The document discusses making the electronic health record (EHR) a "killer app" that accelerates widespread adoption. It argues that a paradigm shift is needed in EHR concepts, stakeholders, integration across domains, and faster adoption of technology. For the EHR to be a killer app, it must provide patient safety, efficient care, data management, knowledge management, and adaptive workflows. Overcoming challenges like standards, data sharing, and usability will help realize the promise of informatics to improve health globally.

1. EHR – The Killer App?
HINZ
Bringing the Electronic Health Record to Life
21 June 2012
W. Ed Hammond. Ph.D., FACMI, FAIMBE, FIMIA, FHL7
Director, Duke Center for Health Informatics
Director, Applied Informatics Research, DHTS
Associate Director, Biomedical Informatics Core, DTMI
Professor, Department of Community and Family Medicine
Professor Emeritus, Department of Biomedical Engineering
Adjunct Professor, Fuqua School of Business
Duke University
Chair Emeritus, HL7
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2. What is a killer app?
An application that
accelerates the adoption
and ubiquitous use of the
application.
3

3. Killer apps
• Personal computer
• World-wide web
• Wireless networks
• Google, Facebook, Social
Networking
4

4. What needs to happen to
make the EHR a killer app?
• Paradigm shift required in
– Concept of EHR/EHRS
– Recognition of all the stakeholders
– Roles of stakeholders
– Integration across all domains relating to
health and healthcare
– Creating common language
– Relationship between venders and users
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5. What needs to happen …
• Greater, quicker and appropriate use of
available technology
• Adopting more quickly to change
• Faster creation and more effective use of
required resources: applications,
standards, workforce
• Sharing data, knowledge, and processes
– Cooperative competition
• Stitch together current silos
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6. Technology Advances
• Mobile devices
– iPad and similar devices
– Personal health devices
• Ubiquitous wireless
• Voice recognition – still coming but useful
• Virtual reality – IBM’s Watson
• Cloud computing
• RFID
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7. From molecules to population
Molecular Clinical Patient Public Population
Biology Research Care Health Health
Individual, Family, Community, Societies
Site of Care: Intensive care, inpatient, ambulatory,
emergency department, long term care, home care
Clinical Specialties
Global
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8. Components of communication
• Data
– Semantically interoperable, high quality, timely
• Knowledge
– Appropriate, accessible, comprehensive
• Information
– Actionable, focused, clear, reduces uncertainty
• Judgment
– Human input based on experience and observation;
an intangible component
• Wisdom
– Individuals trained in how to use data, knowledge,
and information
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9. Application of HIT
Understand Outcome
Understand the Understand measurements Implement
problem to be causes, factors, and data proposed
solved. issues required to solution.
monitor & solve
Evaluate
outcome
Feedback Loop
Articulate health IT problems with the
precision of a scientific hypothesis.
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10. The Spectrum of Problem
Solving
• Science base of biology and medicine
• Collection and interpretation of signals
• Multiple (re-use) of data
• Application of science and data in clinical
care
• Extension of clinical care to populations
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11. Application Areas
• Genetics
– Genomics, proteomics, metabolomics, biomarkers, biomedical
modeling…
• Clinical Research
• Clinical systems (HIS, CPOE, ePrescribing, CDW, …)
– Clinical domain systems (cardiology, oncology, ,,,)
– Electronic Health Records
• EHR, EMR, PHR, Regional, National, Population
• Public Health
• Telemedicine
– Mobile and personal medical devices
• Educational Tools
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12. Genetics
• Gene mutation will identify many treatable genes
such as Hirschsprung’s disease, muscular
dystrophy, and cystic fibrosis
• Drug treatments are already influenced by
genomic information
– The anticoagulant drug warfarin has a narrow
therapeutic window - too high a dose, patient can
bleed to death; too low a dose, clots remain unclotted.
Genetic information [certain versions of two genes
CYP2C9 and VKORC1] are highly predictive of rate of
metabolizing warfarin.
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13. New Associations
• EHR must include genetic information
– Biomarkers need to be included in EHR with
meaning and actions included in an
accompanying knowledge base
– Gene mutations need to be included with links
to meaning and actions including in an
accompanying knowledge base
– Phenotype sets need to be linked to a disease
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14. Resulting Behavior Changes
• Physicians need not become geneticists.
Computers will use associated knowledge
to suggest actions based on biomarkers,
gene data, and phenotypes
• Physicians will become the “action arm”
with computers being the “thinking arm”
• Physicians role is as a participating
service
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15. Changing demands
• Aging population, world wide. In U.S., a
citizen becomes 65 years old every 6
seconds. Over the next 30 years, we will
add 20 million persons to the over 65
category.
• Current health care systems cannot
handle this volume.
• The role of primary care giver role will be
shared with less trained persons.
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16. Changing role of patients
• Increased participation and responsibility
