Big data is more than just a buzzword in healthcare. It's the promise of being able to extract, cull, and interpret medical data to directly benefit population and individual health. learn more about the benefits of big data, roadblocks to leveraging it's potential, how Meaningful Use enablesbig data, what types of cross-country collaboration projects are advancing the use of big data on an international scale, big data's impact on patient privacy and much more! Special thanks to Mandi Bishop for her time on the podcast.

1. M2SYS Healthcare Solutions
Free Online Learning Podcasts
Mandi Bishop, Principal, Adaptive Project Solutions
Topic: “Big Data” in Healthcare: What it Means, How it
Promises to Reshape Healthcare, Roadblocks to Extract
Meaningful Information, How Meaningful Use Enables Big
Data, Cross-Country Collaboration, Effect on Population
Management, Impact on Privacy, & More!
Podcast length – 45:13

2. Topics Covered in Podcast:
Defining Big Data & Identifying the Main Drivers
How Does Big Data Promise to Reshape Healthcare?
Primary Roadblocks for Providers to Extract Meaningful
Information from Big Data
How Meaningful Use Enables Big Data Techniques to be Used in
Healthcare
The “Health Cloud” Initiative & More on Aggregated Big
Data Platforms

3. Topics Covered in Podcast (continued):
Big Data’s Implications on Patient Privacy
Most Effective Security Technologies to Protect Patient Data
Access
The Role of Biometric Identification Technology in Health
Information Exchanges

4. Defining Big Data and Identifying the Main Drivers
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“Big Data” encompasses petabytes and petabytes of patient data
information (clinical data, claims data, personal health record data,
quantified self data)
Several advances in technology have manifested the Big Data movement:
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Computing power
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Connectivity speed
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Faster query times
All of these advances have allowed healthcare to leverage big data
analytics in a way that was not possible 10 years ago
Big data will continue to become more applicable to healthcare as the
move from paper to electronic health records continues
Healthcare as an industry has hampered itself in its use of big data
analytics by not standardizing data capture mechanisms until recently
Data capture standardization is creating opportunities for downstream big
data analytics across clinical and claims continuum

5. Defining Big Data and Identifying Main Drivers
(continued)
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Up until the advent of the Health Insurance Portability & Accountability
Act (HIPAA), healthcare facilities were responsible for maintaining data
internally
The expectation has shifted towards hospitals sharing data outside of their
four walls with external entities creating larger and larger data sets
Effective analytics must come from standard data formats and clinical data
sets must speak the same vocabulary (semantic interoperability) and
currently this does not exist
Opportunity exists for big data to address the quality of patient care
Big data stands to make a significant impact on chronic disease treament
Fiscal incentives and financial aspects of big data analytics are what is
currently driving the healthcare industry until we figure out a way to tie a
definition of quality to clinical outcome improvement

6. How Does Big Data Promise to Reshape Healthcare?
Population Health Management
• Population management – moving away from a fee-for-service payment
model and moving towards value based pricing and population cost
management will provide an opportunity to identify trends – locating
outliers and correlations in large data sets for example
• When dealing with population as a whole, big data may provide ability
to identify a more effective treatment protocol than a more closely
controlled trial size of population
• Accountable Care Organizations (ACOs) may also have impact on
identifying previously unforeseen correlative relationships
• There is both opportunity and risk
• Large data sets allow ACOs to manage member risk similar to insurance
companies
• Big data enables the more rapid assessment of clinical trials
• Population health management should begin to shift away from a focus on
cost and more towards a focus on health & improved quality of life

7. How Does Big Data Promise to Reshape Healthcare?
(continued)
Personalized Medicine
• Personalized medicine – proteomics, genomics, quantified self movement
has the ability to be drastically effected by big data – e.g. personalized
gene therapy
• Information gleaned from big data in population management trickles
down to individualized medicine
• Analyzing the care coordination across a provider network can be applied
to personalized medicine
Did you know?
It doesn’t matter the size of your company, big
data is an area must be carefully examined as
you grow. According to a recent online poll, 76%
of small businesses view big data as an
opportunity for growth.

