Terminology, EHRs, and
Decision support
models:
What are they about?
Alan Rector
School of Computer Science / Northwest Institute of Bio-Health Informatics
rector@cs.man.ac.uk
Dr Jeremy Rogers
Senior Clinical Fellow in Health Informatics
Northwest Institute of Bio-Health Informatics
www.co-ode.org
www.clinical-escience.org
www.opengalen.org
Terminology and other models:
The How and the Why
► A Talk in two parts
► A review of a bit of history of clinical terminology
► Some fundamental problems
► Some challenges for current research
► Focus on the problem of binding terminology to
EHRs
► New opportunities with new technologies
A bit of history
► It all started with public health, vital statistics
and epidemiology…
London Bills of Mortality
every Thursday from 1603 until the 1830s
Aggregated
Statistics 1665
Manchester Mercury
January 1st 1754
List of diseases &
casualties this year
19276 burials
15444 christenings
Deaths by centile
Aged 1456
Executed 18
Consumption 3915
Found Dead 34
Convulsion 5977
Frighted 2
Dropsy 794
Kill'd by falls and other accidents 55
Fevers 2292
Kill'd themselves 36
Smallpox 774
Murdered 3
Teeth 961
Overlaid 40
Bit by mad dogs 3
Poisoned 1
Broken Limbs 5
Scalded 5
Bruised 5
Smothered 1
Burnt 9
Stabbed 1
Drowned 86
Starved 7
Excessive Drinking 15
Suffocated 5
Origins of modern terminologies
100 years of epidemiology
► ICD - Farr in 1860s to ICD9 in 1979
► International reporting of morbidity/mortality
► ICPC - 1980s
► Clinically validated epidemiology in primary care
► Now expanded for use in Dutch GP software
… then took on new tasks .
Organising Care
► Librarianship
► MeSH - NLM from around 1900 - Index Medicus & Medline
► EMTree - from Elsevier in 1950s - EMBase
► Remumeration
► ICD9-CM (Clinical Modification) 1980
►10 x larger than ICD; aimed at US insurance reimbursement
► CPT, …
► Pathology indexing
► SNOMED 1970s to 1990 (SNOMED International)
►First faceted or combinatorial system
►Topology, morphology, aetiology, function
► Specialty Systems
► Mostly similar hierarchical systems
►ACRNEMA/SDM - Radiology
►NANDA, ICNP… - Nursing
… and then with computers
Documenting/Reporting Care
► Early computer systems
► OXMIS
► Aimed at saving space on early
computers
► READ competitor
► 1-5 Mbyte / 10,000 patients
► Derived from empirical data
► Read (1987 - 1995)
► Hierarchical modelled on ICD9
►Detailed signs and symptoms
for primary care
►Purchased by UK government
in 1990
►Single use
► Medical Entities Dictionary
(MED)
► Jim Cimino, Hospital support,
Columbia, USA
► Flat list of codes
► Defunct circa 1999
► ICPC
► Epidemiologically tested, Dutch
► LOINC
► For laboratory data
► DICOM (sdm)
► For images
► MEDDRA
► Adverse Reactions
Unified Medical
Language System
► US National Library of Medicine
► De facto common registry for vocabularies
► Metathesaurus
► 1.8 million concepts
► categorised by semantic net types
► Semantic Net
► 135 Types
► 54 Links
► Specialist Lexicon
Unified Medical
Language System
►Concept Unique Identifiers (CUIs)
►Lexical Unique Identifiers (LUIs)
►String Unique Identifers (SUIs)
Code
SUI
LUI
CUI
CUI
Code
SUI
Code
LUI
LUI
SUI
Code
SUI
Code
…but …The Coding of Chocolate
An international conversion guide
SNOMED-CT
C-F0811
?



C-F0816
C-F0817
C-F0819
C-F081A
C-F081B
C-F081C
C-F0058
Term
Bounty bar
Crème egg
Kit Kat
Mars Bar
Milky Way
Smarties
Twix
Snicker
CTV3
UbOVv
UbOW2
UbOW3
UbOW4
UbOW5
UbOW6
UbOW7
Ub1pT
Origins of modern terminologies
Beyond recording
►Electronic patient records (EPRs)
► Weed’s Problem Oriented Medical Record
► Direct entry by health care professionals
►Decision support
► Ted Shortliffe (MYCIN), Clem McDonald (Computer based
reminders), Perry Miller (Critiquing), Musen (Protégé)
►Re-use
► Patient centred information
Origins of modern terminologies
1990s: a Paradigm Shift
► Human-Human and Human-Machine to Machine-Machine
► From paper to software
► From single use to multiple re-use
► From coding clerks to direct entry by clinicians
► From pre-defined reporting to decision support
From Books to Software
Software
Machine Processing
requires
Machine Readable Information
Need shared, multi-use, multi-purpose
computable
Clinical terminology
Compositional logic-based
Termiologies
Origins of modern terminologies
The PEN&PAD/GALEN Vision
Clinical
Terminology
Data
Entry
Clinical
Record
Decision
Support
Best
Practice
HealthCard
Mr Ivor Bigun
Dun Roamin
Anytown
Any country
4431 3654 90273
NEW
Clinical
Terminology
Data
Entry
Electronic
Health
Records
Decision
Support &
Aggregated
Data
Best
Practice
Fundamental problems:
Enumeration doesn’t scale
The scaling problem:
The combinatorial explosion
► It keeps happening!
► “Simple” brute force
solutions do not scale up!
► Conditions x sites x modifiers x
activity x context
► Huge number of terms to author
► Software CHAOS
Actual
Combination of things to be
done & time to do each thing
► Terms and forms needed
► Increases exponentially
► Effort per term or form
► Must decrease to
compensate
► To give the effectiveness we
want
► Or might accept
Things to
build
The exploding bicycle
►1972 ICD-9 (E826) 8
►READ-2 (T30..) 81
►READ-3 87
►1999 ICD-10 ……
1999 ICD10: 587 codes
to p Class
I Certain in fectio u s an d p arasitic d iseases
II Neo p lasms
III Diseases o f th e b lo o d an d b lo o d -fo rmin g o rg an s an d certain d iso rd ers in v o lv in g th e immu n e mech an ism
IV E n d o crin e, n u tritio n al an d metab o lic d iseases
V M en tal an d b eh av io u ral d iso rd ers
VI Diseases o f th e n erv o u s sy stem
VII Diseases o f th e ey e anaddn ex a
VIII Diseases o f th e ear an d masto id p ro cess
IX Diseases o f th e circu lato ry sy stems
X Diseases o f th e resp irato ry sy stem
XI Diseases o f th e d ig estiv e sy stem
XII Diseases o f th e sk in an d su b cu tan eo u s tissu e
XIII Diseases o f th e mu scu lo sk eletal sy stem an d co n n ectiv e tissu e
XIV Diseases o f th e g en ito u rin ary sy stem
XV P reg n an cy , ch ild b irth an
p ud erp
th eriu
e m
XVI Certain co n d itio n s o rig in atinpgerin
in atal
thpeerio d
XVII Co n g en ital malfo rmatio n s, d efo rmatio n s an d ch ro mo so mal ab n o rmalities
XVIII S y mp to ms, sig n s an d ab n o rmal clin ical an d lab o rato ry fin d in g s, n o t elsewh ere classified
XIX In ju ry , p o iso n in g an d certain o th er co n seq u en ces o f ex tern al cau ses
XX E x tern al cau ses o f mo rb id ity an d mo rtality
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u n4 sp
ity in ju red in co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n sp ecified p ed al cy clist, traffic accid en t, wh ile wo rk in g fo r an in co me
V1 0 . 4 2 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, d riv er, traffic accid en t, wh ile wo rk in g fo r an in co me
. 9 ecified
2 P ed alactiv
cy clist
V1 0 . 4 3 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, d riv er, traffic accid en t, wh ile en g ag ed in o th er ty p es o f wo rk
V1 4 . 9 3 P ed al cy clist in ju red in co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in o th er ty p es o f wo rk
V1 0 . 4 4 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, d riv er, traffic accid en t, wh ile restin g , sleep in g , eatin g o r en g ag in g in V1
o th
v ital
3 erP ed
al cyactiv
clistities
in ju red in co llisio n with car, p ick -u p tru ck o r v an
V1 4 . 9 4 P ed al cy clist in ju red in co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n sp ecified p ed al cy clist, traffic accid en t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
V1 0 . 4 8 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, d riv er, traffic accid en t, wh ile en g ag ed in o th er sp ecified activ ities
