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SNOMED-CT Implementation issues and opportunities Heather Grain Presented at HIMAA Symposium 2008.

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Presentation on theme: "SNOMED-CT Implementation issues and opportunities Heather Grain Presented at HIMAA Symposium 2008."— Presentation transcript:

1 SNOMED-CT Implementation issues and opportunities Heather Grain heather@lginformatics.com Presented at HIMAA Symposium 2008

2 Implementation means Coding in the clinical world Options ▫Give the clinician a list (sometimes a really big list) to choose from….. ▫Develop other mechanisms Photo Coppyright Steffen Foerster

3 Trail of natural language AND ICD-10-AM coding automation in Emergency

4 Issues to conquer first

5 Language of the Language We don’t all describe the concepts of terminology the say way........ Work at ISO on an International Glossary being established to clarify meaning. Internet based toolInternational Glossary Available openly in 2009 (Australian Leader of international activity)

6 Mapping is….. Creation of a relationship between the code or term used to represent a health concept in one system and the code or term that would be used to represent the same concept in another coding or terminological system ABC = XYZ AS5021-2005

7 Mapping – does and doesn’t TermSNOMED-CTICD-10-AM Problem Urinary Tract Infection 25374005 – Urinary Tract Infection (disorder) O03.3 with obstetric spontaneous abortion O86.2 Urinary tract infection following delivery N39.0 – Urinary Tract Infection, site not specified Additional logic is required to determine which code is appropriate. There are also rules in the coding standards that indicate: “do not code the following: N39.0 Urinary tract infection, site not specified, when only microbiology results show organism(s) have been cultured ”.

8 Mapping – does and doesn’t TermSNOMED-CTICD-10-AM Patient had heart attack during laparoscopic appendicectomy, surgery not completed. 51316009- Laparoscopic appendectomy 385660001 - Not done 57054005 - AMI 74477009 – exploratory laparotomy 30373-00 – Exploratory Laparotomy

9 Reference Sets for implementation Select appropriate terms for use in specific situations Lists can be short or long ▫Can include hierarchy (children) information ▫Can ensure correct part of the hierarchy is being used ▫Restricts and guides entry

10 What we have Access capacity (ability to access codes/terms – terminology servers or engines) Ability to represent concepts (SNOMED-CT) Clinically acceptable mechanism for data capture Recognition of context in the use of terminologies What we don’t have

11 Austin investigation - Triage text What is in text 54,543 cases from 12 months at Austin Emergency 9525 different textual descriptions (82% common) Context informs the intended meaning.... ▫PALP + CP- palpitations and chest pain

12 Content of the text 21% have additional qualifiers that indicate additional information about the concept ▫? # 3RD DIGT L 15% of entries had additional specific laterality ▫e.g. R Groin pain 12% of entries had more than one concept ▫e.g. foot inj.fever 5% have other information such as causes of injuries, finding sites. ▫e.g. fall head inj 90% use short forms or have spelling challenges. ▫e.g. bowel obstr ▫> 32 different spellings of.......

13 Objectives of test Identify capacity to process text to SNOMED Identify ability to convert to ICD-10 for reporting purposes (avoiding clinical input entirely) - achieved

14 Testing Results Coded manually in SNOMED-CT and confirmed by clinical staff in emergency Batch processed identifying variations from expected SNOMED-CT returned. Established quality measure 5 th test achieved 95% = 100% confidence 2% = 90% confidence 3% = 80% confidence – require user confirmation (17 cases) 0% e.g.: ? gib Queries to SNOMED – sent to NEHTA e.g.: ? DRINK SPIKE

15 Sample of result

16 Next steps Trial in clinical environment Trial to inform clinical pathways and risk assessment Returning SNOMED-CT into different fields (concepts)

17 Issues Testing environments and support Inhibitors ▫Belief ▫Fear ▫System capacity (interface) – HL7 developing standards for V3 and V2 using Common Terminology Services, Clinical Document Architectures and OpenEHR Archetypes.


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