Semantics is not a luxury

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  • 1. Seman/cs
is
not
a
luxury

 Building
the
new
genera/on
of
Clinical
Informa/on
Systems
 “Intra‐
and
Inter‐operability”
 Paolo
Ciccarese*,
PhD
 Co‐founder
and
knowledge
architect
 *Assistant
in
Neurology
@MassachuseHs
General
Hospital,
Instructor
in
Bioinforma/cs
@Harvard
Medical
School,
 Health
Care
Life
Science
Interest
Group
@W3C,
Consultant
in
SoOware
innova/on

  • 2. Timeline
 Mass
General/Harvard
Medical
School
 Visitor
at
Stanford
Univ.*
 *
Decision
Support/
Workflow
and
Ontology
 Based
SoOware
Dev.
(Constant
innova/on)
 Online
Scien/fic
Communi/es
 (Ontologies
and
Interoperability)
 HCLS
IG
W3C

 (Seman/c
Web
Technologies)
 Simile
Project
–
MIT**
 HMS
Faculty
 (Seman/c
Interoperability)
 University
of
Pavia
and
Consultant
 Clinical
Workflow,
Decision
Support
and
Knowledge
Management
(Guide
Project)
 Temporal
Abstrac/ons
in
Medicine
 Regional
and
Na/onal
Networks
 2000
 2004
 2005
 2006
 2007
 2008
 2009
 *Visi/ng
Samson
Tu
(SAGE
author)
 **Volunteer
(coding)

  • 3. •  I
am
a
developer/technologist/scien/st
 •  I
define
ontologies
I
don't
define
myself
as
 ontologist
 •  I
work
on
interoperability
with
seman/c
 technologies
in
different
fields
 •  I
believe
that
soOware
engineering
is
easier
than
 social
engineering

 •  I
have
been
lucky
because
at
one
point
of
my
life
I
 could
start
from
scratch

  • 4. Medicognos
Research
background

 P.Ciccarese
Phd
(
Medicognos
architect)


 


Mass
General/Harvard
Medical
School
 Online
Scien/fic
Communi/es
 (Ontologies
and
Interoperability)
 HCLS
IG
W3C

 (Seman<c
Web
Technologies)
 Simile
Project
–
MIT**
 HMS
Faculty
 (Seman<c
Interoperability)
 University
of
Pavia
and
Consultant
 Clinical
Workflow,
Decision
Support
and
Knowledge
Management
(Guide
Project)
 Temporal
Abstrac<ons
in
Medicine
 Regional
and
Na<onal
Networks
 















New
Genera/on
Knowledge
&
Process
Based
EHR
 2000
 2004
 2005
 2006
 2007
 2008
 2009
 





























Decision Support/ Workflow and Ontology Based So:ware Dev.  
  • 5. Original
GPs
requirements
2005
 1.  Usability
 2.  Process
Management/Op/miza/on/Improvement

 3.  Collabora/on
‐
care
networks
 4.  Medical
Knowledge
Management
‐
formal
mul/lingual
 terminologies,
evidence‐based
recommenda/ons
 5.  Communica/on
‐
interoperability
with
labs
and
hospitals
 Transform
the
problem
oriented
EPR
in
a
distributed
clinical
process
 management
system
with
embedded
clinical
decision
support
 
Con/nuity
of
Care
and
Disease
Management

  • 6. My
problem
is
 •  Represent
the
pa/ent
 •  Document
the
care
process
enough
to
pursue
 con/nuity
of
care
and
disease
management

  • 7. Why
it
is
so
hard?
 Diminishing

the
seman/c
impedance

 physician

mental
model

soOware


 Usability
 Evidence‐based
 Workflow
op/miza/on
 medicine
 Cost
Containment

 Economies
by
Outcome
 (Disease
Management)
 Improvement
 Interoperability
 Quality
of
data
informa/on
knowledge
 encoded
in
the
plaporm
and
 exchanged
with
the
external
world

  • 8. Processes
and
seman/cs
 Usability,
Con/nuity
of
Care
and
 Disease
Management

