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© 2015 Health Catalystwww.healthcatalyst.com
April 2015Dale Sanders
Microsoft: A Waking Giant In Healthcare Analytics and Big Data
Creative Commons Copyright – Attribution Required
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“In today’s world, business moves at the speed of software.” -- Dale Sanders
Great people and great facilities are not enough anymore.
Software is the enabling or disabling factor to success in today’s business world.
Why should C-levels care about topics like this one?
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For ExampleThink about the impact that good and bad software is having on the speed of these critical business transformations in healthcare, alone
• Healthcare.gov
• Population Health Management
• Accountable Care & Value Based Reimbursement
• EHR interoperability
• Detailed cost accounting
• Patient engagement
• Analytics at the point of care that can help raise quality of care, lower cost of care, and speed translational research
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On a scale of 1-5, what is your overall perception of Microsoft as a company– its people, products, and culture? 307 respondents
1. Very negative – 3%
2. Negative – 10%
3. Neutral – 32%
4. Positive – 45%
5. Very positive – 11%
Poll Question
Agenda• My up and down experiences with Microsoft
• Microsoft’s cultural and technological transformation
• Microsoft’s analytics options
• SQLServer, PDW, APS
• Microsoft Azure
• PowerX product line
• Data visualization and manipulation tools
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© 2015 Health Catalystwww.healthcatalyst.comProprietary and Confidential
My Life On Microsoft
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A few times, I wanted to poke my eye out
Thank you for the cartoon, Darren Merinuk
© 2015 Health Catalystwww.healthcatalyst.comProprietary and Confidential
Analytic Roadmaps for Healthcare
9*-- Sanders D, Protti, D, Electronic Healthcare, 11(2) 2012: e5-e6
Poll QuestionAt what Level does your organization consistently and broadly operate in the Analytics Adoption Model? 248 respondents
0 – 14%
1-2 – 34%
3-4 – 33%
5-6 – 14%
7-8 – 5%
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“Closed Loop Analytics”“Presenting data in the workflow of decision making, such that the data optimizes the outcome of the decision.” (Sanders, HIMSS 2015 )
Physicians are 15x more likely to modify their decisions about patient orders and protocols if presented with data at the point of care, as opposed to presenting data in “offline” clinical quality improvement meetings. (Komomoto, BMJ, 2007)
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Embedded best practices, decision support & care team coordination that support the Triple Aim
EHR embedded popula-tion analytics tailored for personalized medicine at the point of care
EHRClinical Decision Support
EDWClinical Quality Analytics
Define clinical best practices & requirements for embed-ded decision support & care team coordination
Use aggregate views of clinical data for case mix & protocol optimization
Derive population-based health system models for predicting demand
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Executive & Clinical Leadership
Create a cultural expectation for evidence based medicine and use of clinical pathways & standard protocols
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Enterprise Clinical Teams
Act on process & outcome data using protocol-based practice standards Identify new cohorts & gauge practice variations
Clinical, EHR & Analytical Teams
Generate comparative & outcomes data, implement order sets, protocols and decision support rules. Develop & validate clinical models 4
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Start Here
‘Closing the Loops’ on Clinical Outcomes to Optimize QualityUsing an Electronic Health Record, Enterprise Data Warehouse & Clinical Analytics to Generate Local Evidence
Information SystemsSupporting DataDecisions & Actions
© 2015 Contributing authors, listed alphabetically: Eggert C, Moselle K, Protti D, Sanders D.
Align practice informed by analytics
Tailor protocols using better data
Man
age
Serv
ices
Opti
mize
Cap
acity
Deliv
er C
are
Loop A: Patients
Loop B: Protocols
External Evidence Literature, Research
Other Data SourcesExternal, Financial
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Internal Evidence
Internal Evidence
EHR: Electronic Health RecordEDW: Enterprise Data WarehouseMTTI: Mean time to improvementSOPA: Span of providers affected
COptimize system on quality & cost
Loop C: Populations
Internal Evidence
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Confidential DraftMar 21, 2015
Previous Box 6: Assess data quality, cohorts & interventions linked to outcomes
Include socio-economic determinants of health in clinical care management best practices
CLINICAL QUALITY GOVERNANCESet improvement priorities 1
“Closed Loop Analytics”Mean Time To Improvement and Span of Population Affected
Loop C: Populations● MTTI: Years, decades● SPA: Millions, several hundred thousand
● Analytic consumers: Board of Directors, executive leadership team, Strategic plans and policy
Loop B: Protocols● MTTI: Weeks, months● SPA: Subsets of patients– hundreds, thousands● Analytic consumers: Care improvement teams, clinical service lines
Loop A: Patients● MTTI: Minutes, hours● SPA: Individual patients● Analytic consumers: Physicians and patients at the point of care
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Big vs. Small DataThe ROI of data to Population Health
