2009 02 17 - Introduction to EHRs for Rehab Providers
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2009 02 17 - Introduction to EHRs for Rehab Providers Presentation Transcript

  • 1. T558|
OT
Management
in
Today's
Health
&
Community
Systems
 Evidence
for
Electronic

 Health
Record
Systems
 02.17.2009
 Daniel
J.
Vreeman,
PT,
DPT,
MSc
 Assistant
Research
Professor
|
Indiana
University
School
of
Medicine
 Research
Scientist
|
Regenstrief
Institute,
Inc
 dvreeman@iupui.edu
 Copyright
©
2008

  • 2. Overview
 •  Overview
of
national
health
information
 technology
initiatives
 •  Forces
driving
adoption
of
information
 technology
in
healthcare
 •  Evidence
for
computerized
recommendations
 changing
behavior
 •  Evidence
for
EHRs
in
Rehabilitation

  • 3. Objectives
 Upon
participating
in
this
session,
you
will
be
able
to:
 •  Explain
the
forces
in
the
current
healthcare
environment
 promoting
adoption
of
information
technology
 •  Appreciate
the
types
of
problems
in
clinical
practice
and
 healthcare
delivery
that
may
be
amenable
to
improvement
with
 more
judicial
use
of
information
technology
 •  Discuss
the
key
factors
for
success
as
well
as
important
barriers
 to
implementing
electronic
health
record
systems
in
 rehabilitation
 Required
Readings:
 •  Vreeman
DJ,
Taggard
SL,
Rhine
MD,
Worrell
TW.
Evidence
for
electronic
health
 records
in
physical
therapy.
Phys
Ther.
2006;86(3):434‐449.

  • 4. Why
am
I
Here? 

  • 5. Widespread
Recognition 
 
 A
brief
history •  1960’s
–
First
studies
of
computers
in
healthcare
 •  1991
–
IOM

Task
Force
 •  2003
–
HHS
begins
promoting
widespread
use
of
HIT
 •  2003
–
HHS,
DoD,
VA
form
Consolidated
Health
Informatics
 •  2004
–
President
Bush
makes
HIT
a
top
national
priority
 –  State
of
the
Union
Address:
“by
computerizing
health
records,
we
can
 avoid
dangerous
medical
mistakes,
reduce
costs,
and
improve
care”
 –  Calls
for
EHRs
for
most
Americans
in
10
years
 –  Creates
the
Office
of
the
National
Health
IT
Coordinator
 •  2004
–
DHHS
Responds
 –  Secretary
Thompson
launches
the
“Decade
of
Health
Information
 Technology”
 –  Creates
a
strategy
to
develop
a
national
health
information
network
 •  Flurry
of
federal
activity…
 •  2009
–
Stimulus
package:
$20
billion
for
adopting
HIT

  • 6. The
Decade
of
Health
Information
Technology
 •  The
vision

 –  Complete,
longitudinal
health
information
follows
the
consumer
 –  Health
decisions
are
made
with
information
tools
to
assist
and
guide
 •  The
(envisioned)
result
 –  Fewer
medical
errors
 –  Less
wasteful
care
 –  Fewer
variations
in
care
 –  Patient‐centered
care
 –  Employers
with
productivity
and
competitive
edge
from
reduced
spending

  • 7. Big
Picture
 What
is
the
Role
of
Electronic
Health
Records?
 •  EHRs
are
the
primary
building
blocks
 –  Delivering
info
to
clinicians
 –  Collecting
info
from
clinicians
(and
instruments)
 –  Repositories
for
storing
data
 •  A
suite
of
applications
and
processes
 –  Not
just
one
‘program’
 –  Far
more
than
electronic
documentation
systems
 •  Lots
of
acronyms
 –  EHR,
EMR,
EPR,
PHR,
CPRS,
DMR,
etc…
 –  No
consensus
definition
 –  IOM
concept
is
most
prevalent