  • 9. eHealth
for
Safety
2007*
 New
genera/on
of
advanced,
user‐friendly
and
 ubiquitous
tools
for:
 •  Integra/on
of
decision
support
and
workflow
 support
systems
with
pa/ent
record
 •  Knowledge
representa/on
 •  Advanced
terminology‐driven
eHealth
tools
for
data
 entry
and
retrieval
 •  Clinical
informa/on
systems
integra/on
of
pa/ent
 data
across
the
con/nuum
of
care
 *
eHealth
for
Safety
–
Impact
of
ICT
on
Pa/ent
Safety
and
Risk
Management,

 October
2007
European
commission,
Informa/on
Society
and
Media

  • 10. IV‐V
Genera/on
EHR

  • 11. New
organiza/onal
architecture
 Health

Insurance

 Data 2x anonym P4P Quality Indicators Primes (global) Feedback GP
 Data anonymized P4P Primes Cl
Experts
 
QI

 PH
Experts
SP
 Coaches
MD
 Pharmacy
 Pa/ent
 Nurse
 Hospital

  • 12. New
informa/on
architecture
 Knowledge
based
Clinical
Workflow
Management
with
Decision
Support

 Patient Status Patient Status Patient Status Data Data Data Data Data Data KPI KPI KPI Clinical
Guideline

 CDS
 Operational Process Management ex:
lab
tests
 Care flow execution Alerts
 Agreed Care Plan Quality /Safety /Efficiency Indicators Ac/vity
1
 D
 Ac/vity
2
 Ac/vity
n
 Process Reenginering Process Mining Strategic Process Management CDS
:clinical
decision
support


  • 13. The
key
role
of
clinical
decision
support
 •  All
currently
known
large
studies
concluded

that:
EPR/ EHR

are
not
enough
for
quality
improvement!
 •  As
EHR
use
broadens,
one
should
not
assume
an
 automa/c
diffusion
of
improved
quality
of
care
 •  In
selec/ng
an
EHR,
physician
prac/ces
should
carefully
 consider
the
inclusion
of:
clinical
decision
support
to
 facilitate
quality
care

 1.EMR SophisBcaBon Correlates to Hospital Quality Data, Comparing EMR AdopBon to Care Outcomes, HIMSS 2007   2.Electronic Medical Records and Diabetes Quality of Care: Results From a Sample of Family Medicine PracBces  Jesse C. Crosson, PhD  ANNALS OF FAMILY         MEDICINE MAY/JUNE 2007   3.Electronic Health Record Use and the Quality of Ambulatory Care in the United States, Jeffrey A. Linder  ARCH  INTERN MED  JULY  2007  4.The Value of InformaBon Technology‐Enabled Diabetes Management Davis Bu,Center for InformaBon Technology Leadership. 2007  
  • 14. Process
modeling
challenge

  • 15. Knowledge
modeling
challenge
 rela/onship
 Biological

 class
 Nosological
 is
about
 is
about
 syndrome

  • 16. GPs
requirements
 1
‐
Respect
the

ideas
of
Terminfo2004 report
 ‐ 
“How
do
we
use
terminology
models
and
informa/on
models
together
to
represent
clinical
statements
 in
electronic
health
records
for
the
purposes
of
querying,
retrieval,
and
decision
support?”

 ‐ 
“General
sugges/on
(HS):
terminology
and
informa/on
models
should
evolve
in
lockstep”
 2
‐
Avoid
the
problems
pointed
by
Markwell
2008
Report
for
NHS:
Terminology
Binding
Requirements
 and
Principles

 ‐
”efforts
should
be
made
to
co‐evolve
the
Concept
Model
and
the
informa/on
model”

 ‐ 
“the
sum
of
the
concept
model
and
the
informa/on
model
need
to
evolve
so
that
together
they
 address
the
issue”.

