2. Current Data Problems
Current 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
3. 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
4. Why the same Standards?
Standards enable interoperability
Three aspects of interoperability:
Technical: Moving data from system A to system B
Semantic: Ensuring that systems A and B understand
the data in the same way
Process: 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
5. CDISC and HL7
There 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
7. The Philosophy
1) 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 insufficient
3) Healthcare first – data generated and used in Screening,
Diagnosis, Treatment & Management
- CDER Data Standards
Webpage
Nahm,M.,Walden,A.,McCourt,B.,Pieper,K.,Honeycutt,E.,Hamilton,C.D.,Harrington,R.A.,
Diefenbach,J.,Kisler,B.,Walker,M.,Hammond,W.E.,StandardizingClinicalDataElements.International
JournalofFunctionalInformaticsandPersonalisedMedicine(IJFIPM)SpecialIssueon:"TheInformaticsof
Meta-data,Questions,andValueSets".Vol.3,No.4,2010.
8. More Philosophy
4. Clinical professional societies are the only
authoritative source of clinical definitions
5. Data element is the fundamental unit of
information exchange and use
6. Data elements should be standardized (i.e., ANSI
accredited SDO)
7. Standard data elements should be freely
available in searchable metadata registries
Nahm,M.,Walden,A.,McCourt,B.,Pieper,K.,Honeycutt,E.,Hamilton,C.D.,Harrington,R.A.,
Diefenbach,J.,Kisler,B.,Walker,M.,Hammond,W.E.,StandardizingClinicalDataElements.
InternationalJournalofFunctionalInformaticsandPersonalisedMedicine(IJFIPM)SpecialIssueon:
"TheInformaticsofMeta-data,Questions,andValueSets".Vol.3,No.4,2010.
9. 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
10. 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
11. Knowledge Acquisition
Elements
1. Experts
2. Documented knowledge of
experts
Data collection forms
Clinical guidelines
Clinical documentation
Data dictionaries, e.g.,
Registries
EHR screens /
systems
Protocols
Overview of Duke Data Element Standards Work Presentation, 2012
12. 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
AIM severity:
Data Element
AIM severity:
Data Element
AIM severity:
Data Element
AIM severity:
Question or
prompt
Value format
Data Element
None
Minimal
Mild
Moderate
Severe
17. Total Count
MDD Questionnaires # 12
MDD Data Elements # 205
MDD Definitions # 205
MDD Permissible Value list (PVL) # 813
18. Funding
The 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).