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Volume, Ability, ActThe volume of data far outpaces our ability to analyze and act on data… but we think otherwise
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Finding optimal data volume
© 2015 Health Catalystwww.healthcatalyst.comProprietary and Confidential
Microsoft’s Cultural and Technological Transformation
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The Innovator’s DilemmaMicrosoft has shown the repeated ability to overcome this…
Sacrificing the Sacred Cows
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Microsoft Openness
• Over the last three years, the single largest contributor of code to Open Source• 20% of Azure infrastructure runs on Linux• .Net is now in the Open Source community• Tight integration with Hadoop through Hortonworks• Support for Dockers containers• Microsoft owns 310 Android patents• Supports Facebook’s Open Compute data center project• Third largest contributor to the Linux kernel
Steve Ballmer, 2001: “Linux is a cancer”
Satya Nadella, 2014: “Microsoft loves Linux”
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© 2015 Health Catalystwww.healthcatalyst.comProprietary and Confidential
Microsoft’s Analytics Options In The New World
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The Transition Period• Too early to go all-in on Hadoop & NoSQL• Too late to go all-in on relational databases• You have to straddle both and this is where Microsoft’s products and
strategy excel
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Microsoft’s Analytics Product LinesLots of good, familiar patterns and integration across these products
PowerBIExcelPowerViewPowerMPowerQ&APowerQueryPowerPivot
The Future of Computing: Azure
Hybrid Architecture: Analytics Platform Services (APS)
Old Reliable on Steroids: Parallel Data Warehouse (PDW)
Old Reliable: SQLServer
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Price-Performance Numbers*• EMC Greenplum
• IBM PureData
• Microsoft PDW
• Oracle Exadata
• Teradata Data Warehouse Appliance
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* -- Thank you, Value Prism Consulting, Oct 2013
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© 2015 Health Catalystwww.healthcatalyst.comProprietary and Confidential
Hybrid Architecture:Analytics Platform System (APS)
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Microsoft APS (Analytics Platform System)A brilliant hybrid architecture
Polybase Bridges The Skills Gap
Thank you John Kreisa, Hortonworks
HDInsight = Hortonworks in Microsoft APS
Thank you, James Serra
Interactive Analytics Delivered To Any Device
• Native apps for iPad, iPhone, and Windows devices
• Receive alerts to important changesin your data
• Share and collaborate with colleagues and take immediate action
© 2015 Health Catalystwww.healthcatalyst.comProprietary and Confidential
Azure: The Future of Computing
What is Azure?
One of the key missing concepts in this definition is that Azure is a hybrid cloud, meaning you can bridge data and applications between on-premise and the Azure cloud.
As of April 11, 2015, there are 3,019 applications in the Azure Marketplace. These are overwhelmingly business-level apps, not consumer apps as we are accustomed to in the Apple and Google app stores.
Azure is Big and Mature
Huge Azure Infrastructure
100+ datacentersOne of the top 3 networks in the world (coverage, speed, connections) 2x AWS and 6x Google number of offered regions
Operational Announced
Central USIowa
West USCalifornia
North EuropeIreland
East USVirginia
East US 2Virginia
US GovVirginia
North Central US
Illinois
US GovIowa
South Central US
Texas
Brazil South
Sao Paulo
West EuropeNetherlands
China NorthBeijing
China SouthShanghai
Japan East
Saitama
Japan WestOsaka
India West
India East
East AsiaHong Kong
SE AsiaSingapore
Australia West
Melbourne
Australia East
Sydney
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Azure Security, Privacy, Compliance
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• ISO 27001/27002 Audit and Certification
• SOC 1/SSAE 16/ISAE 3402 and SOC 2 Attestations
• Cloud Security Alliance (CSA) Cloud Controls Matrix (CCM)
• Federal Risk and Authorization Management Program (FedRAMP)
• Federal Information Security Management Act (FISMA)
• Federal Bureau of Investigation (FBI) Criminal Justice Information Services (CJIS)
• Payment Card Industry (PCI) Data Security Standards (DSS) Level 1
• United Kingdom G-Cloud OFFICIAL Accreditation
• Australian Government Information Security Registered Assessors Program (IRAP)
• Multi-Tier Cloud Security Standard for Singapore (MTCS SS 584:2013)
• HIPAA Business Associate Agreement (BAA)
• EU Model Clauses
• Food and Drug Administration 21 CFR Part 11
• Family Educational Rights and Privacy Act (FERPA)
• Federal Information Processing Standard (FIPS)
• Trusted Cloud Service Certification developed by China Cloud Computing Promotion and Policy Forum (CCCPPF)
• Multi-Level Protection Scheme (MLPS)
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The Visualization and Analysis LayerPart desktop, part cloud, part mobile
Natural Language Queries
Closing Thoughts• Business moves at the speed of software
• Older C-levels don’t generally grasp this… I’m old so I can say that
• I don’t impress easily when it comes to IT vendors, especially Microsoft
• History will show that the new Microsoft is one of the biggest cultural and technological re-toolings of all time
• Their hybrid “data lake” analytics and big data vision and execution are unmatched
• Azure is the future of computing• It’s going to completely disrupt organizational IT strategies and
the role of the CIO, in a good way