Examples of how leading healthcare organizations use analytics to deliver better clinical and business outcomes. These slides were put together by Jack Phillips Co-founder & CEO of the International Institute for Analytics and Tom Davenport, IIA Director of Research and Visiting Professor of Harvard Business School
For more information on how your healthcare company can be helped using analytics follow this link to take the DELTA-Powered Analytics Assessment TM. It measures how well healthcare providers use data for strategic decision making.
http://info.iianalytics.com/healthcarebenchmarking
2. ANALYTICS 3.0:
OPPORTUNITIES FOR HEALTHCARE
July 24, 2013
Jack Phillips
CEO & Co-Founder
Thomas H. Davenport
Research Director
& Co-Founder
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5. THE ANALYTICAL DELTA
Adapted from Analytics at Work, Davenport, Harris and Morison, 2010
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6. LEVELS OF ANALYTICAL MATURITY
Adapted from Analytics at Work, Davenport, Harris and Morison, 2010
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8. ANALYTICS 1.0âTRADITIONAL ANALYTICS
1.0
Traditional
Analytics
⢠Primarily descriptive
analytics and reporting
⢠Internally sourced,
relatively small,
structured data
⢠âBack roomâ teams
of analysts
⢠Internal decision
support
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9. ANALYTICS 1.0âETHOS
âş Stay in the back roomâas far away from decision-makers as
possibleâand donât cause trouble
âş Take your timeânobodyâs that interested in your results anyway
âş Talk about âBI for the masses,â but make it all too difficult for anyone
but experts to use
âş Look backwardsâthatâs where the threats to your business are
âş If possible, spend much more time getting data ready for analysis
than actually analyzing it
âş Keep inside the sheltering confines of the IT organization
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10. ANALYTICS 2.0âTHE BIG DATA ERA
1.0
Traditional
Analytics
Big Data2.0
⢠Primarily descriptive
analytics and reporting
⢠Internally sourced,
relatively small,
structured data
⢠âBack roomâ teams
of analysts
⢠Internal decision
support ⢠Complex, large,
unstructured data sources
⢠New analytical and
computational capabilities
⢠âData Scientistsâ emerge
⢠Online firms create data-
based products and
services
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11. ANALYTICS 2.0âETHOS
âş Be âon the bridgeâ if not in charge of it
âş âAgile is too slowâ
âş âBeing a consultant is the dead zoneâ
âş Develop products, not Power Points
or reports
âş Information (and hardware and
software) wants to be free
âş All problems can be solved in a
hackathon
âş Share your big data tools with the
community
âş âNobodyâs ever done this before!â
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12. ANALYTICS 3.0âFAST BUSINESS IMPACT
FOR THE DATA ECONOMY
1.0
Traditional
Analytics
Fast Business
Impact for the
Data Economy
Big Data2.0
3.0
⢠Primarily descriptive
analytics and reporting
⢠Internally sourced,
relatively small,
structured data
⢠âBack roomâ teams
of analysts
⢠Internal decision
support ⢠Complex, large,
unstructured data sources
⢠New analytical and
computational capabilities
⢠âData Scientistsâ emerge
⢠Online firms create data-
based products and
services
⢠A seamless blend of traditional
analytics and big data
⢠Analytics integral to running the
business; strategic asset
⢠Rapid and agile insight delivery
⢠Analytical tools available at
point of decision
⢠Cultural evolution embeds
analytics into decision and
operational processes
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13. ANALYTICS 3.0âFAST BUSINESS IMPACT
FOR THE DATA ECONOMY
1.0
Traditional
Analytics
Fast Business
Impact for the
Data Economy
Big Data2.0
3.0
⢠Primarily descriptive
analytics and reporting
⢠Internally sourced,
relatively small,
structured data
⢠âBack roomâ teams
of analysts
⢠Internal decision
support
⢠A seamless blend of traditional
analytics and big data
⢠Analytics integral to running the
business; strategic asset
⢠Rapid an agile insight delivery
⢠Analytical tools available at
point of decision
⢠Cultural evolution embeds
analytics into decision and
operational processes
⢠Complex, large,
unstructured data sources
⢠New analytical and
computational capabilities
⢠âData Scientistsâ emerge
⢠Online firms create data-
based products and
services
Today
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14. ANALYTICS 3.0âCOMPETING IN THE DATA
ECONOMY
âş Every organizationânot just online firmsâ
can create data and analytics-based products
and services that change the game
âş Not just supplying data, but insights and
guides to decision-making
âş Use âdata exhaustâ to help customers use
your products and services more effectively
âş Start with data opportunities or start with
business problems? Answer is yes!
âş Need âdata productsâ team good at data
science, customer knowledge, new
product/service development
âş Opportunities and data come at high speed,
so quants must respond quickly
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15. EXPRESS SCRIPTS
ď Uses analytics on data from 1.5 billion
prescriptions/yr to drive behavior change
and process improvement
ď Developing proactive, customized
messages to educate about more cost
effective methods of filling prescriptions
ď Using predictive analytics to identify
patients at risk of skipping doses and
proactively intervene
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16. INTERMOUNTAIN HEALTHCARE
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ď From Brent Jamesâ âscience experimentsâ
to standard treatment protocols for many
diseases and conditions
ď Cost of treatment can be monitored by
clinicians along with other variables
ď Center for Informatics Research offers
software and services (with Deloitte) on
health outcomes analysis based on 90
million EHR records
17. UNITED HEALTHCARE
ď Using social network analysis to identify
potential fraud
ď Analyzing speech-to-text data from call
centers to understand likely attrition
candidates
ď Predicting likelihood of success in disease
management candidates
ď âHealth in numbersâ marketing
ď Optum Insightsâmajor revenue source
from data and analytics
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18. PARTNERS HEALTHCARE SYSTEM
ď Early adopters of EHR, CPOE,
knowledge management
ď Beginning to connect financial,
operational, and clinical analytics
ď Developed and spun out QPID for
extracting intelligence from EHRs
ď Putting in organization-wide EHR
transaction foundation nowâhow to
preserve emphasis on analytics?