V1 3 . 0 P ed al cy clist in ju red in co llisio n with car, p ick -u p tru ck
n o on rtraffic
v anaccid
, d riv
en ter,
V1 4 . 9 8 P ed al cy clist in ju red in co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in o th er sp ecified activ ities
V1 0 . 4 9 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, d riv er, traffic accid en t, d u rin g u n sp ecified activ ity
•V31.22 Occupant of three-wheeled motor vehicle injured in collision
with pedal cycle, person on outside of vehicle, nontraffic accident, while
working for income
V1 3 . 0 0 P ed al cy clist in ju red in
V1 0 . 5 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, p assen g er, traffic accid en t
V1 0 . 5 0 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, p assen g er, traffic accid en t, wh ile en g ag ed in sp o rts activ ity
V1 3 . 0 1 P ed al cy clist in ju red in
V1 0 . 5 1 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, p assen g er, traffic accid en t, wh ile en g ag ed in leisu re activ ity
V1 3 . 0 2 P ed al cy clist in ju red in
V1 0 . 5 2 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, p assen g er, traffic accid en t, wh ile wo rk in g fo r an in co me
V1 3 . 0 3 P ed al cy clist in ju red in
V1 0 . 5 3 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, p assen g er, traffic accid en t, wh ile en g ag ed in o th er ty p es o f wo rk
V1 3ities
. 0 4 P ed al cy clist in ju red in
V1 0 . 5 4 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, p assen g er, traffic accid en t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ
V1 0 . 5 8 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, p assen g er, traffic accid en t, wh ile en g ag ed in o th er sp ecified activ ities
V1 3 . 0 8 P ed al cy clist in ju red in
V1 0 . 5 9 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, p assen g er, traffic accid en t, d u rin g u n sp ecified activ ity
V1 3 . 0 9 P ed al cy clist in ju red in
V1 0 . 9 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, u n sp ecified p ed al cy clist, traffic accid en t
V1 3 . 1 P ed al cy clist in ju red in co llisio n
V1 0 . 9 0 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in sp o rts activ ity
V1 0 . 9 1 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in leisu re activ ity
V1 3 . 1 0 P ed al cy clist in ju red in
V1 0 . 9 2 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, u n sp ecified p ed al cy clist, traffic accid en t, wh ile wo rk in g fo r an in co me
V1 3 . 1 1 P ed al cy clist in ju red in
V1 0 . 9 3 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in o th er ty p es o f wo rk
1 2er P
cy clist
V1 0 . 9 4 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, u n sp ecified p ed al cy clist, traffic accid en t, wh ile restin g , sleep in g , eatin g o r en g ag in g V1
in 3o .th
v ed
italal activ
itiesin ju red in
V1 0 . 9 8 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in o th er sp ecified activ ities V1 3 . 1 3 P ed al cy clist in ju red in
V1 0 . 9 9 P ed al cy clist in ju red in co llisio n with p ed estrian o r an imal, u n sp ecified p ed al cy clist, traffic accid en t, d u rin g u n sp ecified activ ity
V1 3 . 1 4 P ed al cy clist in ju red in
V1 1 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle
V1 3 . 1 8 P ed al cy clist in ju red in
V1 1 . 0 P ed al cy clist in ju red in co llisio n with o th er p ed al
n ocyn cle,
traffic
daccid
riv er,
en t
V1 3 . 1 9 P ed al cy clist in ju red in
V1 1 . 0 0 P ed al cy clist in ju red in co llisio n with o th er p ed nalocy
n traffic
cle, daccid
riv er,
en t, wh ile en g ag ed in sp o rts activ ity
V1 1 . 0 1 P ed al cy clist in ju red in co llisio n with o th er p ed nalocy
n traffic
cle, daccid
riv er,
en t, wh ile en g ag ed in leisu re activ ity
V1 3 . 2 P ed al cy clist in ju red in co llisio n
V1 1 . 0 2 P ed al cy clist in ju red in co llisio n with o th er p ed nalocy
n traffic
cle, daccid
riv er,
en t, wh ile wo rk in g fo r an in co me
V1 3 . 2 0 P ed al cy clist in ju red in
V1 1 . 0 3 P ed al cy clist in ju red in co llisio n with o th er p ed nalocy
n traffic
cle, daccid
riv er,
en t, wh ile en g ag ed in o th er ty p es o f wo rk
V1 3 . 2 1 P ed al cy clist in ju red in
V1 1 . 0 4 P ed al cy clist in ju red in co llisio n with o th er p ed nalocy
n traffic
cle, daccid
riv er,
en t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
V1 3 . 2 2 P ed al cy clist in ju red in
V1 1 . 0 8 P ed al cy clist in ju red in co llisio n with o th er p ed nalocy
n traffic
cle, daccid
riv er,
en t, wh ile en g ag ed in o th er sp ecified activ ities
V1 1 . 0 9 P ed al cy clist in ju red in co llisio n with o th er p ed nalocy
n traffic
cle, daccid
riv er,
en t, d u rin g u n sp ecified activ ity
V1 3 . 2 3 P ed al cy clist in ju red in
V1 1 . 1 P ed al cy clist in ju red in co llisio n with o th er p ed al cyn cle,
o n traffic
p assen
accid
g er,
en t
V1 3 . 2 4 P ed al cy clist in ju red in
V1 1 . 1 0 P ed al cy clist in ju red in co llisio n with o th er p ed al cy
n ocle,
n traffic
p assen
accid
g er,
en t, wh ile en g ag ed in sp o rts activ ity
V1 3 . 2 8 P ed al cy clist in ju red in
V1 1 . 1 1 P ed al cy clist in ju red in co llisio n with o th er p ed al cy
n ocle,
n traffic
p assen
accid
g er,
en t, wh ile en g ag ed in leisu re activ ity
V1 1 . 1 2 P ed al cy clist in ju red in co llisio n with o th er p ed al cy
n ocle,
n traffic
p assen
accid
g er,
en t, wh ile wo rk in g fo r an in co me
V1 3 . 2 9 P ed al cy clist in ju red in
V1 1 . 1 3 P ed al cy clist in ju red in co llisio n with o th er p ed al cy
n ocle,
n traffic
p assen
accid
g er,
en t, wh ile en g ag ed in o th er ty p es o f wo rk
V1 3 . 3 P ed al cy clist in ju red in co llisio n
V1 1 . 1 4 P ed al cy clist in ju red in co llisio n with o th er p ed al cy
n ocle,
n traffic
p assen
accid
g er,
en t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
V1 3 . 3 0 P ed al cy clist in ju red in
V1 1 . 1 8 P ed al cy clist in ju red in co llisio n with o th er p ed al cy
n ocle,
n traffic
p assen
accid
g er,
en t, wh ile en g ag ed in o th er sp ecified activ ities
V1 3 . 3 1 P ed al cy clist in ju red in
V1 1 . 1 9 P ed al cy clist in ju red in co llisio n with o th er p ed al cy
n ocle,
n traffic
p assen
accid
g er,
en t, d u rin g u n sp ecified activ ity
V1 1 . 2 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified
n o n traffic
p ed al
accid
cy clist,
en t
V1 3 . 3 2 P ed al cy clist in ju red in
V1 1 . 2 0 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified
n o n traffic
p edaccid
al cy en
clist,
t, wh ile en g ag ed in sp o rts activ ity
V1 3 . 3 3 P ed al cy clist in ju red in
V1 1 . 2 1 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified
n o n traffic
p edaccid
al cy en
clist,
t, wh ile en g ag ed in leisu re activ ity
V1 3 . 3 4 P ed al cy clist in ju red in
V1 1 . 2 2 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified
n o n traffic
p edaccid
al cy en
clist,
t, wh ile wo rk in g fo r an in co me
V1 1 . 2 3 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified
n o n traffic
p edaccid
al cy en
clist,
t, wh ile en g ag ed in o th er ty p es o f wo rk
V1 3 . 3 8 P ed al cy clist in ju red in
V1 1 . 2 4 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified
n o n traffic
p edaccid
al cy en
clist,
t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
V1 3 . 3 9 P ed al cy clist in ju red in
V1 1 . 2 8 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified
n o n traffic
p edaccid
al cy en
clist,
t, wh ile en g ag ed in o th er sp ecified activ ities
V1
3
.