for one’s own health
• Requires new methods of education,
monitoring, networking, data access
– Personal Health Records and patient portals
• Addressing health disparities
• Treating social and environment and
cultural issues
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17. A killer app delivers …
• Patient safety
• Efficient and effective health care delivery
• Health surveillance, bio-defense and natural
disaster health data management
• Real quality, reduced uncertainty, trust
• Cost containment in face of increasing costs of
healthcare
• Accommodation of an aging and mobile
population
• Effective management of chronic disease
• Higher quality of life as well as longevity
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18. A killer app delivers …
• Equal access to care
• Consumer sophistication and knowledge in health;
mobility
• Increasing continuous uses of data – translational
medicine
• Changes in doctor’s information gathering skills
• Increase in options for testing and treatment
• Limited connectivity among providers with multiple
providers involved in care
• The Healthcare Gamble – who calls the play?
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19. A killer app delivers …
• Practice of medicine that is predictive, personalized,
pre-emptive, and participatory [the 4Ps]
• Accommodating increasing limitations of resources:
– Decreasing number of providers
– Smaller hospitals disappearing
– Long waits for appointments
– Few walk-in appointments available
• Changing models for healthcare
– Consumer driven health care
– Health savings accounts
– Shopping mall clinics, Doc in Box clinics
– Wal-Mart, Google and Microsoft movement into healthcare
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20. A killer app accommodates …
• Volume of data about a patient has increased
tremendously over the past decades
– Increasing number of diagnostic tests
– Increasing numbers and modality of images
– Genetic testing
– Access to data at place and time of decision making is
critical
– Informed decision requires data
– Data must be used for multiple purposes
– From bytes to kilobytes to megabytes to gigabytes to
terabytes to petabytes to exabytes to zettabytes to …
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21. A killer app accommodates …
• Sources and amount of knowledge have
increased exponentially over the past decades
• NLM indexes over 1 million documents each
year
• Undergraduate and graduate education is
based on out-of-date concepts
• Continuing medical education is inadequate
• We can’t learn fast enough to be effective
• New knowledge requires new skills and new
understanding
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22. Killer app EHR provides …
• Data and data management
– The right data and only the right data
– Complete, aggregated, timely, trustworthy, unambiguous,
reusable, logically accessible
– Event driven displays, logically driven
• Knowledge and knowledge management
– Evidence-based, up-to-date, appropriate, integrated into work
flow, human and computer useable
• Processes and work flow
– Effectively and efficiently combines data with knowledge to
enable optimum human decision-making
– Monitor decisions and outcomes and provide safety checks,
feedback and recommendations
– Integrate data collection, presentation and decision support
transparently into care delivery process
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23. Requires paradigm shifts
• Technologists – more appropriate use of technology;
understanding the problems that need to be solved; better
coupling with the clinical community
• Clinical community – recognize what technology can do to
significantly enhance health care; become the drivers for the
use of eHealth; understand value of team approach that
includes the patient
• Patient – Accept responsibility for one’s own health; become
engaged in decision-making related to one’s own health;
enhanced awareness of personal risk factors; practice
prevention
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24. EHR – The Centerpiece of HIT
Data Creation
EHR
Data Collection The Enablement
Patient Care
Data Interchange
Data Aggregation Personalized Care
Community Care
Public Health
Includes the service Proactive interpretation
Real-time integration of of data to direct behavior
functions:
knowledge to direct and to enable quality care.
HIS, CPOE, CDS, e
control collection of data.
Prescribing, billing
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25. Enabling Better Health
 EHR systems must be adaptive. We need to be
able to include any new data element (self-
defined) without additional programming.
 Exchange of data should be driven by filters or a
defined set of business rules based on data
elements.
 Systems should use Enterprise Architecture
(SOA) approach in order to accommodate new
functionalities and new technologies.
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26. Possible Scenario
Knowledge Database
Institutional Clinical
Data Data Data Data Mining
Repository Warehouse
Push, pull or query based
Service
The
Filter
Applications National
(CPOE, ePres Patient-centric
Linkage
cribing, etc.) Essential EHR
Other Contained
systems in Regional
HIE
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27. EHR
• Architecture of EHR must support at variety of
uses.
– Requires independence of data from data
collection and application set
• Data must be interoperable; it must be
automatically reusable, capable of continuous
use
• It must be capable of integrating with new data
to produce new value and understanding.
• Granularity of data must start at lowest levels to
permit effective computer analyses and
understanding
• Reevaluate patient care and treatment as new
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data enters incorporating old data