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19. CIGNA
ď Broad use of âsmart innovationâ testing
approaches to understand cause-and-
effect from interventions, e.g. disease
management calls
ď Beginning to analyze MyCigna.com web
data and call center speech-to-text
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20. PRESCRIPTION FOR A 3.0 WORLD
ď Start with an existing capability for data
management and analytics
ď Add some unstructured, large-volume data and
product/service innovation
ď Take Hadoop and NoSQL as needed
ď Embed this result into the organizationâs
processes and systems
ď Promote the doctor or pharmacist to Chief
Analytics Officer
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21. RECOMMENDATIONS
CopyrightŠ 2013 IIA All Rights Reserved
âş Use five factors (DELTA), five levels (1-5) to
establish and measure analytical maturity
âş Become a student of the analytics
environment
âş Educate your leaders on potential of analytics
based on what youâre seeing
âş Use IIA as your barometer!
22. DELTA POWERED ANALYTIC ASSESSMENT TM
DEVELOPED IN PARTNERSHIP WITH HIMSS ANALYTICS
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24. LEARN ABOUT THE DELTA-POWERED
ANALYTICS ASSESSMENT TM
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http://info.iianalytics.com/healthcarebenchmarking
25. ANALYTICS 3.0 RESOURCES
http://iianalytics.com/a3/
Research Note & Diagram
Research Brief
Frequently Asked Questions
E-book
Blogs
IIA Members can download âBig Data in Big Companiesâ from
client website.
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26. JOIN US FOR THE NEXT IIA WEBCAST
August 22 Improving analytic results with decision modeling
James Taylor, IIA Faculty and CEO of Decision
Management Solutions
Register at iianalytics.com
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Jack â 18 named to Honor Roll overall, 3 IIA clients in the top 10.We know in our guts that the investment in analytics
Jack
Jack
Jack
Jack â transition to Tom
Tom
Tom
Tom
Tom â main point â we agree that Big Data is still the topic of the day. But, weâre pointing to a future state that we think will become the norm.
Express Scripts, Inc., one of the largest pharmacy benefit management companies in North America, See article for more detailsPharmacy benefit management firm Express Scripts is rolling out a software service to identify patients at high risk for not following their medication regime.The firm calls the service ScreenRx and has tested it in a large-scale pilot program with 600,000 members. The pilot is scaling down and Express Scripts during the summer expects to start making the service available, initially focusing on members with high blood pressure, high cholesterol, diabetes, asthma and osteoporosis.The pilot testing found that 69 percent of non-adherence cases are caused by forgetfulness and procrastination, 16 percent because of the cost of medication and 15 percent because of clinical questions or concerns a patient has about the medication or disease.Express Scripts uses more than 400 known factors about patients, their physician, the disease and prescribed therapy, and contends ScreenRx is 98 percent accurate in predicting non-adherence one year in advance. Patients identified as being at-risk because of forgetfulness or procrastination may receive daily alerts to take the medication, 90-day prescriptions or auto-renewals.Eliminating non-adherence would save an estimated $317.4 billion annually, enough to cover insurance costs for 44.8 million Americans, according to the firm.Â
Big Data at United HealthcareUnited Healthcare, like many large organizations pursuing big data, has been focused on structured data analysis for many years, and even advertises its analytical capabilities to consumers (âHealth in Numbersâ). Now, however, it is focusing its analytical attention on unstructured dataâin particular, the data on customer attitudes that is sitting in recorded voice files from customer calls to call centers. The level of customer satisfaction is increasingly important to health insurers, because consumers increasingly have choice about what health plans they belong to. Service levels are also being monitored by state and federal government groups, and published by organizations such as Consumer Reports.  In the past, that valuable data from calls couldnât be analyzed. Now, however, United is turning the voice data into text, and then analyzing it with ânatural language processingâ software. The analysis process can identifyâthough itâs not easy, given the vagaries of the English languageâcustomers who use terms suggesting strong dissatisfaction. A United representative can then make some sort of interventionâperhaps a call exploring the nature of the problem. The decision being made is the same as in the pastâhow to identify a dissatisfied customerâbut the tools are different. To analyze the text data, United Healthcare uses a variety of tools. The data initially goes into a âdata lakeâ using Hadoop and NoSQL storage, so the data doesnât have to be normalized. The natural language processingâprimarily a âsingular value decompositionâ, or modified word countâtakes place on a database appliance. A variety of other technologies are being surveyed and tested to assess their fit within the âfuture state architecture. United also makes use of interfaces between its statistical analysis tools and Hadoop. The work to put the customer satisfaction data, along with many other sources of customer data, into a customer data warehouse and analyze it is being led by Mark Pitts, who is based in the Finance organization. However, several other functions and units of United, including its Optum business specializing in selling data and related services to healthcare organizations, are participating. Pittâs team includes both conventional quantitative analysts and data scientists with strong IT and data management skills.