4
P
ed al cy clist in ju red in co llisio n
V1 1 . 2 9 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified
n o n traffic
p edaccid
al cy en
clist,
t, d u rin g u n sp ecified activ ity
V1 3 . 4 0 P ed al cy clist in ju red in
V1 1 . 3 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, wh ile b o ard in g o r alig h tin g
V1 1 . 3 0 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in sp o rts activ ity
V1 3 . 4 1 P ed al cy clist in ju red in
V1 1 . 3 1 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in leisu re activ ity
V1 3 . 4 2 P ed al cy clist in ju red in
V1 1 . 3 2 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, wh ile b o ard in g o r alig h tin g , wh ile wo rk in g fo r an in co me
co llisio n with car, p ick -u p tru ncko no traffic
r v anaccid
, d riv
en t,er,wh ile en g ag ed in sp o rts activ ity
co llisio n with car, p ick -u p tru ncko no traffic
r v anaccid
, d riv
en t,er,wh ile en g ag ed in leisu re activ ity
V1 4 . 9 9 P ed al cy clist in ju red in co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n sp ecified p ed al cy clist, traffic accid en t, d u rin g u n sp ecified activ ity
V1 5 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle
co llisio n with car, p ick -u p tru ncko no traffic
r v anaccid
, d riv
en t,er,wh ile wo rk in g fo r an in co me
V1 5 . 0 P ed al cy clist in ju red in co llisio n with railway train o r railwayn ov nehtraffic
icle,accid
d rivener,
t
co llisio n with car, p ick -u p tru ncko no traffic
r v anaccid
, d riv
en t,er,wh ile en g ag ed in o th er ty p es o f wo rk
V1 5 . 0 0 P ed al cy clist in ju red in co llisio n
co llisio n with car, p ick -u p tru ncko no traffic
r v anaccid
, d riv
en t,er,wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er
V1v5ital
. 0 1activ
P edities
al cy clist in ju red in co llisio n
co llisio n with car, p ick -u p tru ncko no traffic
r v anaccid
, d riv
en t,er,wh ile en g ag ed in o th er sp ecified activ ities
V1 5 . 0 2 P ed al cy clist in ju red in co llisio n
co llisio n with car, p ick -u p tru ncko no traffic
r v anaccid
, d riv
en t,er,d u rin g u n sp ecified activ ity
V1 5 . 0 3 P ed al cy clist in ju red in co llisio n
with railway train o r railway
n ovneh
traffic
icle,accid
d riv
en er,
t, wh ile en g ag ed in sp o rts activ ity
with railway train o r railway
n ovneh
traffic
icle,accid
d riv
en er,
t, wh ile en g ag ed in leisu re activ ity
with railway train o r railway
n ovneh
traffic
icle,accid
d riv
en er,
t, wh ile wo rk in g fo r an in co me
with railway train o r railway
n ovneh
traffic
icle,accid
d riv
en er,
t, wh ile en g ag ed in o th er ty p es o f wo rk
with car, p ick -u p tru ck on ro vn an
traffic
, paccid
assenen
g er,
t
V1 5 . 0 4 P ed al cy clist in ju red in co llisio n with railway train o r railway
n ovneh
traffic
icle,accid
d riv
en er,
t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
co llisio n with car, p ick -u p tru ck no or nv traffic
an , paccid
asseneng t,er,wh ile en g ag ed in sp o rts activ ity
V1 5 . 0 8 P ed al cy clist in ju red in co llisio n with railway train o r railway
n ovneh
traffic
icle,accid
d riv
en er,
t, wh ile en g ag ed in o th er sp ecified activ ities
co llisio n with car, p ick -u p tru ck no or nv traffic
an , paccid
asseneng t,er,wh ile en g ag ed in leisu re activ ity
V1 5 . 0 9 P ed al cy clist in ju red in co llisio n with railway train o r railway
n ovneh
traffic
icle,accid
d riv
en er,
t, d u rin g u n sp ecified activ ity
co llisio n with car, p ick -u p tru ck no or nv traffic
an , paccid
asseneng t,er,wh ile wo rk in g fo r an in co me
V1 5 . 1 P ed al cy clist in ju red in co llisio n with railway train o r railway v nehoicle,
n traffic
p assen
accid gener,
t
co llisio n with car, p ick -u p tru ck no or nv traffic
an , paccid
asseneng t,er,wh ile en g ag ed in o th er ty p es o f wo rk
V1 5 . 1 0 P ed al cy clist in ju red in co llisio n
co llisio n with car, p ick -u p tru ck no or nv traffic
an , paccid
asseneng t,er,wh ile restin g , sleep in g , eatin g o r en g ag in g in oV1
th 5er. 1v 1italP ed
activ
ities
al cy
clist in ju red in co llisio n
co llisio n with car, p ick -u p tru ck no or nv traffic
an , paccid
asseneng t,er,wh ile en g ag ed in o th er sp ecified activ ities
V1 5 . 1 2 P ed al cy clist in ju red in co llisio n
co llisio n with car, p ick -u p tru ck no or nv traffic
an , paccid
asseneng t,er,d u rin g u n sp ecified activ ity
V1 5 . 1 3 P ed al cy clist in ju red in co llisio n
with car, p ick -u p tru ck o r v an , u n spn ecified
o n traffic
paccid
ed al encyt clist,
V1 5 . 1 4 P ed al cy clist in ju red in co llisio n
with railway train o r railway vneho icle,
n traffic
p accid
assen en
g er,
t, wh ile en g ag ed in sp o rts activ ity
with railway train o r railway vneho icle,
n traffic
p accid
assen en
g er,
t, wh ile en g ag ed in leisu re activ ity
with railway train o r railway vneho icle,
n traffic
p accid
assen en
g er,
t, wh ile wo rk in g fo r an in co me
with railway train o r railway vneho icle,
n traffic
p accid
assen en
g er,
t, wh ile en g ag ed in o th er ty p es o f wo rk
with railway train o r railway vneho icle,
n traffic
p accid
assen en
g er,
t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
co llisio n with car, p ick -u p tru ck o r v an , u n sp
n oecified
n traffic
paccid
ed alencyt,clist,
wh ile en g ag ed in sp o rts activ ity
V1 5 . 1 8 P ed al cy clist in ju red in co llisio n with railway train o r railway vneho icle,
n traffic
p accid
assen en
g er,
t, wh ile en g ag ed in o th er sp ecified activ ities
co llisio n with car, p ick -u p tru ck o r v an , u n sp
n oecified
n traffic
paccid
ed alencyt,clist,
wh ile en g ag ed in leisu re activ ity
V1 5 . 1 9 P ed al cy clist in ju red in co llisio n with railway train o r railway vneho icle,
n traffic
p accid
assen en
g er,
t, d u rin g u n sp ecified activ ity
co llisio n with car, p ick -u p tru ck o r v an , u n sp
n oecified
n traffic
paccid
ed alencyt,clist,
wh ile wo rk in g fo r an in co me
co llisio n with car, p ick -u p tru ck o r v an , u n sp
n oecified
n traffic
paccid
ed alencyt,clist,
wh ile en g ag ed in o th er ty p esV1o 5f .wo
2 Prked al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n sp necified
o n traffic
p ed
accid
al cy
en clist,
t
co llisio n with car, p ick -u p tru ck o r v an , u n sp
n oecified
n traffic
paccid
ed alencyt,clist,
wh ile restin g , sleep in g , eatin g o r en gV1
ag5in. 2g0 inP ed
o th
ital in
activ
itiesin co llisio n with railway train o r railway v eh icle, u n spnecified
al er
cy vclist
ju red
o n traffic
p accid
ed al en
cy t,clist,
wh ile en g ag ed in sp o rts activ ity
co llisio n with car, p ick -u p tru ck o r v an , u n sp
n oecified
n traffic
paccid
ed alencyt,clist,
wh ile en g ag ed in o th er sp ecified activV1
ities
5 . 2 1 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n spnecified
o n traffic
p accid
ed al en
cy t,clist,
wh ile en g ag ed in leisu re activ ity
co llisio n with car, p ick -u p tru ck o r v an , u n sp
n oecified
n traffic
paccid
ed alencyt,clist,
d u rin g u n sp ecified activ ity
V1 5 . 2 2 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n spnecified
o n traffic
p accid
ed al en
cy t,clist,
wh ile wo rk in g fo r an in co me
•W65.40 Drowning and submersion while in bath-tub, street and highway,
while engaged in sports activity
with car, p ick -u p tru ck o r v an , wh ile b o ard in g o r alig h tin g
V1 5 . 2 3 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n spnecified
o n traffic
p accid
ed al en
cy t,clist,
wh ile en g ag ed in o th er ty p es o f wo rk
co llisio n with car, p ick -u p tru ck o r v an , wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in sp o rts activ
V1 ity
5 . 2 4 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n spnecified
o n traffic
p accid
ed al en
cy t,clist,
wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
co llisio n with car, p ick -u p tru ck o r v an , wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in leisu re activ
V1 ity
5 . 2 8 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n spnecified
o n traffic
p accid
ed al en
cy t,clist,
wh ile en g ag ed in o th er sp ecified activ ities
co llisio n with car, p ick -u p tru ck o r v an , wh ile b o ard in g o r alig h tin g , wh ile wo rk in g fo r an in co V1
me 5 . 2 9 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n spnecified
o n traffic
p accid
ed al en
cy t,clist,
d u rin g u n sp ecified activ ity
co llisio n with car, p ick -u p tru ck o r v an , wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in oV1
th er
woclist
rk in ju red in co llisio n with railway train o r railway v eh icle, wh ile b o ard in g o r alig h tin g
5 . ty
3 pP es
ed oal f cy
co llisio n with car, p ick -u p tru ck o r v an , wh ile b o ard in g o r alig h tin g , wh ile restin g , sleep in g , eatin
ag alin cy
g clist
in o in
th ju
er red
v italin activ
ities n with railway train o r railway v eh icle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in sp o rts activ ity