28. EHR Issues
• Usability is key – minimize keystrokes for input
and query
• Every user, regardless of level, must understand
the value of the data
• Think ahead of user – alert fatigue can be
avoided by walking behind when appropriate
and alert only what is important
• Capture data from least expensive source but
maintain quality
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29. EHR Issues
• Free text is necessary as modifiers but attached
to structure
• Cognitive support provides intelligent interaction
with content
• Is an active partner with human in awareness,
evaluation and decision making
• Supports push, pull, interactive queries,
packaged queries, event-based queries
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30. Challenges
• Privacy issues; recognize that personal control of
data may harm creation of new knowledge and
seamlessly connecting the contributing domains for
the most effective care
• Identification and implementation of standards for
data and data exchange
• Controlled and purposeful exchange of data
• Quality of data is insured through process,
algorithms, and certainty factor
• Addresses provenance
31

31. Match Computational Approach to
Complexity of Data
Automation
Evidence-
based
Work lists advisors
Decision
Connectivity Support
Disease
Aggregate
Stead WW. Electronic Health management
EHR
Records. In: Rouse
WB, Cortese DA, eds.
dashboards
Engineering the system of
healthcare delivery.
Tennenbaum Institute Series
on Enterprise Systems, Vol. 3.
Amsterdam: IOS Press; 2009.
Data Mining

32. U.S. Focus
• HIE and interoperability (probably the #1
discussion issue in the town-hall session)
• Usability
• Vendor relations and vendor accountability
• Need for reimbursement reform before
providers will benefit from HIT
• Data sharing, as well as privacy, consent,
and cases of breach
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33. U.S. Focus
• Stories of successful overhead reduction
• Use of more “scientific methods” of
research and testing to determine future
mandates, such as Meaningful Use,
Phase 3
• Patient buy-in and collaboration
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34. Informatics
• Within Informatics is the power to bridge
existing silos and significantly advance
health, longevity and quality of life for all
citizens of the world.
• This achievement can only happen through
the global community acting together, sharing
costs and responsibility.
• The inequalities of the world, the globally
growing aging population, and economics
demand this action be taken.
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35. Conclusion / Summary
• The pace of technology has been paced
by Moore’s law: roughly, computational
power doubles approximately every two
years
• Use of technology – informatics – has not
kept pace. The future of health care
depends on our getting ahead of the curve
• That step demands a step change –
revolution, not evolution!
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36. The Final Word
• Informatics and HIT holds the promise for a
better world.
• Limited resources requires working together and
sharing everything.
• We must speak the same language with the
same meaning.
• Connectivity and communication is essential.
• Leadership and commitment of governments are
a necessity.
• Will the EHR become the killer app in our
lifetime? 37