The document discusses how healthcare organizations are becoming increasingly data-driven. It notes that there is an estimated 50 petabytes of healthcare data, much of which is unstructured, and stored across hundreds of different sources like medical images and lab results. Integrating medical devices with electronic health records could save over $30 billion per year while improving patient care. However, only a third of hospitals currently integrate devices with EHRs. The large amount of data from various sources presents challenges around data quality, fragmentation, accuracy, and security. Healthcare organizations are increasingly relying on data and analytics to support population health, deliver best practices, increase patient engagement, and move from volume-based to value-based care. Clean, connected, and secure data

1. The Healthcare Organization
of the Future will be Data-Driven
of health data is unstructured
and stored in hundreds of forms
such as lab results, images, and
medical transcripts.180%
petabytes
There is an estimated
50 petabytes of data
in the healthcare realm2
Improving interoperability between
medical devices and EHRs in
hospitals could save more than
$30 billion a year while improving
patient care and safety.6
$30B4.9M
Devices such as defibrillators, electrocardiographs,
vital signs monitors, ventilators and infusion pumps.
of hospitals use 6 or more types of devices that
could be integrated with EHRs.3
90%+
33.3%
Yet only a third of hospitals integrate any medical
devices with EHRs, and those that do, usually
integrate only 3 types of devices.3
On average, patient monitoring
equipment pumps out 1000
readings per second, or
86400 readings per day.4
EHR
4.9 million patients
worldwide will use remote
monitoring devices by 2016.5
1000
Improvements in care and operational efficiencies will be realized when healthcare data, from every source,
is leveraged.
1
http://www.zdnet.com/within-two-years-80-percent-of-medical-data-will-be-unstructured-7000013707/
2
http://www.scribd.com/doc/107279699/Big-Data-in-Healthcare-Hype-and-Hope
3
http://www.informationweek.com/interoperability/medical-device-ehr-integration-could-save-$30b-study/d/d-id/1109208?
4
http://info.healthdirections.com/blog/bid/330034/Infographic-Big-Data-is-Healthcare-s-Biggest-Threat-And-Likely-Savior
5
http://mobihealthnews.com/15487/berg-2-2m-patients-remotely-monitored-globally/
6
http://www.informationweek.com/interoperability/medical-device-ehr-integration-could-save-$30b-study/d/d-id/1109208
7
http://www.informationweek.com/healthcare/clinical-information-systems/healthcare-analytics-sought-for-population-health-management/d/d-id/1111071?page_number=1
8
http://www.informationweek.com/healthcare/clinical-information-systems/hospitals-seek-analytics-tools-in-rush-to-meet-mandates/d/d-id/1105906?
9
http://www.ajmc.com/publications/issue/2013/2013-1-vol19-n7/Healthcares-Big-Data-Challenge
10
http://www.experian.com/blogs/data-breach/2013/05/01/medical-data-breaches-a-source-of-chronic-pain/
2 Data Fragmentation:
Healthcare data quality is concerning for 2 reasons:
Manual entry
introduces intentional
and unintentional
systematic errors.9
Even if we achieve
perfect data accuracy;
data fragmentation
remains.9
Incomplete data, like inaccurate data, can also lead to missed or spurious associations that can be wasteful or even harmful
to patient care. These issues need to be addressed in order to ensure that insights from electronic clinical data are valid.9
1 Human Error:
of hospitals exposed by a breach in the
past 2 years.10
of medical devices are vulnerable to
hackers because they are not secure.10
69%
94%
patients have had records exposed
in healthcare data breaches.10
total records exposed in data breaches
in Quarter 1 2013.10
874,667
21.7M
10% of hospitals implemented data analytics tools in 2011,
50%+ are predicted to do so by 2016.8
82% of respondents of a CIO survey identified population health
management (PHM) as a key focus of analytics in coming years.7
Nearly 80% felt that leveraging big data and predictive
analytics was important to their organization's goals.7
Analytics will reveal insights. However, the quality of the decisions you make will mirror the quality of the
data fed into the analytics. Clean, safe and connected data is required for confident decision making.
Data needs to be clean and connected.
Data needs to be safe.
This is where data infrastructure comes in
Transformed Healthcare organizations rely on data to:
Support population health:
Researchers gain knowledge from
access to integrated clinical and
genomic data; cures for some forms
of cancer can be identified.
Deliver best practice care:
Data with context powers
innovation across the boundaries of
science and technology; cures can
be discovered.
Increase engagement:
Ecosystem-wide information sharing
fosters strong, actionable
relationships; patients are engaged
through collaboration and
nontraditional channels like loyalty
programs and social media.
Move from volume to value:
Trustworthy insights and patterns
revealed in clean, safe and connected
data improve treatments and reduce
costs for chronically ill patients.
3
Be safe:
A managed data lifecycle saves millions
annually by reducing data breaches,
ensuring regulatory compliance and
eliminating redundant costs.
4
Power the internet of healthy things:
Device integration and web-connected
sensors mesh with social networks to
collect patient / community data –
anywhere, any time.
5
For example:
For the first time ever, with foundational
architecture and the new enterprise data
warehouse in place, UPMC researchers
were able to electronically integrate clinical
and genomic information on 140 patients
previously treated for breast cancer.
BCBS Michigan complied with
ICD10 regulatory requirements
creating a easy to use crosswalk
between IC9 and ICD10 codes.
The largest children's hospital in the US
retained access to historical clinical data
for care delivery and regulatory
compliance while achieving resource
agility by eliminating maintenance costs of
the legacy EHR – saving $2.8M annually.
Moving to a value-driven model demands agility from people, processes, and technology. Organizations that
succeed in this transformation will be those that leverage data to:
1) Establish analytics as a core competency
2) Deliver best practice care
3) Engage patients and collaborate across the ecosystem to foster strong, actionable relationships