 3
–
Align
with
OBO
Foundry
 4
‐
Design
the
Medicognos
terminology

for
workflow
and
decision
support
and
make
it
*open*

  • 17. Ontology‐based
plaporm
 •  Every
aspect
in
the
system
is
built
on
ontologies
 defined
using
a
subset
of
OWL
(proprietary
 solu/on
at
run/me)*
 •  More
expressive
OWL
for
analysts
(knowledge
 modeling,
model
checking,
maintenance,
mining)
 with
enterprise
tools
 •  Referent
tracking**
(unique
IDs)

 *
Ontology‐Based
Integra/on
of
Medical
Coding
Systems
and
Electronic
Pa/ent
Records
 Ceusters
W,
Smith
B,
De
Moor
G

 **
Strategies
for
referent
tracking
in
electronic
health
records.
Ceusters
W,
 Smith
B.
J
Biomed
Inform.
2006
Jun;39(3):362‐78.
Epub
2005
Sep
9.

  • 18. Seman/c
UI
Engine

  • 19. Seman/c
UI
Engine

  • 20. Unified
Seman/c
Model
 THE
STORY
TOLD
BY
MY
EPR
:

 The
concept
of
«
Systolic
pressure
»
/
occurred
the
07.04.08
in
the
context
 of:
aOer
effort,
with
the
value
of:
130
/
as
declared
by:
Dr
XY,
the
09.04.08
 at
15.35
/
and
acquired
by
Dr
XY
within
the
Careplan:
14527,
the
Careplan
 State
14527‐3,
the
ac/vity
nr
14527‐3‐2
using
the
data
template
“Pressure
 measurement”
and
value
of
this
systolic
pressure
instance
was
classified
 under
:

Pa/ent
status
/
Cardiovascular
Parameters

/
Arterial
Pressure

and
 it
can
be
seen
by
the
User
in
the
Summary
screen
the
Biometry
frame


  • 21. Unified
Seman/c
Model
 Occurrence
 How
it
occurred
 When?
 Who
reported
it?
 What
were
circumstances?

 


…
 Process
(Workflow)
 How
it
was
acquired
 Who?
 Biomedical
 Disease
 When?
 Sign
 What
 Data
 Within
which
 Symptom
 careplan
task?
 …
 …
 Classifiers
 ‐ Ac/ve
problems/cau/ons/…
 Journal
 ‐ Encounter/sub‐encounter
 Medicognos

 ‐ Observa/on/Query
templates
 Onthotypes®
 How
it
organized
for
the
users
 Clinical
Info
Management

  • 22. Medicognos
onthotypes®
 •  Defined
through
expressions
 •  Decoupling
meaning
from
presenta/on
 •  Extensive
usage
of
classifica/on

 •  Mul/ple
presenta/on
forms
can
have
the
same
 meaning

  • 23. Knowledge
Management
Suite

  • 24. Medicognos
architecture
 20%
 80%
 Onto‐Terminology
 Info.
Models
 Executable
Drug
Wf
 Executable
CDS
logic
 “ontotypes”
KB

 Templates

KB

 Drug
Therapy
Wf
KB

 Rules
KB
 Concept

 Template
 Workflow

 Drug
KB
 Queries
&Rules
Builder

 Builder
 Builder
 Builder
 Builder
 Clinical
Domain
Language

 Clinical
Knowledge
Management
Studio

 Domain   Clinical SituaBon     Care  OrganisaBon Biomedical    Ontologies    Care Plan OBO? BFO? OrganisaBon Time/Space Process FoundaBonal layer 
  • 25. 2
cents
on
interoperability
 •  Need
for
formally
defined
seman/cs
 •  Intra‐operability
and
Inter‐operability
go
together

 •  Being
able
to
communicate
with
other
systems
 depends
on
the
expressiveness
of
the
“internals”
first
 and
of
the
communica/on
protocols
later
on
 •  The
seman/c
models
have
to
be
produced
 incrementally
and
tested
con/nuously
in
seman/cally
 oriented
soOware
(full
stack)
 •  The
seman/c
is
not
limited
to
pa/ent
data
but
is
a
 mix‐up
of
several
clinical
aspects
 •  All
the
aspects
have
to
evolve
in
lockstep