Accelerating Insights in Healthcare with “Big Data” with HaDoop , use case description of Hadoop at IBC ( Independence Blue Cross, Alex Zeltov and Darwin Leung speakers for IBC)

1. Accelerating Insights in Healthcare
with “Big Data” with HaDoop - 4152
Ed Macko – CTO Healthcare
Darwin Leung – Director of Informatics Applications, IBC
Alex Zeltov – Research Scientist, IBC
Joel Vengco – CIO, Baystate
© 2014 IBM Corporation

2. Please Note
• IBM’s statements regarding its plans, directions, and intent are subject to change or
withdrawal without notice at IBM’s sole discretion.
• Information regarding potential future products is intended to outline our general
product direction and it should not be relied on in making a purchasing decision.
• The information mentioned regarding potential future products is not a commitment,
promise, or legal obligation to deliver any material, code or functionality. Information
about potential future products may not be incorporated into any contract.
• The development, release, and timing of any future features or functionality described
for our products remains at our sole discretion.
Performance is based on measurements and projections using standard IBM benchmarks
in a controlled environment. The actual throughput or performance that any user will
experience will vary depending upon many factors, including considerations such as
the amount of multiprogramming in the user’s job stream, the I/O configuration, the
storage configuration, and the workload processed. Therefore, no assurance can be
given that an individual user will achieve results similar to those stated here.
2

3. Acknowledgements and Disclaimers
Availability. References in this presentation to IBM products, programs, or services do not imply that they will be available in all countries in
which IBM operates.
The workshops, sessions and materials have been prepared by IBM or the session speakers and reflect their own views. They are provided for
informational purposes only, and are neither intended to, nor shall have the effect of being, legal or other guidance or advice to any participant.
While efforts were made to verify the completeness and accuracy of the information contained in this presentation, it is provided AS-IS without
warranty of any kind, express or implied. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this
presentation or any other materials. Nothing contained in this presentation is intended to, nor shall have the effect of, creating any warranties or
representations from IBM or its suppliers or licensors, or altering the terms and conditions of the applicable license agreement governing the use
of IBM software.
All customer examples described are presented as illustrations of how those customers have used IBM products and the results they may have
achieved. Actual environmental costs and performance characteristics may vary by customer. Nothing contained in these materials is intended to,
nor shall have the effect of, stating or implying that any activities undertaken by you will result in any specific sales, revenue growth or other
results.
© Copyright IBM Corporation 2014. All rights reserved.
— U.S. Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract
with IBM Corp.
— Please update paragraph below for the particular product or family brand trademarks you mention such as WebSphere, DB2,Maximo,
Clearcase, Lotus, etc
IBM, the IBM logo, ibm.com, [IBM Brand, if trademarked], and [IBM Product, if trademarked] are trademarks or registered trademarks of
International Business Machines Corporation in the United States, other countries, or both. If these and other IBM trademarked terms are marked
on their first occurrence in this information with a trademark symbol (® or TM), these symbols indicate U.S. registered or common law
trademarks owned by IBM at the time this information was published. Such trademarks may also be registered or common law trademarks in
other countries. A current list of IBM trademarks is available on the Web at
•“Copyright and trademark information” at www.ibm.com/legal/copytrade.shtml
•If you have mentioned trademarks that are not from IBM, please update and add the following lines:[Insert any special 3rd party trademark
names/attributions here]
•Other company, product, or service names may be trademarks or service marks of others.
3

4. IBM Smarter Care uncovers valuable insights into lifestyle choices, social
determinants, clinical and financial factors that effect the overall health of
an individual …
Social
Demographic determinants such as
where one is born, grows, lives, works
and ages have direct impact on an
individual’s overall health, mental
health and well-being.
Lifestyle
Choices have direct impact on an
individual’s mental and physical
wellness.
Clinical
Factors such as specific medical symptoms,
history, medications, diagnoses, etc are
indicators of an individual’s health.
Financial
Costs, insurance, reimbursement, incentive
to modify behavior, new payment models,
co-pays, etc. will pay a significant role.

5. Every organization is on its own
analytics journey
Foundational
• What happened?
• When and where?
• How much?
Advanced, Predictive
• What will happen?
• What will be the
impact?
•Dashboards
•Clinical data repositories
•Departmental data marts
•Enterprise data warehouse
BI Reporting
•Enterprise analytics
•Unstructured content analytics
•Outcomes analytics
•Evidence-based medicine
Population Analytics
•Streaming analytics
•Similarity analytics
•Personalized healthcare
•Consumer engagement
•Cognitive Computing
Care Optimization
Prescriptive
• What are potential
scenarios?
• What is the best course?
• How can we pre-empt and
mitigate the crisis?

