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Making Terminology work
Driving in situ use of wicked
classification schemes with
commoditised software
Werner van Huffel
Regional Strategist, Microsoft APAC
wvhuffel@microsoft.com
Associations:
The Author is an employee of Microsoft and undertaking health Informatics field studies.
Masters degree in Health Information Management (Health Informatics) [HIM-HI], University of Sydney,
Australia
Acknowledgements as:
Raphael Mastier (Microsoft, France)
Marc Horowitz (HealthLanguage, Global)
Andrew Kirby (Microsoft, UK)
Neil Jordan (Microsoft, Global)
Brian Levy (HealthLanguage, USA)
“…Houston, we've had a problem...”
- Apollo 13, Lovell J. A. , 1970
Clinicians wanted this
Got this
Why is this work being done?
What thu?!?
Due to MANY
“wicked“
influences.
Agenda
• Scenario
• What is Wicked about classification?
• Why commoditized software?
• Demo
Scenario
patient
injury
Clinical notes
“multi-modal”
data entry
EMR
Classification
Human Readable
Machine Readable
Possible Patterns:
• Referral Process
• Discharge Summary
• Rx Distribution
• CPOE
• …
2 (+ a bit) ways of data entry
Source: “Smart Forms” in an Electronic Medical Record: Documentation-based Clinical
Decision Support to Improve Disease Management; SCHNIPPER J L, et al; J Am Med Inform
Assoc. 2008;15:513–523. DOI 10.1197/jamia.M2501.
Source: Plug-and-Play XML: A Health Care Perspective; SCHWEIGER R, et al; J Am Med Inform
Assoc. 2002;9:37–48
Source: An Applied Evaluation of SNOMED CT as a Clinical Vocabulary for the
Computerized Diagnosis and Problem List; Wasserman H, et al; AMIA Symposium
Proceedings 2003; pp 207.
Dropdown Lists Free Text
Hybrid (the bit)
“Wicked” Concept
• Riddel and Webber (1973)
• Westbrooke et al (2007)
• Summarized paraphrase:
– A fuzzy solution space in which the problem locus is
variably re-referential
• As one thing is solved another introduces itself and, potentially, re-
influences the original point from this the current solution was derived.
Religious
Disney
Network
Geography
Vegetable
Sport
Pathology
Laboratory
GP Clinic
Service
Instance
Directory
Authentication
Service
HPI service IHI service
Internet2, 3
4
5
8
6
Pathology
report
Receipt
response
10
1
7, 9
Health messaging Clinical Communications Clinical Terminologies
Project premise
Infrastructure
Without the “guru-needed” syndrome
Embed Terminology
ICD <-> SNOMED
Clinical Data container
CDA, CCR, CCD, Archetype, …?
Clinical Noting
With terminology
Why Commoditized software?
• Because it is part of the infrastructure
• Has the container abilities required
• Had the technology extensibility needed
Wicked clinical system
Concept Demonstrator (Demo time)
MS Word 2007+
document/templates
CDA/Archetype/
other XML
document
Services:
• Terminology (HLi)
• ID services
• sCCOW
• PKI
• Medications
• Decision Support
• Integration…
What Clinician
sees
HealthLanguage
Language Engine (LE)
Web-services linkage
Commoditized Clinical noting:
Embedded Machine readable structures for data mining
combined with Human readable formats for knowledge
gathering using Commoditized software
Guru’s are important
Recognized issuesX12N
ISO
OMG
CDISC
AHIC
ASTM
HL7 v2IHE
W3C
OASIS
DICOM
SNOMED-RTLOINC
Continua
NCPDPHIMS CCHIT
IEEE-SA
ICPC
ICD-9
ICD-10 SNOMED-CT
SNOP
HIPAA
WEDI-SNIP
ISO 29500
HL7 v3
HL7 CDA
openEHR
CCD
CCR CEN 13606
CEN
HTML
SOAP
SOAP
WSRP
PKI
WS-i*
REST
BPEL
XPDL
XAML
IHE-XDS.b
IHE-XDS.a
SMTP
FTP
HTTP
S/MIME
MTOM
SAML
Doctors don’t work like this
There are many standards that can be incorporated
We may be trying to stuff too much in
Not stress tested within an evidence based evaluation framework
There are a wicked number of ways to solve the clinical noting problem
“If an idea seems new to an individual, it is an innovation”
- Diffusion of Innovations 5th Ed, Rogers E., 2003
DynaBS
gloStream
Making Terminology Work