  • 8. The
EHR
 An
EHR
Includes:
 1.  Longitudinal
collection
of
electronic
health
 information
for
and
about
persons
 2.  Immediate
electronic
access
to
person‐
and
 population
level
information
by
authorized,
and
 only
authorized
users
 3.  Provision
of
knowledge
and
decision‐support
that
 enhance
the
quality,
safety,
and
efficiency
of
patient
 care
 4.  Support
of
efficient
processes
for
health
care
 delivery
 •  Institute of Medicine (U.S.). Committee on Data Standards for Patient Safety. Board on Health Care Services. Key Capabilities of an Electronic Health Record System. Washington, DC: National Academy Press; 2003.
  • 9. Big
Picture
 What
Will
This
Look
Like?
 •  A
‘Network
of
Networks’
 –  Not
a
central
database
 –  Communication
via
shared
set
of
technical
and
 policy
requirements
 –  Lots
of
ways
underlying
networks
can
form
 •  Geography
 •  Affinity
 •  Benefits
 –  Leverage
existing
data
pools
 –  ‘All
healthcare
is
local’

  • 10. Indiana
Network
for
Patient
Care
 •  A
working
health
information
exchange
for
13+
years
 –  100
source
systems
 –  1
billion
discrete
results
 –  Core
participant
in
NHIN
prototype
projects
 •  5

major
Indianapolis
healthcare
systems
 –  24
hospitals
(95%
of
hospital/ER
care
in
Indy)
 –  Hospital‐associated
group
practices
 •  County
and
State
health
departments
 –  Immunization
records,
lab
results,
tumor
registry
 •  National
and
regional
laboratories
 •  Lots
more
on
the
way…
 –  18
new
hospitals
within
existing
systems
 –  12
new
hospitals
have
signed
agreements
 –  10
new
hospitals
have
verbally
committed
 McDonald
CJ,
Overhage
JM,
Barnes
M,
et
al.
The
Indiana
network
for
patient
care:
a
working
local
health
information
infrastructure.
Health
Affairs.
1005;24(5):1214‐1220.

  • 11. Key
Challenges
to
Creating
an
NHIN
 •  Limited
adoption
of
EHRs
 –  Social/political
challenges
often
hardest
 –  Unequal
adoption
rates
by
practice
size
 •  Financial
risk
 –  Uncertain
ROI
 –  Unequal
accumulation
of
benefits
 •  Threats
to
privacy
and
security

  • 12. Key
Challenges
to
Creating
an
NHIN
 •  Lack
of
Standards
 – Silos
of
information
 •  Exchanging
health
 information
requires:
 – Vocabulary
standards
 – Messaging
standards
 – Transmission
standards

  • 13. The
Decade
of
Health
Information
Technology
 Key
Focus
Areas
 •  Regional
Health
Information
Organizations
(RHIOs)
 •  Nationwide
Health
Information
Network
(NHIN)
 •  Driving
EHR
Adoption
 –  Reduce
the
risk
of
investing
in
EHRs
 –  Developing
a
certification
process
 –  Provide
implementation
support

  • 14. Forces
in
Healthcare
Driving
 Adoption
of
Information
Technology

  • 15. Consumerism
 •  Empowered
patients
with
changing
expectations
 –  Technology‐enabled
experiences
 •  Consumers
(patients)
are
demanding
 –  Speed
 –  Convenience
 –  Customized
service
and
tools
 –  Security,
confidentiality
 •  Patients
move
faster
and
further
than
their
 health
information
 Kaplan B, Brennan PF. Consumer informatics supporting patients as co-producers of quality. JAMIA. 2001;8(4):309-316.
  • 16. Consumerism
 How
can
information
technology
help?
 •  Consumers
view
technology
as
‘state‐of‐the‐art’
 –  Can
promote
a
perception
of
high
quality
 •  Integrate
information
from
multiple
sources
across
 the
life‐span,
but
with
challenges
 •  Repositories
can
be
substrate
for
 –  Customizing
healthcare
delivery
and
resource
 distribution
 –  Enabling
process/system
integration
to
improve
 consumer
experience
 Kaplan B, Brennan PF. Consumer informatics supporting patients as co-producers of quality. JAMIA. 2001;8(4):309-316.
  • 17. Personal
Health
Records 
 •  A
fast
growing
area
of
interest/activity