6. • How are you measuring and
reducing preventative
readmissions?
• How are you providing
clinicians with targeted
diagnostic assistance?
• Which patients are
following discharge
instructions?
• How are you using data to
predict intervention
program candidates?
• Would revealing insights
trapped in unstructured
information facilitate more
informed decision making?
 Physician notes and discharge summaries
 Patient history, symptoms and non-symptoms
 Pathology reports
 Tweets, text messages and online forums
 Satisfaction surveys
 Claims and case management data
 Forms based data and comments
 Emails and correspondence
 Trusted reference journals including portals
 Paper based records and documents
Over 80% of stored health
information is
unstructured*
Does unlocking the unstructured data
help accelerate your transformation?
... Biggest blind spot still remains unstructured data

7. 7
BIOGRAPHY
Independence Blue Cross
 Darwin Leung
 Director, Informatics Application Development and Operations
 Responsible for the development of analytical applications across
the Informatics Division for Independence Blue Cross.
 Alex Zeltov
 Research Scientist, Advanced Analytics
 Lead the development and research of Big Data initiative and
predictive analytics.
 Contact Info:
 Email: darwin.leung@ibx.com / Phone:215.241.2255
 Email: alex.zeltov@ibx.com / Phone: 215.241.9885

8. I ndependence and i t s subsi di ar i es and af f i l i at es
Dat a
War ehous e
We ser ve mor e t han 7 mi l l i on peopl e i n 24 st at es as wel l as t he Di st r i ct of Col umbi a – 4
mi l l i on t hr ough our medi cal cover age and admi ni st r at i ve ser vi ces, and 3 mi l l i on t hr ough
phar macy, dent al , and vi si on cover age and ot her anci l l ar y pr oduct s.
AmeriHealth Caritas
AmeriHealth
Administrators
AmeriHealth
Administrators
AmeriHealth Caritas
AmeriHealth Caritas
AmeriHealth Caritas and
AmeriHealth Administrators
AmeriHealth Caritas
AmeriHealth
AmeriHealth Caritas
AmeriHealth
Administrators
AmeriHealth Caritas
AmeriHealth Caritas
PA & NJ Market
Independence Blue Cross
AmeriHealth
AmeriHealth Administrators
CompServices
AmeriHealth Caritas
AmeriHealth Caritas
AmeriHealth Caritas
AmeriHealth and AmeriHealth
Administrators
AmeriHealth
Administrators
Medical, service, and ancillary
Medical and ancillary
Service and ancillary
Medical
Service
Ancillary
AmeriHealth Caritas and
AmeriHealth Administrators
AmeriHealth Caritas and
AmeriHealth Administrators
AmeriHealth
Caritas

9. What are key business drivers that
require “Big Data” solution @ IBC ?
 Apply text analytics to all information available for different
business cases.
 Need to bring all information (structured and instructed) to a level
where our technologies can be applied.
 Use advanced predictive analytics for various business use cases.
 Apply search technologies to all of our structured and unstructured
data

10. Business Cases
 Product Recall
 Nurse Chart Review Process
 Predictive models:
– Customer complaints / grievances
– Diabetes
– Likelihood of hospitalization
 Sentiment analysis
 Text Search on Electronic Medical Records/Data

11. Business Case: Product Recall

12.  The text mining process helps identify the manufacturers that are on
recall list.
 Scheduled report alerts with potential identified members that match
the recall manufacturers.
 Create a database of extracted patient and manufacturer information.
 The OCR + Text mining process analyzes charts 300+ pages long on
average
 Generated reports on the OCR results in IBM BigSheets
Business Case: Product Recall

13. Nurse Chart Review Process
 The text mining process helps identify conditions and diagnoses
based on the medical ontology matches for the nurse review.
 The text analytics priorities the charts for nurse review, the highest
scored EMR charts are presented first for the nurse review process.
 The nurse has the ability to open the text version of the chart that
was created part of the OCR process to the exact location of the
matched terms in the scanned version of chart.

14. Predictive models:
Customer complaints / grievances
Diabetes
Likelihood of hospitalization
14

15. CTM and Grievances Rates
15
 Issue: Identify Members with a High Likelihood to file a
CTM/Grievance
 Results:
– Customer Satisfaction
– STAR Ratings

16. Likelihood to File a CTM : Pre-Intervention
16
Likelihood to File a CTM
0
.50
1.0
Unlikely Very Likely
.25
.75
David
Pierce
John Doe
Barbara
Wilson
Jessica
Smith
Mary Miller
“Benefits
”
“Upset
”
“Bill”

17. Outreach Intervention
17
17
“Hello John Doe. I see that you called
yesterday about a billing issue. How can I
assist you?

18. Likelihood to File a CTM : Post-Intervention
18
18
Likelihood to File a CTM
0
.50
1.0
Unlikely Very Likely
.25
.75
David
Pierce
John
Doe
Barbara
Wilson
Jessica
Smith
Mary Miller
“Positive
Interventio
n”
“Great
Customer
Experience
”
“Better
Stars
Rating”

19. 19
BIOGRAPHY
 Joel Vengco
 Chief Information Officer
 Baystate
 Responsible for xxxxthe development of analytical applications
across Baystate
 Contact Info:
 Phone:xxx.xxx.xxxx
 Email: joel.vengco@baystate.com

20. Who is Baystate ?
 Give 1 page overview of Baystate (who do you serve, # provider, #
patients, demographics, etc. )

21. Q & A

22. Thank You