V1g 5 o. 3r 0en Pg ed
co llisio
co llisio n with car, p ick -u p tru ck o r v an , wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in o th er sp ecified
ities
V1 5 . 3 activ
1 P ed
al cy clist in ju red in co llisio n with railway train
co llisio n with car, p ick -u p tru ck o r v an , wh ile b o ard in g o r alig h tin g , d u rin g u n sp ecified activ ityV1 5 . 3 2 P ed al cy clist in ju red in co llisio n with railway train
with car, p ick -u p tru ck o r v an , d riv er, traffic accid en t
V1 5 . 3 3 P ed al cy clist in ju red in co llisio n with railway train
co llisio n with car, p ick -u p tru ck o r v an , d riv er, traffic accid en t, wh ile en g ag ed in sp o rts activ ity
V1 5 . 3 4 P ed al cy clist in ju red in co llisio n with railway train
co llisio n with car, p ick -u p tru ck o r v an , d riv er, traffic accid en t, wh ile en g ag ed in leisu re activ ity
o r railway v eh icle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in leisu re activ ity
o r railway v eh icle, wh ile b o ard in g o r alig h tin g , wh ile wo rk in g fo r an in co me, wh ile wo rk in g fo r an in co me
o r railway v eh icle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in o th er ty p es o f wo rk
o r railway v eh icle, wh ile b o ard in g o r alig h tin g , wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
V1 5 . 3 8 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in o th er sp ecified activ ities
co llisio n with car, p ick -u p tru ck o r v an , d riv er, traffic accid en t, wh ile wo rk in g fo r an in co me
V1 5 . 3 9 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, wh ile b o ard in g o r alig h tin g , d u rin g u n sp ecified activ ity
V1 3 . 4 3 P ed al cy clist in ju red in co llisio n with car, p ick -u p tru ck o r v an , d riv er, traffic accid en t, wh ile en g ag ed in o th er ty pV1
es o5 f. 4woP rk
V1 1 . 3 3 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in o th er ty p es o f wo rk
ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, d riv er, traffic accid en t
V1 1 . 3 4 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, wh ile b o ard in g o r alig h tin g , wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v italV1activ
3 . 4ities
4 P ed al cy clist in ju red in co llisio n with car, p ick -u p tru ck o r v an , d riv er, traffic accid en t, wh ile restin g , sleep in g , eatin g o r enV1
g ag
v italin activ
5 .in
4 0g Pined oalthcyerclist
ju redities
in co llisio n with railway train o r railway v eh icle, d riv er, traffic accid en t, wh ile en g ag ed in sp o rts activ ity
V1 1 . 3 8 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in o th er sp ecified activ ities
V1 3 . 4 8 P ed al cy clist in ju red in co llisio n with car, p ick -u p tru ck o r v an , d riv er, traffic accid en t, wh ile en g ag ed in o th er sp ecified activ
V1 ities
5 . 4 1 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, d riv er, traffic accid en t, wh ile en g ag ed in leisu re activ ity
V1 1 . 3 9 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, wh ile b o ard in g o r alig h tin g , d u rin g u n sp ecified activ ity
V1
3
.
4
9
P
ed
al
cy
clist
in
ju
red
in
co
llisio
n
with
car,
p
ick
-u
p
tru
ck
o
r
v
an
,
d
riv
er,
traffic
accid
en
t,
d
u
rin
g
u
n
sp
ecified
activ
ity
V1 1 . 4 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, d riv er, traffic accid en t
V1 5 . 4 2 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, d riv er, traffic accid en t, wh ile wo rk in g fo r an in co me
V1 3 . 5 P ed al cy clist in ju red in co llisio n with car, p ick -u p tru ck o r v an , p assen g er, traffic accid en t
V1 1 . 4 0 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, d riv er, traffic accid en t, wh ile en g ag ed in sp o rts activ ity
V1 5 . 4 3 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, d riv er, traffic accid en t, wh ile en g ag ed in o th er ty p es o f wo rk
V1 1 . 4 1 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, d riv er, traffic accid en t, wh ile en g ag ed in leisu re activ ity
V1 3 . 5 0 P ed al cy clist in ju red in co llisio n with car, p ick -u p tru ck o r v an , p assen g er, traffic accid en t, wh ile en g ag ed in sp o rts activ ity V1 5 . 4 4 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, d riv er, traffic accid en t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
V1 1 . 4 2 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, d riv er, traffic accid en t, wh ile wo rk in g fo r an in co me
V1 3 . 5 1 P ed al cy clist in ju red in co llisio n with car, p ick -u p tru ck o r v an , p assen g er, traffic accid en t, wh ile en g ag ed in leisu re activ ity V1 5 . 4 8 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, d riv er, traffic accid en t, wh ile en g ag ed in o th er sp ecified activ ities
V1 1 . 4 3 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, d riv er, traffic accid en t, wh ile en g ag ed in o th er ty p es o f wo rk
V1 3 . 5 2 P ed al cy clist in ju red in co llisio n with car, p ick -u p tru ck o r v an , p assen g er, traffic accid en t, wh ile wo rk in g fo r an in co me V1 5 . 4 9 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, d riv er, traffic accid en t, d u rin g u n sp ecified activ ity
V1 1 . 4 4 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, d riv er, traffic accid en t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
•X35.44 Victim of volcanic eruption, street and highway, while resting,
sleeping, eating or engaging in other vital activities
V1 1 . 4 8 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, d riv er, traffic accid en t, wh ile en g ag ed in o th er sp ecified activ ities
V1 3 . 5 3 P ed al cy clist in ju red in co llisio n with car, p ick -u p
V1 1 . 4 9 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, d riv er, traffic accid en t, d u rin g u n sp ecified activ ity
V1 3 . 5 4 P ed al cy clist in ju red in co llisio n with car, p ick -u p
V1 1 . 5 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, p assen g er, traffic accid en t
V1 3 . 5 8 P ed al cy clist in ju red in co llisio n with car, p ick -u p
V1 1 . 5 0 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, p assen g er, traffic accid en t, wh ile en g ag ed in sp o rts activ ity
V1 3 . 5 9 P ed al cy clist in ju red in co llisio n with car, p ick -u p
V1 1 . 5 1 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, p assen g er, traffic accid en t, wh ile en g ag ed in leisu re activ ity
V1 1 . 5 2 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, p assen g er, traffic accid en t, wh ile wo rk in g fo r an in co me
V1 3 . 9 P ed al cy clist in ju red in co llisio n with car, p ick -u p tru ck o r
V1 1 . 5 3 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, p assen g er, traffic accid en t, wh ile en g ag ed in o th er ty p es o f wo rk
V1 3 . 9 0 P ed al cy clist in ju red in co llisio n with car, p ick -u p
V1 1 . 5 4 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, p assen g er, traffic accid en t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
V1 3 . 9 1 P ed al cy clist in ju red in co llisio n with car, p ick -u p
V1 1 . 5 8 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, p assen g er, traffic accid en t, wh ile en g ag ed in o th er sp ecified activ ities
V1 1 . 5 9 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, p assen g er, traffic accid en t, d u rin g u n sp ecified activ ity
V1 3 . 9 2 P ed al cy clist in ju red in co llisio n with car, p ick -u p
V1 1 . 9 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified p ed al cy clist, traffic accid en t
V1 3 . 9 3 P ed al cy clist in ju red in co llisio n with car, p ick -u p
V1 1 . 9 0 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in sp o rts activ ity
V1 3 . 9 4 P ed al cy clist in ju red in co llisio n with car, p ick -u p
V1 1 . 9 1 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in leisu re activ ity
V1 3 . 9 8 P ed al cy clist in ju red in co llisio n with car, p ick -u p
V1 1 . 9 2 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile wo rk in g fo r an in co me
V1 1 . 9 3 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in o th er ty p es o f wo rk
V1 3 . 9 9 P ed al cy clist in ju red in co llisio n with car, p ick -u p
V1 1 . 9 4 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
V1 4 P ed al cy clist in ju red in co llisio n with h eav y tran sp o rt v eh icle o r b u s
V1 1 . 9 8 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in o th er sp ecified activ ities
V1 4 . 0 P ed al cy clist in ju red in co llisio n
V1 1 . 9 9 P ed al cy clist in ju red in co llisio n with o th er p ed al cy cle, u n sp ecified p ed al cy clist, traffic accid en t, d u rin g u n sp ecified activ ity
V1 2 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle
V1 4 . 0 0 P ed al cy clist in ju red in
V1 2 . 0 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo ton ro vn eh
traffic
icle,
accid
d riv
en ter,
V1 4 . 0 1 P ed al cy clist in ju red in
V1 2 . 0 0 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to