  • 18. Expanded
Uses
of
Health
Information
 •  JCAHO
 –  Requires
data
to
support
management
ops,

 performance
improvement,
patient
care
 •  HIPAA

 –  Admin
procedures,
physical
safeguards,
security
 –  Standards
for
electronic
claims
attachments
 •  Public
Health
 •  Clinical
Research
 –  Clinical
data
repositories
have
well
documented
 research
uses

  • 19. Expanded
Uses
of
Health
Information
 
 •  Practice
Management
 – Exponential
increases
in
demand
for
 various
types
of
administrative
reports
 • Referral
patterns
 • Productivity
 • Lots
more…
 – Outcomes
tracking
 • Practice‐based
Evidence
 • Pay
for
performance
initiatives

  • 20. Expanded
Uses
of
Health
Information
 How
can
information
technology
help?
 •  Large
potential
efficiencies
via
improved
data
 –  Storage
 –  Processing
and
analysis
 –  Transmission
 –  Monitoring
and
tracking
(quality
assurance)
 •  Key
enabler:
structure
of
underlying
data
 –  Build
flexible
analytics
on
top

  • 21. Cost
of
Care
 •  US
spends
$1.7
trillion
annually
 – 16%
of
GDP
 • 2x
the
EU
average
 •  Serious
problems
with
 – Inefficiency
 – Poor
quality
 – Lack
of
access

  • 22. Cost
of
Care
 How
can
information
technology
help?
 •  Estimates
of
saving
$140
billion
annually
 –  Central
Indiana
estimates
$120
million
 •  How?
 –  Improved
information
sharing
and
care
coordination
 –  Reduced
redundancy
and
medical
errors
 •  Challenge:
mere
adoption
won’t
produce
savings
 –  Real
process
change
(transformation)
must
occur
 •  Misaligned
financial
incentives
 Hillestad R, Bigelow J, Bower A, et al. Can electronic medical record systems transform health care? Potential health benefits, savings and costs. Health Affairs. 2005;24(5):1103-1117.
  • 23. Clinical
Decision
Making 
 •  Making
sound
clinical
decisions
requires:
 –  Right
information,
right
time,
right
format
 •  EBP
(Patients
+
evidence
+
clinical
expertise)
 –  Lots
of
hype
 –  Clinicians
want
it,
but
don’t
have
time
 •  Clinicians
face
a
surplus
of
information
 –  ambiguous,
incomplete,
or
poorly
organized
 •  Rising
tide
of
information
 –  Expanding
knowledge
sources
 –  Improved
communication
methods
 Tierney WM. Improving clinical decisions and outcomes with information: a review. Int J Med Inf. 2001;62:1-9. Jette DU, Bacon K, et al. Evidence-based practice: beliefs, attitudes, knowledge, and behaviors of physical therapists. Phys Ther. 2003;83(9):786-805.
  • 24. Clinical
Decision
Making
 What’s
the
Problem?
 •  Man
is
an
imperfect
data
processor
 –  Sensitive
to
quantity
and
organization
of
information
 •  Decisions
hurt
by
too
many,
too
few,
or
poorly
organized
data