8. Primary Roadblocks for Providers to Extract
Meaningful Information from Big Data
• #1 and most obvious reason is money – healthcare providers aren’t funded
like insurance companies – it takes a significant information technology
investment to enable effective analytics
• Smaller healthcare providers may not have access to those kind of
funds
• Smaller providers may not have the ability to invest in data analytics IT
infrastructure unless they join larger Integrated Delivery Networks
(IDNs) to leverage cost sharing
• Paper process is still a significant barrier
• A lack of universal standards for clinical data remains a barrier
• Not all hospitals use HL7 clinical data capture language and some are still
communicating in proprietary formats
• Incentives to stay proprietary because of patent issues, treatment
protocols are additional barriers

9. How Meaningful Use Enables Big Data Techniques to
be Used in Healthcare
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There are a few components of Meaningful Use that are integral for
effective big data analytics:
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Data capture – Meaningful Use guidelines require that specific
clinical data elements be captured in a standard format
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Interoperability – Meaningful Use standardizes the transport
mechanisms between electronic health record (EHR) systems –
helps to amass a set of meaningful analytics and apply that to
population management
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Patient engagement – patients will have the ability to get full
medical records in the same format from disparate providers

10. The “Health Cloud” Initiative & More on Aggregated
Big Data Platforms
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“Health Cloud” is a joint effort by U.S. (MedRed) and UK (BT Health) – it’s
an open data repository of approximately 50 million people and 5 years
of data that includes:
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Clinical encounter
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Pharmacy utilization
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Outcomes
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Desire to include CMS & FDA event reporting data sets
Hope is that larger data set will help to proactively identify larger
problems – (e.g. – the possibility of predicting the next FDA recall)
Tremendous opportunity especially if contextual data is layered in down
the road (e.g. – geographic, demographic, even weather data – anything
that can potentially impact health)
Expect to see more initiatives like the “Health Cloud” as the public
demand rises and data capture tools improve
Currently, “Health Cloud” efforts are primarily focused on
pharmaceutical industry – expect to see shift in next couple of years

11. The “Health Cloud” Initiative & More on Aggregated
Big Data Platforms
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Expect to see more cross country collaboration on big data in healthcare
moving forward
Other countries have already been leveraging the power of big data in
healthcare longer and more effectively than the U.S. because the U.S.
market has been so focused on privacy and data silos
Clinical data standards that cross countries like HL7 – as we continue to
develop multi-language and improved language capabilities, and natural
language processing, collaborations will become very effective and
provide us with global data sets – helps to look at the human population
as a whole

12. Big Data’s Implication on Patient Privacy
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Big data can be a frightening concept, especially for those with low
medical literacy
Patients are legitimately concerned that specific types of sensitive data
will be shared amongst entities without their permission (e.g. – some
patients prefer that their mental health data not be shared with their
primary care provider or lab results going to an insurance payor)
Patients themselves limit the efficacy of the information listed on their
own individual medical record through opt-outs
Privacy in healthcare is a double edged sword:
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Fines/penalties in place for data breaches are significant and there
is a much larger data set available now for patients who do opt-in
and are victims of breach
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Health Information Exchanges (HIEs) have opened the door for
larger breaches and exposure to sensitive information that is
detrimental to patient privacy
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However, the sharing of data amongst providers is helping to
contribute to better care coordination & clinical decision support

13. Most Effective Security Technologies to Protect
Patient Data Access
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The shift from paper to electronic health records necessitates a shift
change in how to effectively protect patient data
Patient data information used to be limited and siloed – the advent of
EHR’s, HIEs, Meaningful Use mandates, and an increased interest in
leveraging the power of big data to perform population management
has increased the availability of electronic information that is easier to
transport (and steal)
Critical that a security protocol be in established & observed to:
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Validate a patient’s identity & ensure they are who they say they are
both in person and online (e.g. – patient portals)
Biometrics for patient identification is increasing and a viable tool to
verify a patient’s identity with near 100% accuracy – can also be used at
each touch point along the continuum of care to authenticate identity
before service/procedure is rendered

14. The Role of Biometric Identification Technology in
Health Information Exchanges
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Tremendous opportunity for biometrics to play a critical role in uniquely
identifying a patient
Universal standards on the use of biometrics for identification are still
evolving & could temporarily hamper the rapid pace of adoption
Biometrics are proving to be the easiest and most definitive way to
validate a patient’s identity
The judicious application of biometrics that follows standards with an
alternative in place for providers who can’t afford to leverage biometrics
is critical for wider adoption
Did you know?
Not all biometric identification solutions are the
same. When researching which is best for you,
make sure that no patient contact is needed to
support hospital infection control and the back
end matching is one-to-many.

15. Thank you to Mandi for her time and
knowledge for this podcast!
Please follow Mandi on Twitter
(@mandibpro) and visit her LinkedIn page
under: Adaptive Project Solutions

16. Contact Information
John Trader
PR and Marketing Manager
M2SYS Healthcare Solutions
1050 Crown Pointe Pkwy.
Suite 850
Atlanta, GA 30338
jtrader@m2sys.com
770-821-1734
www.m2sys.com/healthcare
Podcast home page: http://www.m2sys.com/healthcare/healthcare-biometricspodcasts/
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