n or nvtraffic
eh icle,
accidd en
rivt,er,wh ile en g ag ed in sp o rts activ ity
V1 4 . 0 2 P ed al cy clist in ju red in
V1 2 . 0 1 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to
n or nvtraffic
eh icle,
accidd en
rivt,er,wh ile en g ag ed in leisu re activ ity
V1 4 . 0 3 P ed al cy clist in ju red in
V1 2 . 0 2 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to
n or nvtraffic
eh icle,
accidd en
rivt,er,wh ile wo rk in g fo r an in co me
V1 2 . 0 3 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to
n or nvtraffic
eh icle,
accidd en
rivt,er,wh ile en g ag ed in o th er ty p es o f wo rk
V1 4 . 0 4 P ed al cy clist in ju red in
V1 2 . 0 4 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to
n or nvtraffic
eh icle,
accidd en
rivt,er,wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
V1 4 . 0 8 P ed al cy clist in ju red in
V1 2 . 0 8 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to
n or nvtraffic
eh icle,
accidd en
rivt,er,wh ile en g ag ed in o th er sp ecified activ ities
V1 4 . 0 9 P ed al cy clist in ju red in
V1 2 . 0 9 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to
n or nvtraffic
eh icle,
accidd en
rivt,er,d u rin g u n sp ecified activ ity
V1 2 . 1 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r vn eh
o nicle,
traffic
paccid
asseneng ter,
V1 4 . 1 P ed al cy clist in ju red in co llisio n
V1 2 . 1 0 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r nv oehn icle,
traffic
paccid
assenengt,er,wh ile en g ag ed in sp o rts activ ity
V1 4 . 1 0 P ed al cy clist in ju red in
V1 2 . 1 1 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r nv oehn icle,
traffic
paccid
assenengt,er,wh ile en g ag ed in leisu re activ ity
V1 4 . 1 1 P ed al cy clist in ju red in
V1 2 . 1 2 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r nv oehn icle,
traffic
paccid
assenengt,er,wh ile wo rk in g fo r an in co me
V1 4 . 1 2 P ed al cy clist in ju red in
V1 2 . 1 3 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r nv oehn icle,
traffic
paccid
assenengt,er,wh ile en g ag ed in o th er ty p es o f wo rk
V1 2 . 1 4 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r nv oehn icle,
traffic
paccid
assenengt,er,wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ
V1 4ities
. 1 3 P ed al cy clist in ju red in
V1 2 . 1 8 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r nv oehn icle,
traffic
paccid
assenengt,er,wh ile en g ag ed in o th er sp ecified activ ities
V1 4 . 1 4 P ed al cy clist in ju red in
V1 2 . 1 9 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r nv oehn icle,
traffic
paccid
assenengt,er,d u rin g u n sp ecified activ ity
V1 4 . 1 8 P ed al cy clist in ju red in
V1 2 . 2 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, u n spn ecified
o n traffic
paccid
ed alencyt clist,
V1 2 . 2 0 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, u n sp
n oecified
n traffic
accid
p ed alency
t, clist,
wh ile en g ag ed in sp o rts activ ity
V1 4 . 1 9 P ed al cy clist in ju red in
V1 2 . 2 1 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, u n sp
n oecified
n traffic
accid
p ed alency
t, clist,
wh ile en g ag ed in leisu re activ ity
V1 4 . 2 P ed al cy clist in ju red in co llisio n
V1 2 . 2 2 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, u n sp
n oecified
n traffic
accid
p ed alency
t, clist,
wh ile wo rk in g fo r an in co me
V1 4 . 2 0 P ed al cy clist in ju red in
V1 2 . 2 3 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, u n sp
n oecified
n traffic
accid
p ed alency
t, clist,
wh ile en g ag ed in o th er ty p es o f wo rk
al cy
clist in ju red in
V1 2 . 2 4 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, u n sp
n oecified
n traffic
accid
p ed alency
t, clist,
wh ile restin g , sleep in g , eatin g o r en g ag in g in oV1
th 4er. 2v 1italP ed
activ
ities
V1 2 . 2 8 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, u n sp
n oecified
n traffic
accid
p ed alency
t, clist,
wh ile en g ag ed in o th er sp ecified activ ities
V1 4 . 2 2 P ed al cy clist in ju red in
V1 2 . 2 9 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, u n sp
n oecified
n traffic
accid
p ed alency
t, clist,
d u rin g u n sp ecified activ ity
V1 4 . 2 3 P ed al cy clist in ju red in
V1 2 . 3 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, wh ile b o ard in g o r alig h tin g
V1 4 . 2 4 P ed al cy clist in ju red in
V1 2 . 3 0 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in sp o rts activ ity
V1 4 . 2 8 P ed al cy clist in ju red in
V1 2 . 3 1 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in leisu re activ ity
V1 4 . 2 9 P ed al cy clist in ju red in
V1 2 . 3 2 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, wh ile b o ard in g o r alig h tin g , wh ile wo rk in g fo r an in co me
V1 4 . 3 P ed al cy clist in ju red in co llisio n
V1 2 . 3 3 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in o th er ty p es o f wo rk
V1 4 . 3 0 P ed al cy clist in ju red in
V1 2 . 3 4 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, wh ile b o ard in g o r alig h tin g , wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
V1 4 . 3 1 P ed al cy clist in ju red in
V1 2 . 3 8 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in o th er sp ecified activ ities
V1 4 . 3 2 P ed al cy clist in ju red in
V1 2 . 3 9 P ed al cy clist in ju red in co llisio n with two - o r th ree-wh eeled mo to r v eh icle, wh ile b o ard in g o r alig h tin g , d u rin g u n sp ecified activ ity
V1 4 . 3 3 P ed al cy clist in ju red in
tru ck o r v an , p assen g er, traffic accid en t, wh ile en g ag ed in o th er ty
V1p5es. 5o fP wo
ed alrkcy clist in ju red in co llisio n with railway train o r railway v eh icle, p assen g er, traffic accid en t
tru ck o r v an , p assen g er, traffic accid en t, wh ile restin g , sleep in g , eatin g o V1
r en5 g. 5ag0 inPged in
o th
er vinital
activinities
al cy
clist
ju red
co llisio n with railway train o r railway v eh icle, p assen g er, traffic accid en t, wh ile en g ag ed in sp o rts activ ity
tru ck o r v an , p assen g er, traffic accid en t, wh ile en g ag ed in o th er sp ecified V1
activ
5 . 5ities
1 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, p assen g er, traffic accid en t, wh ile en g ag ed in leisu re activ ity
tru ck o r v an , p assen g er, traffic accid en t, d u rin g u n sp ecified activ ity
V1 5 . 5 2 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, p assen g er, traffic accid en t, wh ile wo rk in g fo r an in co me
v an , u n sp ecified p ed al cy clist, traffic accid en t
V1 5 . 5 3 P ed al cy clist in ju red in co llisio n
tru ck o r v an , u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in V1
sp 5o .rts
5 4 activ
P ed ity
al cy clist in ju red in co llisio n
tru ck o r v an , u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in V1
leisu
5 . 5re8 activ
P ed ity
al cy clist in ju red in co llisio n
tru ck o r v an , u n sp ecified p ed al cy clist, traffic accid en t, wh ile wo rk in g foV1
r an
5 . 5in9 coPme
ed al cy clist in ju red in co llisio n
with railway train o r railway v eh icle, p assen g er, traffic accid en t, wh ile en g ag ed in o th er ty p es o f wo rk
with railway train o r railway v eh icle, p assen g er, traffic accid en t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
with railway train o r railway v eh icle, p assen g er, traffic accid en t, wh ile en g ag ed in o th er sp ecified activ ities
with railway train o r railway v eh icle, p assen g er, traffic accid en t, d u rin g u n sp ecified activ ity
tru ck o r v an , u n sp ecified p ed al cy clist, traffic accid en t, wh ile en gV1
ag ed
p esin
o fjuwo
5 . 9inP oedthal ercytyclist
redrkin co llisio n with railway train o r railway v eh icle, u n sp ecified p ed al cy clist, traffic accid en t
tru ck o r v an , u n sp ecified p ed al cy clist, traffic accid en t, wh ile restin g , sleep
r en
g agininjug red
in in
o thcoerllisio
v italn activ
V1in5 g. 9, 0eatin
P edg alo cy
clist
withities
railway train o r railway v eh icle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in sp o rts activ ity
tru ck o r v an , u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in V1
o th
5 .er9 1sp Pecified
ed al cyactiv
clistities
in ju red in co llisio n with railway train o r railway v eh icle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in leisu re activ ity
tru ck o r v an , u n sp ecified p ed al cy clist, traffic accid en t, d u rin g u n sp ecified
V1 5activ
. 9 2 ity
P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile wo rk in g fo r an in co me
V1 5 . 9 3 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in o th er ty p es o f wo rk
with h eav y tran sp o rt v eh icle
n o notraffic
r b uaccid
s, d en
rivt er,
V1 5 . 9 4 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
co llisio n with h eav y tran sp o rt v eh nicle
o n otraffic
r b uaccid
s, den
rivt, er,
wh ile en g ag ed in sp o rts activ ity
V1 5 . 9 8 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n sp ecified p ed al cy clist, traffic accid en t, wh ile en g ag ed in o th er sp ecified activ ities