 –  Clinicians
are
susceptible
to
errors
of
omission
 •  Humans
are
“non‐perfectable”
data
processors
 –  Better
performance
requires
more
time
to
process
 –  Irony
 •  Clinicians
increasingly
face
productivity
expectations
 •  Clinicians
face
increasing
administrative
tasks
 •  McDonald CJ. Protocol-based computer reminders, the quality of care and the non-perfectability of man. N Engl J Med 1976;295(24):1351-5. •  Lopopolo RB. Hospital restructuring and the changing nature of the physical therapist’s role. Phys Ther. 1999;79(2) 171-185. •  American Physical Therapy Association. Reported Productivity Expectations of PTs 1999-2002. Available from http://apta.org
  • 25. EBP
and
Quality
of
Care
 How
can
information
technology
help?
 •  Eliminate
the
logistic
problems
 •  Efficient
access
to
primary
literature
 •  Efficient
access
to
needed
clinical
 information
 •  Tools
to
support
implementing
the
best
 evidence
at
the
point
of
care
 –  Computers
are
tireless
data
processors
 Vreeman DJ. Clinical prediction rules. Phys Ther 2006;86(5):761-762. Sackett DL, Rosenberg WM, et al. Evidence based medicine: what it is and what it isn’t. BMJ 1996;312(13):71-72 Jette DU, Bacon K, et al. Evidence-based practice: beliefs, attitudes, kowledge, and behaviors of physical therapists. Phys Ther. 2003;83(9):786-805.
  • 26. What
is
a
Computerized
Reminder?
 •  A
computer‐generated
suggestion
about
clinical
care
 for
an
individual
patient
 –  Informed
by
data
stored
in
an
EHR
 –  Suggestions
based
on
programs
that
operationalize
EBP
as
 computable
rules
 •  Often
integrated
into
a
clinical
application
 –  E.g.
Provider
order
entry
or
documentation
 •  Most
common
form
of
computerized
decision
support
 •  Can
be
presented
on
paper
or
a
workstation

  • 27. Care
 Reminders

  • 28. Computerized
Reminder

  • 29. Evidence
for
Computerized
Reminders 
 
 A
Long
History
  • 30. Evidence
for
Computerized
Reminders

  • 31. Evidence
for
Computerized
Reminders

  • 32. Why
Information
Technology? 
 •  All
of
these
forces
 –  Clinical
decision
making
(EBP)
 –  Quality
of
care
 –  Consumerism
 –  Expanded
uses
of
health
information
 

are
converging
on
the
need
to
effectively
 

manage
health
information
 •  Inadequacy
of
our
current
paper‐based
 health
information
system

  • 33. Why
are
there
no
reminder
studies
 in
rehabilitation?

  • 34. Reminders
for
Rehab
Providers 
 How
Can
Computers
Help? 
 •  Activity:
Examples
from
clinical
practice
 –  Content
of
the
reminder
 –  What
data
would
the
computer
need?

  • 35. Implications
for
Rehabilitation
 Evidence
for
EHRs

  • 36. Evidence
for
EHRs
in
Rehabilitation
 •  The
EHRs
operated
on
all
major
historical
classes
 of
computers
 –  1968
–
2004
 •  Software
 –  12/13
used
in‐house
developed
 –  Only
1
used
commercial
software
 •  Wide
variety
of
practice
settings
 –  Early
intervention,
outpatient,
sub‐acute,
actue

  • 37. Benefits
of
EHRs

  • 38. Barriers
to
Implementing
EHRs

  • 39. Success
Factors
in
Implementing
EHRs

  • 40. Evidence
for
EHRs
in
Rehabilitation

  • 41. Additional
Recommendations 
 
 My
Opinion •  Adopt
EHRs,
but
be
mindful
of
the
complexity
 involved
 –  Clinician
workflow
(not
hardware)
is
paramount
 •  Make
EHR
purchase
decisions
with
the
NHIN
 vision
in
mind
 –  Demand
features
of
interoperability
 •  HL7
Messaging
(import/export)
essential
 –  What
features
will
help
me
make
better
clinical
 decisions?
 –  What
vocabulary
standards
are
supported?

  • 42. Other
Questions?