s about choice, adaptability, and personal software
preferences
• The wrong IT strategy will haunt M&A value for
decades
• Rip & Replace: Incremental value for massive investment
• Focus on integrating data, not applications, through a
DOS or Enterprise Data Warehouse
The Moral to This Story…

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Mergers, acquisitions, and partnerships dramatically reducing it consolidation expenses with a data operating system

  • 1. Mergers, Acquisitions, And Partnerships Dramatically Reducing IT Consolidation Expenses With a Data Operating System Dale Sanders September 2017 Thanks, Rus Tabet, for graphic
  • 2. • I work for Health Catalyst and the technology we produce is related to the concepts that I advocate in this lecture • The technology strategies and concepts advocated herein, I would also follow myself, if I were still an operational healthcare CIO Disclosure One of our Four Operating Principles
  • 3. • Digitizing healthcare… EHRs we’re just beginning • Mergers, Acquisitions, and Partnerships and IT strategy • What’s a Data Operating System and what role does it play in M&A? Today’s Story
  • 4. 1. For better or worse, faster or slower, your company runs at the speed of software now 2. Everything you want and need to do is either helped or hindered by software and data 3. All C-levels now need to be a little bit Chief Information Officer and Chief Digital Officer Advice to C-levels About a Digital Health Future Thank you, Russel Reynolds Associates for the graphic
  • 5. • The world’s largest taxi company… owns no taxis • The world’s largest voice/video communications companies… own no telco • The most popular media company… owns no content • The largest lodging company… owns no property • The world’s most valuable retailer… owns no inventory • The world’s largest software vendors… don’t write the apps Digital Disruption is Already Happening Thanks for the inspiration, Ron Kalifa of Worldpay; and IBM
  • 6. The world’s largest and most successful healthcare and health management companies, will own no hospitals In the Digital Future of Healthcare…
  • 7. The Parallels Between Health and Car Maintenance An ounce of prevention is worth a pound of cure • Every 10 hours, Tesla collects 1 million miles of driving data • 25Gbytes per car per hour • We collect 100Mbytes per patient per year, on average • “We can fix problems in your car and make it safer, long before you know you need it.” • ”10,000 fatalities and 500,000 injuries per year will be prevented.” • Ram Ramachander, Chief Commercial Officer, Social Innovation Business at Hitachi
  • 8. 80% of Factors Affecting Health Outcomes Fall Outside Traditional Healthcare Delivery
  • 9. The Breadth of the Human Health Data Ecosystem What data do we need for research, personalized care, and community health? And, by the way, we have barely any data on healthy patients
  • 10. Humans Gravitate Towards Freedom of Choice 6 billion smart phones by 2020 in a world population of 8 billion 10
  • 12. In The Meantime, This Is What’s Possible… • 103 applications on my iPhone • 89 different vendors • They build on a common platform with open software standards • I wouldn’t expect nor hope for a single vendor to meet all my needs
  • 13. Mergers, Acquisitions, & Partnerships And the IT strategies that help or hurt
  • 14. • It’s not over… • 11 straight quarters of more than 200 M&As in healthcare, totaling $49.6B • PwC • “Top performers across all industries focus first on data integration and have a plan to do so within six months post- merger.” • “40% of M&A value in healthcare is directly tied to IT strategy.” • McKinsey Mergers, Acquisitions, Partnerships 14
  • 15. • Your new company is not integrated until your data is integrated • HIE’s are not sufficient for data integration… not even close • Ripping and replacing EMRs and ERP systems with a single, common vendor is not an affordable or timely strategy • M&A strategy in the digital world is more about data acquisition than bricks & mortar acquisition– but that’s not happening in healthcare Sanders’ Assertions
  • 16. IT Integration vs. The Technology Stack Computing Infrastructure, e.g., severs, networks, data centers, storage Databases and Operating Systems, e.g. Oracle, SQL, MySQL, Hadoop, Spark, iOS, Android, Linux, Windows Data Content Software Applications, e.g. EHR, HR, Finance, Email, Web, etc. The data content layer is the only layer in the stack that can be “peeled” away without impacting the other layers There is a tendency to start here in healthcare
  • 17. • Economies of scale… more efficient through consolidation of shared services and other infrastructure • Combining scarce resources • Move into complementary markets, by geography or product • Reduce risk through larger populations and revenue • Improve an underperforming organization or asset and thus increase revenue Common Motives Behind M&As in Healthcare 17
  • 18. • There generally isn’t one, other than the hope of administrative savings through IT consolidation • The strategic value of data acquisition is still largely ignored What’s the IT Strategy in Healthcare M&A? 18
  • 19. IT Strategies that Drive M&A Success • The acquirer gets its own IT house in-order, first • Many develop a “Services Oriented Architecture” anticipating the need to be flexible and adaptable • IT leaders are heavily involved in the due diligence prior to acquisition • Forecasts of revenue growth and cost synergies are driven by financial rules of thumb, ignoring the challenges of integrating the business and clinical functions that IT enables • Carefully plan post-merger integration, during due diligence, and factor those into the overall acquisition costs • A data integration plan within 6 months post-merger • Not a systems or application integration plan 10-15% cost savings from a successful IT integration strategy 19
  • 20. • The prevailing solution: Rip and replace • You’ll be finished in 3-4 years, if you’re lucky, and be 74% over-schedule, 59% over-budget, and deliver 56% less value than predicted* • In the meantime… ERP, EHR, and Other Systems Consolidation *McKinsey, 2012; Standish, 2013
  • 21. Costs to Rip & Replace... Just for EHRs These are my personally calculated numbers, based on first-hand experience… • $13K, minimum, per employee • $41K, minimum, per physician • Hundreds of millions of $$ is common That’s one of dozens of application software systems in today’s healthcare systems 21
  • 22. “Will you ever consolidate to a single EHR?” “Oh no, I can’t imagine. We’ve looked at it a few times, but the total costs are in the billions, and for what? Minor incremental value? We’re using our data warehouse and building a software services layer to tie them together until there are better options.” --C-level at the largest for-profit health system in the U.S. 22
  • 23. • The demand for EHRs was stretched by federal incentives. That’s over. • The underlying software and database technology of EHRs was commoditized a long time ago. • We can stretch the lifecycle and value of EHRs with DOS and open APIs, e.g. FHIR. You Can Extend the Life of Existing EHRs With a Good Data Strategy
  • 24. So, What’s a Data Operating System?