co llisio n with h eav y tran sp o rt v eh nicle
o n otraffic
r b uaccid
s, den
rivt, er,
wh ile en g ag ed in leisu re activ ity
V1 5 . 9 9 P ed al cy clist in ju red in co llisio n with railway train o r railway v eh icle, u n sp ecified p ed al cy clist, traffic accid en t, d u rin g u n sp ecified activ ity
co llisio n with h eav y tran sp o rt v eh nicle
o n otraffic
r b uaccid
s, den
rivt, er,
wh ile wo rk in g fo r an in co me V1 6 P ed al cy clist in ju red in co llisio n with
n o n mo
o thtoverreh icle
co llisio n with h eav y tran sp o rt v eh nicle
o n otraffic
r b uaccid
s, den
rivt, er,
wh ile en g ag ed in o th er ty p es o f wo rk V1 6 . 0 P ed al cy clist in ju red in co llisio n nwith
o n mo
o th
tov er
reh icle, d riv ner,o n traffic
accid en t
co llisio n with h eav y tran sp o rt v eh nicle
o n otraffic
r b uaccid
s, den
rivt, er,
wh ile restin g , sleep in g , eatin g o r en g ag in g in V1
o th6 er
. 0 v0 ital
P edactiv
al cyities
clist in ju red in co llisio nn with
o n mooto
th
v reh
er icle, d riv ner,o n traffic
accid en t, wh ile en g ag ed in sp o rts activ ity
co llisio n with h eav y tran sp o rt v eh nicle
o n otraffic
r b uaccid
s, den
rivt, er,
wh ile en g ag ed in o th er sp ecified activ ities
V1 6 . 0 1 P ed al cy clist in ju red in co llisio nn with
o n mooto
th
v reh
er icle, d riv ner,o n traffic
accid en t, wh ile en g ag ed in leisu re activ ity
co llisio n with h eav y tran sp o rt v eh nicle
o n otraffic
r b uaccid
s, den
rivt, er,
d u rin g u n sp ecified activ ity
V1 6 . 0 2 P ed al cy clist in ju red in co llisio nn with
o n mooto
th
v reh
er icle, d riv ner,o n traffic
accid en t, wh ile wo rk
with h eav y tran sp o rt v eh icle noor nbtraffic
u s, accid
p assen
engt er,
co llisio n with h eav y tran sp o rt v eh iclenoornbtraffic
u s, accid
p assen
en gt,er,
wh ile en g ag ed in sp o rts activ ity
co llisio n with h eav y tran sp o rt v eh iclenoornbtraffic
u s, accid
p assen
en gt,er,
wh ile en g ag ed in leisu re activ ity
co llisio n with h eav y tran sp o rt v eh iclenoornbtraffic
u s, accid
p assen
en gt,er,
wh ile wo rk in g fo r an in co me
co llisio n with h eav y tran sp o rt v eh iclenoornbtraffic
u s, accid
p assen
en gt,er,
wh ile en g ag ed in o th er ty p es o f wo rk
co llisio n with h eav y tran sp o rt v eh iclenoornbtraffic
u s, accid
p assen
en gt,er,
wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
co llisio n with h eav y tran sp o rt v eh iclenoornbtraffic
u s,, pwh
assen
ile gener,
g ag ed in o th er sp ecified activ ities accid en t
co llisio n with h eav y tran sp o rt v eh iclenoornbtraffic
u s,, pd assen
u rin g er,
u n sp ecified activ ity accid en t
with h eav y tran sp o rt v eh icle o r b u s, u n sp
n oecified
n traffic
accid
p ed alency
t clist,
co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n nspoecified
n traffic
accid
p ed al
en cy
t, clist,
wh ile en g ag ed in sp o rts activ ity
co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n nspoecified
n traffic
accid
p ed al
en cy
t, clist,
wh ile en g ag ed in leisu re activ ity
co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n nspoecified
n traffic
accid
p ed al
en cy
t, clist,
wh ile wo rk in g fo r an in co me
co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n nspoecified
n traffic
accid
p ed al
en cy
t, clist,
wh ile en g ag ed in o th er ty p es o f wo rk
co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n nspoecified
n traffic
accid
p ed al
en cy
t, clist,
wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n nspoecified
n traffic
accid
p ed al
en cy
t, clist,
wh ile en g ag ed in o th er sp ecified activ ities
co llisio n with h eav y tran sp o rt v eh icle o r b u s, u n nspoecified
n traffic
accid
p ed al
en cy
t, clist,
d u rin g u n sp ecified activ ity
with h eav y tran sp o rt v eh icle o r b u s, wh ile b o ard in g o r alig h tin g
co llisio n with h eav y tran sp o rt v eh icle o r b u s, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in sp o rts activ ity
co llisio n with h eav y tran sp o rt v eh icle o r b u s, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in leisu re activ ity
co llisio n with h eav y tran sp o rt v eh icle o r b u s, wh ile b o ard in g o r alig h tin g , wh ile wo rk in g fo r an in co me
co llisio n with h eav y tran sp o rt v eh icle o r b u s, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in o th er ty p es o f wo rk
V1 4 . 3 4 P ed al cy clist in ju red in co llisio n with h eav y tran sp o rt v eh icle o r b u s, wh ile b o ard in g o r alig h tin g , wh ile restin g , sleep in g , eatin g o r en g ag in g in o th er v ital activ ities
V1 4 . 3 8 P ed al cy clist in ju red in co llisio n with h eav y tran sp o rt v eh icle o r b u s, wh ile b o ard in g o r alig h tin g , wh ile en g ag ed in o th er sp ecified activ ities
V1 4 . 3 9 P ed al cy clist in ju red in co llisio n with h eav y tran sp o rt v eh icle o r b u s, wh ile b o ard in g o r alig h tin g , d u rin g u n sp ecified activ ity
Clinical Data Capture
Choose terms from a coding scheme
enter search:
cystitis
Cholecystitis,
Cystitis,
Iatrogenic
NOS
cystitis
NOS
Acute
Chronic
Chemical
cystitis
cholecystitis
cystitis
Subacute
Acute
Postoperative
cholecystitis
cystitis,
cystitis
NOS
Follicular
Bacterial
Drug induced
cystitis
Cholecystitis
cystitis
Idiopathic
Bacterial
Radiation
cystitis
cystitis
cystitis
etc
next page
Too Big
...picking lists
too long
Too Small
...not enough
clinical detail
Defusing the exploding bicycle:
500 codes in pieces
► 10 things to hit…
► Pedestrian / cycle / motorbike / car / HGV / train / unpowered
vehicle / a tree / other
► 5 roles for the injured…
► Driving / passenger / cyclist / getting in / other
► 5 activities when injured…
► resting / at work / sporting / at leisure / other
► 2 contexts…
► In traffic / not in traffic
V12.24 Pedal cyclist injured in collision with two- or three-wheeled motor vehicle,
unspecified pedal cyclist, nontraffic accident, while resting, sleeping, eating or
engaging in other vital activities
Conceptual Lego… it could be...
Goodbye to picking lists…
Structured Data Entry
File
Edit
Help
Cycling Accident
What you hit
Your Role
Activity
Location
Intelligent Forms
And generate it in language
Logic as the clips for
“Conceptual Lego”
gene
hand
protein
extremity
polysacharide
body
cell
expression
chronic
Lung
acute
infection
inflammation
abnormal
normal
bacterium
deletion
polymorphism
ischaemic
virus
mucus
Logic as the clips for
“Conceptual Lego”
“SNPolymorphism of CFTRGene causing Defect in MembraneTransport of
Chloride Ion causing Increase in Viscosity of Mucus in CysticFibrosis…”
“Hand which is
anatomically
normal”
Species
Genes
Protein
Function
Gene in humans
Disease
Protein coded by
gene in humans
Build complex
representations from
modularised
primitives
Function of
Protein coded by
gene in humans
Disease caused by abnormality in
Function of
Protein coded by
gene in humans
But of course the logic is not all you need
Modules in the GALEN Server
Server
Multilingual
Module
Client
Client
Application
A
P
I
Reference Management
Multilingual Dictionaries
Concept
Module
Common Reference
Model
Code Conversion
Module
Code Store
Indexing
Module
Extrinsics Store
A single point of access for language, classification, code
conversion, and indexing - well separated internally
Problem:
System may be perfect
…but
Users still fallible
User Problems
Inter-rater variability
ART & ARCHITECTURE THESAURUS (AAT)
Domain: art, architecture, decorative arts, material culture
Content: 125,000 terms
Structure: 7 facets, 33 polyhierarchies
Associated concepts (beauty, freedom, socialism)
Physical attributes (red, round, waterlogged)
Style/Period (French, impressionist, surrealist)
Agents: (printmaker, architect, jockey)
Activities: (analysing, running, painting)
Materials (iron, clay, emulsifier)
Objects: (gun, house, painting, statue, arm)
Synonyms
Links to ‘associated’ terms
Access: lexical string match;
hierarchical view
User Problems
Inter-rater variability
Headcloth
Cloth
Scarf
Model Person
Woman
Adults
Standing
Background
Brown
Blue
Chemise
Dress
Tunics
Clothes
Suitcase
Luggage
Attache case
Brass Instrument
French Horn
Horn
Tuba
X
X
X
X
X
X
X
X
X
X
X
X
X X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X X
X
X X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
User Problems
Inter-rater variability
New codes added per Dr per year
READ CODE
Practice A
Sore Throat Symptom
0.6
Visual Acuity
0.4
ECG General
2.2
Ovary/Broad Ligament Op
7.8
Specific Viral Infections
1.4
Alcohol Consumption
0
H/O Resp Disease
0
Full Blood Count
0
Practice B
117
644
300
809
556
106
26
838
Repeatability
Inter-rater reliability
► Only ICPC has taken seriously
► Originally less than 2000 well tested rubrics with proven
inter-rater reliability across five languages
►As it has been put into wider use, has grown and is less tested
► Includes the delivery software
► Confounding, but we can’t ignore it
Where next?