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Making Terminology Work

  • 1. Making Terminology work Driving in situ use of wicked classification schemes with commoditised software Werner van Huffel Regional Strategist, Microsoft APAC wvhuffel@microsoft.com Associations: The Author is an employee of Microsoft and undertaking health Informatics field studies. Masters degree in Health Information Management (Health Informatics) [HIM-HI], University of Sydney, Australia Acknowledgements as: Raphael Mastier (Microsoft, France) Marc Horowitz (HealthLanguage, Global) Andrew Kirby (Microsoft, UK) Neil Jordan (Microsoft, Global) Brian Levy (HealthLanguage, USA)
  • 2. “…Houston, we've had a problem...” - Apollo 13, Lovell J. A. , 1970 Clinicians wanted this Got this Why is this work being done? What thu?!? Due to MANY “wicked“ influences.
  • 3. Agenda • Scenario • What is Wicked about classification? • Why commoditized software? • Demo
  • 4. Scenario patient injury Clinical notes “multi-modal” data entry EMR Classification Human Readable Machine Readable Possible Patterns: • Referral Process • Discharge Summary • Rx Distribution • CPOE • …
  • 5. 2 (+ a bit) ways of data entry Source: “Smart Forms” in an Electronic Medical Record: Documentation-based Clinical Decision Support to Improve Disease Management; SCHNIPPER J L, et al; J Am Med Inform Assoc. 2008;15:513–523. DOI 10.1197/jamia.M2501. Source: Plug-and-Play XML: A Health Care Perspective; SCHWEIGER R, et al; J Am Med Inform Assoc. 2002;9:37–48 Source: An Applied Evaluation of SNOMED CT as a Clinical Vocabulary for the Computerized Diagnosis and Problem List; Wasserman H, et al; AMIA Symposium Proceedings 2003; pp 207. Dropdown Lists Free Text Hybrid (the bit)
  • 6. “Wicked” Concept • Riddel and Webber (1973) • Westbrooke et al (2007) • Summarized paraphrase: – A fuzzy solution space in which the problem locus is variably re-referential • As one thing is solved another introduces itself and, potentially, re- influences the original point from this the current solution was derived. Religious Disney Network Geography Vegetable Sport Pathology Laboratory GP Clinic Service Instance Directory Authentication Service HPI service IHI service Internet2, 3 4 5 8 6 Pathology report Receipt response 10 1 7, 9 Health messaging Clinical Communications Clinical Terminologies
  • 7. Project premise Infrastructure Without the “guru-needed” syndrome Embed Terminology ICD <-> SNOMED Clinical Data container CDA, CCR, CCD, Archetype, …? Clinical Noting With terminology Why Commoditized software? • Because it is part of the infrastructure • Has the container abilities required • Had the technology extensibility needed Wicked clinical system
  • 8. Concept Demonstrator (Demo time) MS Word 2007+ document/templates CDA/Archetype/ other XML document Services: • Terminology (HLi) • ID services • sCCOW • PKI • Medications • Decision Support • Integration… What Clinician sees HealthLanguage Language Engine (LE) Web-services linkage Commoditized Clinical noting: Embedded Machine readable structures for data mining combined with Human readable formats for knowledge gathering using Commoditized software
  • 9. Guru’s are important Recognized issuesX12N ISO OMG CDISC AHIC ASTM HL7 v2IHE W3C OASIS DICOM SNOMED-RTLOINC Continua NCPDPHIMS CCHIT IEEE-SA ICPC ICD-9 ICD-10 SNOMED-CT SNOP HIPAA WEDI-SNIP ISO 29500 HL7 v3 HL7 CDA openEHR CCD CCR CEN 13606 CEN HTML SOAP SOAP WSRP PKI WS-i* REST BPEL XPDL XAML IHE-XDS.b IHE-XDS.a SMTP FTP HTTP S/MIME MTOM SAML Doctors don’t work like this There are many standards that can be incorporated We may be trying to stuff too much in Not stress tested within an evidence based evaluation framework There are a wicked number of ways to solve the clinical noting problem
  • 10. “If an idea seems new to an individual, it is an innovation” - Diffusion of Innovations 5th Ed, Rogers E., 2003 DynaBS gloStream

Editor's Notes

  1. James "Jim" Arthur Lovell, Jr., (born March 25, 1928) One of the reasons I am doing this work is to better understand how we can give clinicians more of what they want by understanding what the practical constraints are to what they want. One of the problems is how to implement effective use of terminology within a HIT pattern of data gathering
  2. Patient has morbidity Sees GP/presents to ER Clinician (GP/Other) records notes in any preferred manner These notes are stored in the clinical EMR system A classification or terminology is applied as per the context/standards/ policy of the location But need to share the information To share need to use a terminology for contextual interop of data … e.g. SNOMED Apply to patient data (say CDA) By using OOXML we are able to embed the CDA in a human readable format and distribute
  3. Drop-down – pre-populated, generally static, easier to control from IUT perspective Free Text – better for clinician, very bad for interop and IT control Hybrid – usually cumbersome and “not the best” of both worlds above
  4. Riddel and Webber (1973) “…one of the most intractable problems is that of defining problems and of finding where in the complex causal networks the trouble really lies…” Westbrooke et al (2007) Wicked problems are dynamic with multiple sets of complex, interacting issues that evolve in an emergent social context. SNOMED-CT 300,000 Current Concept; 750,000 Descriptions;(English & Spanish); 900,000 Relationships Source www.IHTSDO.org ICD-10(AM) 34000 entries (A00.0 [“Cholera due to Vibrio cholerae 01, biovar cholerae”] to Z99.9 [“Dependence on unspecified enabling machine and device”]) Source: NCCH Usyd ICD-10-AM book
  5. No-one seems to look at the value within the infrastructure to provide a common platform for clinician noting purposes. If we look at the complex scenario of clinical noting with terminology and at infrastructure then we can suggest that clinical noting follows the commoditized processes of word processing software. If this is taken as a possibility then can we use commoditized word processing software to accept clinical noting while allowing us to embed contexutalisation data (in the form of terminology) and a clinical contextualisation structure on the data (in the form of CDA, etc) We should aim to remove the “Guru” syndrome requirements in HIT.
  6. “sCCOW” is “simplified” CCOW – currently CCOW may be too complex and not versatile enough for many controlled environments. It may be possible to simplify the process using process engines and contextualisaiton based upon patient-clinician time-in-motion studies.