  • 25. Back to the Technology Stack 25 Cloud Computing, e.g. Amazon, Microsoft, Google Databases and Operating Systems, e.g. Oracle, SQL, MySQL, Hadoop, Spark, iOS, Android, Linux, Windows Domain-Specific Data Content, e.g. Health and Healthcare Software Development Environments, e.g., Git, Eclipse, Angular, D3, Mono, Node, Python, R Amazing capability Amazing capability This is the layer of the Data Operating System Amazing capability
  • 26. • Sitting on top of a cloud-based, lake of data • All of the healthcare and health-related data in your organization; publicly available health data; and the data of your health system partners • >100 different, disparate sources of data, integrated and bound together in logical groupings • 100 terabytes of data, and more • Organized and optimized for software developers to leverage that data content so they don’t have to reinvent the wheel • And the applications they write are contributing data back to the DOS, enhancing its data content • Dozens or hundreds of applications of your choice, meeting your specific needs Imagine Your Smart Phone…
  • 27. Using Related Concepts… DOS is a combination of the following, but enabled by modern technology, designs, and software… 1. HIE 2. Clinical Data Repository 3. Enterprise Data Warehouse DOS is a platform of constantly updated raw and organized data, from multiple transaction systems, within a domain such as healthcare, that enables rapid development and changes to the software applications built upon it. 27
  • 28. DOS is a Hybrid Architecture Gartner: Hybrid Transactional/Analytical Processing (HTAP) “Because traditional data warehouse practices will be outdated by the end of 2018, data warehouse solution architects must evolve toward a broader data management solution for analytics.” 29
  • 29. 1. Reusable clinical and business logic: Registries, value sets, and other data logic lies on top of the raw data and can be accessed, reused, and updated through open APIs, enabling 3rd party application development. 2. Streaming data: Near or real-time data streaming from the source all the way to the expression of that data through the DOS, that can support transaction-level exchange of data or analytic processing. 3. Integrates structured and unstructured data: Integrates text and structured data in the same environment. Eventually, incorporates images, too. 4. Closed loop capability: The methods for expressing the knowledge in the DOS include the ability to deliver that knowledge at the point of decision making, including back into the workflow of source systems, such as an EHR. 5. Microservices architecture: In addition to abstracted data logic, open microservices APIs exist for DOS operations such as authorization, identity management, data pipeline management, and DevOps telemetry. These microservices also enable third party applications to be built on the DOS. 6. Machine Learning: The DOS natively runs machine learning models and enables rapid development and utilization of ML models, embedded in all applications. 7. Agnostic data lake: Some or all of the DOS can be deployed over the top of any healthcare data lake. The reusable forms of logic must support different computation engines; e.g. SQL, Spark SQL, SQL on Hadoop, et al. Seven Attributes of a Data Operating System
  • 30. DOS Can Bridge the Data and Applications Health Catalyst Applications Client-Built Applications Registry Builder Leading Wisely Care Management CAFÉ Benchmarks ACO Financials Choosing Wisely Patient Safety Measure Library Patient Engagement Catalyst Analytics Platform Data Ingest Data ExportData Pipelines Source Connectors Hadoop/ Spark Data Lake Fabric Real-Time Services Real-Time Processing HL7 Real-Time Streaming Machine Learning Pipelines Marketplace Atlas and more …SAMD & SMD Fabric Application Services Registries Terminology & Groupers FHIREHR Integration Security, Identity & Compliance Patient & Provider Matching Measures Fabric Data Services Data Governance Pattern Recognition NLP Data QualityMetadata Standard Data Models ML Models 3rd Party Apps Reusable Content
  • 31. Data Operating Systems, and their recent predecessors, Enterprise Data Warehouses, cost a fraction of ripping and replacing EHRs, ERPs, and other applications • ~$3M-$5M to install and deploy in a few months • ~$2M-$3M per year to operate and evolve • ~$340 per employee vs. $13,000 per employee for an EHR What About the Costs? 31
  • 32. Between 2001 and 2009, they implemented similar concepts to DOS as well as a “DevOps” culture in software development. The results in their software were dramatic… Related Impact at Amazon
  • 33. • The digital future of healthcare is about data that persists for a patient’s lifetime, but applications that last for months or, at most, a few years • It’s about choice, adaptability, and personal software preferences • The wrong IT strategy will haunt M&A value for decades • Rip & Replace: Incremental value for massive investment • Focus on integrating data, not applications, through a DOS or Enterprise Data Warehouse The Moral to This Story…