The genome / ’omics explosion
► Open Biolological Ontologies (OBO)
► Gene Ontology, Gene expression ontology (MGED), Pathway
ontology (BioPAX), …
►400+ bio databases and growing
► National Cancer Institute Thesaurus
► CDISC/BRIDG - Clinical Trials
► HL7 genomics model…
► …
Coming to an EHR near you!
Enter the ‘O’ word the ‘M’ word
and the ‘S’ word
► “Ontologies” - claimed by philsophers, computer
scientists, …
► Logically, computationally solid skeletons
► “Metadata”
► Applications that know what they need and resources that
can say what they are about
► “Service Oriented Architectures”
► Loosely coupled computing based on discovery
►The GRID
… and the Semantic Web / GRID
… and E-Science / E-Health
… and digital libraries
… and … and
► RDF, RDFS, OWL, SWRL, WSDL, Web Services,…
► W3C Healthcare and Life Sciences Special Interest Group
► ISO 11179
► Dublin Core
► SKOS
► “Metadata and ontologies with everything”
► Google & web mining
► Text Processing
► Open Directory & Wikipedia - “Folksonomies” & social computing
► …
It’s a big open world out there!
Key issue 1:
Creating an open community
► Terminologies have succeeded for three
reasons
► Coercion - use them or don’t get paid
►ICD-CM, CPT, MEDDRA, Read 2
► They belonged to the community and were useful or key to
software
►LOINC, HL7v2, Gene Ontology, Read 1 …
► They gave access to a key resource
►MeSH, BNF, …
Logic + Web liberates users
Open ‘Just-in-time Terminology’
► If you can test the consequences then you can give users
the freedom to develop
► New compositions
► New additions to established lists
► Hide the complexity
► “Close to user forms”
►GALEN’s “Intermediate Representation”
►Training time down from 3 months to 3 days!
►The logic is the assembly language
► Move the development to the community
► Look at OpenDirectory, Wikipedia, FLKR, etc.
►Social computing
► Requires more and better tools
► Requires a different style of curation
Worldwide
Resources
GALEN’s Pre-Web version
Local author
uses resources & templates
to formulate definition
templates
Local
Author
needs new
terms for application
Server validates &
organises
Local author
checks
Local
Ontology
updates
problems
Central Gurus
integrate & fix
problems
Central
Ontology
Key issue II:
Applications centric development
► If it is built for everything it will be fit for nothing!
►Must have a way to see if it works
► If it is built for just one thing it will not be fit even for that
►Change is the only constant
► Cannot predict which abstractions needed in
advance
► Even very large ontologies tend to be missing 50% or more
of terms in practice
►Compose them when you need them and share
► Is there a optimal ‘90-10’ point?
► You can only tell against a specific application
Applications centric Development
Meta-authoring
Common Terminology/
Ontology
Meta-authoring
authoring
environments
Intermediate Representations
clinicians / Applications builders
Empowered Authors
clinical
applications
Key issue III:
Binding to the EHR
► HL7 v3 + SNOMED = Chaos
► Unless we can formalise the mutual constraints
►The documentation is beyond human capacity
►To write or to understand
► Templates/Archetypes + SNOMED =
Missed opportunities
► Unless we avoid trivialising terminology
… or chaos if we attempt to use the terminology
► Requires new tools
► Formalisms probably adequate
Key issue IV:
Decision support
►Meaningful decision support is still rare
►Terminology is not the only problem
►But it is a barrier
►Ontology should be the scaffolding
►But requires the terminology to be computable
►SNOMED still too idiosyncratic to use easily
►Inter-rater reliability crucial
►Can we afford GIGO for patient management?
►Semantics of combined EHR+Terminology must be
well defined
Key issue V:
Avoiding “Pregacy”
► Prebuilt legacy
► Errors built in from the beginning
► ≤ .01% of SNOMED coded data to be held in 10
years time has been collected
► Fixes now will be less expensive than fixes later
► Rigorous schemas rigorously adhered to
► Conformance and Regression testing
►Cannot depend on people to do it right
►Must be formally verifiable
► It’s software - Let’s have some basic software engineering!
Key issue VI:
Empirical data
► Need empirical data on
► What’s worth doing - what’s esssential
►Language used by doctors
►Terms used
► What works
►Reliability of terms used - errors made
►Effect on Decision Support and other applications
► What scales
►What are the consequences of design decisions
► Effort required to develop software
►Usability of development tools
► Effort required by users
►Usability of interfaces and clinical systems
► Where is the science base for our work?
Key issue VII:
Human FactorsHelping with a humanly impossible task
► Language technology will help
► But will always have limitations
► Tailored forms will help
► But we must beet the combinatorial explosion
► …but the key issues are organisational, social
& clinical
► …and needs empirical data
Requires serious investment and
Commitment
Part II: Binding Terminology to EHR
and Messages - an approach
using new techniques
Patient Specific Records (1)
Information Model
(Patient Data Model)
Inference Model
(Guideline Model)
Dynamic Guideline
Knowledge (2b)
Concept Model
(Ontology)
Static Domain
Knowledge (2a)
But what are codes anyway?
How do they relate to medical
records?
► The odd case of clinical record models
► Three different groups
►Meaning/Terminology ► SNOMED, ICD, LOINC, …
►Data structures - Messages and Records ► HL7, OpenEHR/CEN13606
►Decision support ►GLIF, GLEEM, Pro Forma, EON, ASBRU, …
Problems….
Family History of Heart Disease
May exist in
terminology as single
term
May exist as two
terms and a link, and
be stored as such in
the EPR
NB FH heart disease
does not mean
patient has heart
disease
Problems….
Negation & context Terms
► Very unlikely to be exhaustively in static terminology
► Because too numerous
► Must not be detached from ‘kernel term’
► Patient with ‘no heart disease’ must never be mistaken for patient with ‘heart
disease’
► Terminological phenomenon
► But places particular constraint on how the information model, and queries on
it, must work
► Despite this…
► Legacy terminologies pre-coordinated negated terms…but only a subset
► Legacy information systems must therefore allow negation to cover e.g.
negations not present in terminology
Problems….
Negation & context Terms
Logical negation
very problematic
Information model
must support
negation…but how
to reason across
double negatives?
Problems…. No renal disease?
Negation and conjunction in the terminology
Another challenge to answering the query: possibility of conflicting
information
Problems….Diabetic?
Lots of codes
in the
terminology
under expected
abstraction…
…but includes assertion &
negation of (not always
specified) other diseases
Meaning & Use
► Nesting of Terminology and Medical record
► Nesting of terminology in statements
►Nesting of statements in Archetypes
► Nesting of Archetypes in Templates
► Nesting of templates in records
► Querying of the result
► How do I ask if the patient has
►Had a elevated diastolic blood pressure?
►Has had their left ureter removed?
Requirement:
Manage the Interface
► Identify Information required
► abstractions needed for inference
► concepts needed to record EHR
► Allocate information between information and concept
models
► Identify and agree mutual constraints
► Represent all information unambiguously
► Design the structure in the information model
► Represent the Terminology
► Represent the Terminology representation in the information model
► Represent agreed mutual constraints formally
Basis of allocation
► Information representable only in one way and in one
model
► Or, must be way to spot equivalence and also to generate all
possible forms for querying
► Different information types only representable in one
model
► Or explicit mutual constraints
► Business rules of medical institution and clinical rules may interact
The Terminfo / NPfIT Hypothesis
► The record model (HL7)
► Concerned with business model
► The terminology (S-CT)
► Concerned with clinical implications
►Encapsulate all clinical information
► The inference model - as yet undefined
► the meaning of the combined record + terminology models
HL7 & SNOMED-CT
Potential Conflicts
► HL7
► MoodCode - Event, Intention, Risk, …
► Subject of care - patient, family member, fetus, …
► Negation indicator - true or false
► Status - done, aborted, suspended, etc. ► “Flavours of null”
► SNOMED-CT Context wrapper
► Context dependent finding/procedure
Family history
Request
With/without / present absent
► Logical Equivalence
► What do the two really mean together?
