practicum presentation nidhi 2013
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Nidhi GulatiUNC Carolina Health Informatics Program Practicum
May 24, 2013
Current Data ProblemsCurrent data standards are inadequate to support exchange and re-use
of data collected and used in clinical domains
Data may be exchanged between providers, but variations in meaning, measurement, and coding systems, etc. result in data that cannot be easily used for patient care or support secondary uses such as quality improvement and research
Terminologies (ICD and SNOMED) alone are insufficient to cope up with these challenges
This lack of semantic interoperability results in poor information quality in health care and in secondary data uses
'Standardizing clinical data elements' paper by Meredith Nahm, et al.'Knowledge Aquisition from and Semantic Variability in Schizophrenia Clinial Trial Data' paper by Meredith Nahm
Solution
Standardization of data elements to support patient care and secondary uses is strongly considered part of the solution to the problems of lack of semantic interoperability and poor information quality in healthcare
Standardization will facilitate meaningful quality exchange of health information and re-use of data
'Standardizing clinical data elements' paper by Meredith Nahm, et al.'Knowledge Aquisition from and Semantic Variability in Schizophrenia Clinial Trial Data' paper by Meredith Nahm
Why the same Standards?
Standards enable interoperability
Three aspects of interoperability:Technical: Moving data from system A to system BSemantic: Ensuring that systems A and B understand
the data in the same wayProcess: Enabling business processes at organizations
housing systems A and B to work together
http://www.hl7.org/documentcenter/public_temp_973A0F7F-1C23-BA17-0C22BE995BB25E98/training/IntroToHL7/player.html
CDISC and HL7There are two standards development organizations relevant for this work:
Clinical Data Standards Interchange Consortium (CDISC) – the data standards organization for FDA regulated research
Health Level Seven (HL7) – the data standards development organization for Healthcare
2012
Health Level Seven (HL7)
The Philosophy1) Developing data element standards with healthcare and
secondary data use stakeholders will enable standards that work for patient care AND also support secondary data uses such as research, performance measurement, quality improvement, and public health reporting
2) Supporting only one use is insufficient3) Healthcare first – data generated and used in Screening,
Diagnosis, Treatment & Management
- CDER Data Standards Webpage N
ahm
, M.,
Wal
den,
A.,
McC
ourt
, B.,
Piep
er, K
., H
oney
cutt
, E.,
Ham
ilton
, C.D
., H
arri
ngto
n, R
.A.,
D
iefe
nbac
h, J.
, Kis
ler,
B.,
Wal
ker,
M.,
Ham
mon
d, W
.E.,
Sta
ndar
dizi
ng C
linic
al D
ata
Elem
ents
. Int
erna
tiona
l Jo
urna
l of F
unct
iona
l Inf
orm
atic
s an
d Pe
rson
alis
ed M
edic
ine
(IJF
IPM
) Spe
cial
Issu
e on
: "Th
e In
form
atic
s of
M
eta-
data
, Que
stio
ns, a
nd V
alue
Set
s". V
ol. 3
, No.
4, 2
010.
More Philosophy4. Clinical professional societies are the only
authoritative source of clinical definitions5. Data element is the fundamental unit of
information exchange and use6. Data elements should be standardized (i.e., ANSI
accredited SDO)7. Standard data elements should be freely
available in searchable metadata registries
Nah
m, M
., W
alde
n, A
., M
cCou
rt, B
., Pi
eper
, K.,
Hon
eycu
tt, E
., H
amilt
on, C
.D.,
Har
ring
ton,
R.A
.,
Die
fenb
ach,
J., K
isle
r, B
., W
alke
r, M
., H
amm
ond,
W.E
., S
tand
ardi
zing
Clin
ical
Dat
a El
emen
ts.
Inte
rnat
iona
l Jou
rnal
of F
unct
iona
l Inf
orm
atic
s an
d Pe
rson
alis
ed M
edic
ine
(IJF
IPM
) Spe
cial
Issu
e on
: "T
he In
form
atic
s of
Met
a-da
ta, Q
uest
ions
, and
Val
ueSe
ts".
Vol
. 3, N
o. 4
, 201
0.
Therapeutic Area Projects Cardiology
Acute Coronary Syndromes (ACS) Cardiovascular Imaging
Tuberculosis
Anesthesia- preop. Assmt. Pre-hospital Emergency Care Diabetes (pilot) Trauma registration Schizophrenia Major Depressive Disorder ICU, Pediatric exercise testing,
TBI
Cardiology R1 May 2008 – 24 data elements R2 Jan. 2012 – 383 data elements CDISC SDTM representation
underway Tuberculosis
R1 Sept 2008 – 139 data elements CDISC SDTM representation
release for public comment summer 2012
R1 Sept 2011, R2 Jan 2013 R1 Sept 2010, CDA R2 2011 Diabetes pilot completed 2011 New project Ballot 2012, re-ballot May/Sept
2013 Ballot May/Sept 2013 New projects in discussion
Overview of Duke Data Element Standards Work Presentation, 2012
Data Element Standardization Process
1. Data element Knowledge Acquisition- Identify data elements here, Major Depressive Disorder (MDD) questionnaires
2. Data element Synthesis (not within my scope)
3. Data element Definitions- Clinical definitions from Authoritative Clinical Professional Society(ies) and form context
Knowledge Acquisition
Elements
1. Experts2. Documented knowledge of experts
Data collection formsClinical guidelinesClinical documentationData dictionaries, e.g.,
RegistriesEHR screens /
systemsProtocols
Overview of Duke Data Element Standards Work Presentation, 2012
Anatomy of a Data Element
Data element is the fundamental unit of data exchange
It is an association of a data element concept and a representation primarily of a value domain (ISO/IEC 11179)
AIM severity:
Data Element
AIM severity:
Data Element
AIM severity:
Data Element
AIM severity:Question or
prompt
Value format
Data Element
NoneMinimalMildModerateSevere
Abnormal Involuntary Movement Scale (AIMS) – Rating Scale Data Element example
Abstracted Data Elements & Definitions
The Drug Abuse Screening Test (DAST)
Abstracted Data Elements & Definitions
Total CountMDD Questionnaires # 12
MDD Data Elements # 205
MDD Definitions # 205
MDD Permissible Value list (PVL) # 813
FundingThe work presented here in:
Major Depressive Disorder (R24FD004656-01)
was made possible by funding from the Food and Drug Administration (FDA), a component of the Department of Health and Human Services (HHS).
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