► What is a decision support system to use
Observation class
Context model
Kernel clinical notion
Terminology/Ontology
Example ontology nested in the
EHR
the ehr (hl7 rim)
[moodCode=“Event”
subject=“Relative”
code={ diabetes (subject person_in_family) } ]
the ontology (snomed-ct)

<family_hx (assoc_find Diabetes)>
the combined meaning
What’s it really mean?
What is legal? Required?
Mandatory?…
Meaning and Data structure Models
Model of
Meaning/
Terminology
class of
patients &
diseases
Diabetes
Condition
Diabetes
Type 1
Participation
Observation
Diabetes
Observation
Type 1
Diabetes
Observation
Individual
Codes in
Information
Model data
structures
Condition
has_subcode
Information
Model
Classes
of data
structures
Diabetes
Type 2
Diabetes
Diabetes
Type 1
Diabetes
Type 2
Classes of
codes
The information model is ‘meta’
to the model of meaning model
► For ‘information model’ read
“Model of data structure”
► What we really represent in HL7, OpenEHR, Templates and
Archetypes
►What information should be present in a form/message/record
► For “model of meaning” read
“Model of our conceptualisation of the world”
► Our understanding of what is universally / typically true of patients,
diseases, treatments etc.
► The data structures are fundamentally syntax:
The model of meaning is fundamentally semantics
Most obvious for negation
► Domain knowledge
► All animals, including human organisms, have a body temperature
► It does not make biological sense to talk of an animal without a body temperature
► Even if it is dead and the body temperature is ambient
► Information Structure Knowledge
► A form / data structure / Archetype about a person may, or may not have an
entry / field / element for ‘body temperature’.
► The vital signs form for a person contains an entry for body temperature
► The chief complain form for a person does not contain an entry for body
temperature
“Aboutness” or “Topic”
► Data structures are “about” something
► A data structure for diabetes is about “Diabetes” or diabetic
patient
► Domain entities are not “about” anything
► Diabetes is not about anything.
► John’s diabetes is not about anything
So what is ‘Terminology’
► A representation (model) of meaning
► An “ontology” in the computer science sense
►A theory to be tested against the world
► The set of axioms and definition prior to classification
►What it is sensible to say
► A representation in of the representation of
meaning
► The ‘codes’ organised so as to reflect the model of meaning
►Reflecting the result of classification
► A specific set of things to be said
► A lexicon
► How to say it
Terminology bound to the data
structure model
►A terminology bound to a data structure
model
►The codes organised so as to be processed
►What it is allowed or required to say in a particular
context
►What should be verified to check that a message /
record is valid
First represent the reference
model in OWL
► Parallel to OpenEHR Reference Model or HL7
RIM
► All association and attribute properties
subproperties of has_subelement
► Abbreviated to “has_subel”
►NB No distinction between associations and attributes in OWL.
►In theory attributes do not need inverses. In practice, to
capture context, it is better to include them
►EHR + Terminology makes for strange UML
The Reference Ontology
► For Templates
► For The RIM
The Properties
► Templates
► The RIM
Allows unfolding of Template
along has_sub_el
Definition
Unfolding
Then represent the coding
system
► Every class in the coding system becomes an
individual in the EHR model
► In theory linked by the relation has_subcode/is_subcode_of
► All IDs etc. are datatype properties of the individual
► Naming convention: “…_code”
► For every code define a class for the code and
its descendants
► Only one direct individual in the class
► Naming convention “…_code_or_subcode
► Make class hierarchty mirror code hierarchy
►Even if this makes no sense in the domain model
►Modelling codes not the Domain
Code selection:
Matches requirements from NHS
to represent:
► List of specified individual codes
► Bind to: {x_code1, x_code2,…,x_coden}
► The set of a code or any of its children
► Bind to: X_code_or_its_children
►Possibly minus some subhierarchy of terms
► The set of a code’s children but not the code
itself
► Bind to: (X_code_or_its_children AND NOT {x_code})
► Any boolean combination of the above
► e.g. Bind to: {x_code} AND Y_code_or_its_children AND
NOT (Z_code_or_its_children AND NOT {z_code})
Binding terminology using
placeholders
► Borrow from Archetypes the notion of a
placeholder code in information model
► Whenever a code or code set is required, create a
placeholder code and insert it
►The message or template author does not need to know
anything about the coding system
►Although it is helpful if he/she documents their intent
► Later add binding axioms that the placeholder is logically
equivalent to some set of codes in the appropriate coding
system
►Can be expressed as a boolean combination of classes of
codes
Meaning and Data structure Models
Model of
Meaning/
Terminology
class of
patients &
diseases
Diabetes
Condition
Diabetes
Type 1
Participation
Observation
Diabetes
Observation
Type 1
Diabetes
Observation
Individual
Codes in
Information
Model data
structures
Condition
has_subcode
Information
Model
Classes
of data
structures
Diabetes
Type 2
Diabetes
Diabetes
Type 1
Diabetes
Type 2
Classes of
codes
Using Placeholders
Observation
Condition
has_subcode
Participation
Diabetes
Observation
Diabetes
Placeholder 1
Type 1 Diabetes
Observation
Placeholder 2
Diabetes
Type 1
Diabetes
Type 2
A concrete example
Kinds of codes
► Internal Codes
► Part of the Archetype or HL7 mechanism
► External codes - from elsewhere e.g. SNOMED-CT
► Placeholder codes
► Correspond ot the references in the Archetype
► Will be bound to external codes by “binding axioms”
► Binding axioms
► Bind placeholders to external codes with owl:EquivalentClass()
axioms
► Show up in Code hierarchy if named
► Protégé-requires them to be named
Kinds of codes
Binding using placeholders
► Using placeholders
► And binding axioms
A more complex example
involving SNOMED Context
► A SNOMED Request medication must combine
medication_act and request context:
► Request_medication_binding_axiom_snct ≡
Req_for_Med_admin_placeholder ≡
(SNCT_medication_admin_act_code_or_its_subcodes AND
SNOMED_request_context_code_or_its_subcodes)
► A SNOMED Request code must have qualifier
procedure_request_code with value request_code
► SNCT_request_context_code_or_its_subcodes ≡
SNCT_code AND
has_qualilfier SOME
(Qualifier AND has_name_code VALUE
procedure_request_code AND
has_value_code VALUE request_code)
…and from elsewhere in the
same example
► the rule for compatible Act_status_codes for
requests as per NPfIT models
► Request_compatible_act_code_placeholder ≡
(Act_aborfted_code_or_its_subcodes OR
ACT_active_code_or_its_subcodes OR
ACT_completed_code_or_its_subcodes)
Hypotheses
► This representation allows full expression of all
archetype and HL7 RIM constraints
► Provided we have support for concrete expressions
►Numeric ranges, string matching, and regular expressions
►In OWL and OWL 1.1 spec although not quite
implemented in all reasoners
► Transformation languages can be implemented
as a grammar with typed variables
► Terminology to bindiing model - regular and straightforward
► Joint to contingent model for decision support
►Best standard under investigation
What’s been left out…
► Inferring the state of the patient
► What it is all about!
► Ontology is what is true of all patients
Decision support is about what is true of THIS patient
► Must map back to the space of diseases and patients
► Another talk
Diseases and patients: individuals in the model of meaning
Model of
Meaning/
John
smith
Terminology
and
hisof
class
patients &
Diabetes
diseases
Diabetes
Type 2
Diabetes
Condition
Diabetes
Type 1
type 1
Participation
Observation
Diabetes
Observation
Type 1
Diabetes
Observation
Individual
Codes in
Information
Model data
structures
Condition
has_subcode
Information
Model
Classes
of data
structures
Diabetes
Diabetes
Type 1
Diabetes
Type 2
Classes of
codes
Summary: Lessons & Directions
for terminology binding
► The model of the data structure is meta to the
model of meaning
► The model of meaning is a model of categories of diseases
and procedures
►Inference is about individual patients’ diseases and procedures
► Use of placeholders defines a clean interface
► Logic based formalisms can provide the glue
► OWL works surprisingly well
Summary: Lessons & Directions
for terminology
► Understand scaling and the combinatorial explosion
► All lists are too big and too small
► Too many niches to cope with one by one
► Focus on applications
► Answer “What’s it for?”
► Don’t be afraid to use logic
► Bind terminology to EHR and Decision support
► It’s an open world changing rapidly
► Especially basic biology
► Avoid Pregacy
► Gather empirical data
► Human factors are critical