1. Overview, Benefits and how to approach Implementing - Robyn Richards (NEHTA)

2.  Australian extension of the international SNOMED CT  Allows us to add to and ensure the content is applicable for Australia  Contains all international content plus any Au additions or changes  Australian Medicines Terminology

3.  The Basics

4.  Over 300,000 concepts that are organised into 19 top-level hierarchies Body structure Clinical finding Environment or geographic location Event Linkage concept Observable entity Organism Pharmaceutical/biologic product Physical force Physical object Procedure Qualifier value Record artefact Situation with explicit context Social context Special concept Specimen Staging and scales Substance

5. SCTID: 22298006  A concept and its descriptions Myocardial infarction Synonym MI - Myocardial infarction SCTID: 1784872019 Synonym Infarction of heart SCTID: 37441018 Synonym Cardiac infarction SCTID: 37442013 Synonym Heart attack SCTID: 37443015 Fully Specified Name Myocardial infarction (disorder) SCTID: 751689013 Preferred term Myocardial infarction SCTID: 37436014

6.  Attributes Over 60 types of attributes These ‘link’ concepts together to provide definitions Most important Attribute is the IS-A The use of IS-A attribute forms the hierarchies parents-children; types-subtypes; subsumption- inheritance Other attributes are used to form lateral links between or across hierarchies Body Structure has an attribute of Laterality Procedure has an attribute of Access

7.  Concepts within the top-level hierarchies exist in a poly-hierarchical structure Pneumonia Pneumonitis Lung consolidation Inflammatory disorder of lower respiratory tract Disorder of lung Disorder of lower Respiratory system Is A

8. Role grouping  Attributes Viral Bronchitis Bronchitis Is A Virus (organism) Infectious process (morphologic abnormality) Bronchial structure (body structure) Inflammation (morphologic abnormality) Causative agent Pathological process Associated morphology Finding site

9.  Pre and post coordination are the names given to how you approach representing clinical expressions in a record  Pre coordination encapsulates all the information to convey meaning in a single code  Post coordination encapsulates meaning in a series of attribute value pairs associated with a concept. Pre and Post-coordination

10.  Pre coordinated example ◦ One concept conveys all the required meaning ◦ E.g.31978002 ‘Fracture of tibia’  Post coordinated expression ◦ E.g.31978002: 272741003 = 7771000 ‘Fracture of tibia: laterality = left’ Pre and Post-coordination

11.  Group or subset of concepts from SNOMED CT used for a specific purpose  Implementation tools used to provide a smaller set of concepts for implementation in a specific section of a record  There are other uses for reference sets such as annotation and navigation references sets, but these are the most common at the moment

15.  At Data Entry  Content coverage  Specificity  One concept with multiple descriptions

16. SNOMED CT Five concepts ICD-10-AM One code | 29774004 Vascular myelopathy | | 432249006 Infarction of spinal cord | | 39134007 Haematomyelia | | 65605001 Oedema of spinal cord | | 83982007 subacute necrotic myelopathy | G95.1 Vascular myelopathies Includes: - Acute infarction of spinal cord - Haematomyelia - Oedema of spinal cord - Subacute necrotic myelopathy

17.  For communication  Standard terminology across the system  Unambiguous concept identification

18.  For Retrieval  Can utilise all SNOMED CT features to assist with retrieval for planning, reporting, research  Standard terminology ensures ‘apples are compared with apples’ no matter where data sourced from  This is where the power of SNOMED CT can really be realised

19.  Example ICD-10-AM Diseases of the Respiratory System | Influenza and Pneumonia | J12.9 – Viral Pneumonia, NEC | J12.9 – Viral Pneumonia, unspecified

20. SNOMED CT-AUICD-10-AM  Disorder of respiratory system  Pneumonia  Viral pneumonia  Infectious diseases  Inflammatory disorders  Infection by sites (lung etc)  Viral infections  Respiratory conditions that have had related procedures  SNOMED CT uses its hierarchies and attributes to allow retrieval queries to be written  Diseases of respiratory system  Influenza’s and Pneumonia  Viral Pneumonia  ICD was developed to quantify and fund inpatient events which it will continue to do

21.  Longer term  Used with decision support  Drive evidence based medicine  Drive clinical process improvement  Facilitate knowledge management

22.  Many of these benefits are for the future  In order to reap the benefits we need to get SNOMED CT into systems NOW

23.  It is not a standalone solution  It needs to be deployed IN a clinical software application  SNOMED CT is one part of an EHR product  The other half is the clinical application itself and its information model

24.  Information models define the data entry boxes (names)  Terminology defines the values which can be selected and recorded within those boxes (values) Diagnosis: Viral Pneumonia Information model Terminology

25.  Natively – get SNOMED CT into the backend of clinical systems  Need to find a balance between using reference sets to isolate content or using searching functionality  Recommend reduce dependence on reference sets and mappings by improving Searching Functionality

26.  Only provide search results for current concepts  Don’t return Fully Specified Names  Use the Australian Language Reference Set to extract relevant descriptions (US spellings out)  Use ‘contains any word’ parameters rather than ‘starts with’  Ensure frequently selected concepts return to the top of the search results list  Do Not provide pick lists if there are more than ~8 to choose from

27.  Provide options to browse the hierarchy around a selected concept  Utilise indexing tables  The better the searching functionality, the larger your reference set can be without affecting usability  Realise that improvements here may take some time to implement – but this is definitely the way to go!!!

28.  Options are:  Natively (with basic searching criteria)  Use Mappings..(more on this later)

29.  Steps to implement into a specific data element

30.  Understand your information model data element ◦ What is the definition of the data element? ◦ What use cases does it need to cover? ◦ Where in the record is it used? ◦ What other data elements sit next to it? Adverse reaction substance: Substance that is responsible for a reaction in a patient Adverse reaction manifestation: Reaction experienced by patient Adverse reaction type: The type of reaction determined by the clinician

31.  Does this include medications?  Does this include foods?  Does this include organisms?  Does this include chemicals? Adverse reaction substance: Substance that is responsible for a reaction in a patient

32.  Understand the context of the information that will be captured in the data element ◦ Often relates to the SNOMED CT top-level hierarchies: Clinical findingSpecimenObservable entity ProcedureOrganismSubstance EventSocial ContextPharmaceutical or Australian Medicines Terminology Product Body StructureSituation with explicit context

33. AMT Product/ Pharmaceutical Biologic hierarchy ‘Pepzan’ ‘Brolene eye drops’ Substance hierarchy ‘penicillin’ ‘latex’ Clinical finding hierarchy ‘allergy to penicillin’ Adverse reaction substance: Substance that is responsible for a reaction in a patient

34.  Identify terminology content  Get to know the SNOMED CT hierarchies and where different kinds of concepts can be found  Search based on your use cases  Are there any existing codesets you can use as a source list  Identify content that is NOT valid as well as what is  Document the reasoning used for your decisions  Identify if any existing reference sets can be used or cut down

35.  Build your reference set  Methods will vary based on tools  NEHTA CTI methods include  Source data method  Attribute method  Concept enumeration method  Simple inclusion method More information can be found in the ‘Development approach for reference sets’ document in the SNOMED CT-AU Release

36.  Unpack reference sets – technical processes  Use Australian language reference set  Ensure searching functionality works  Test it

37. Two distinct types 1.From local terms and codesets TO SNOMED CT 2.FROM SNOMED CT to other instruments (ICD for eg)  Different purposes  Different methods  Different outcomes

38. Type 1 Mapping codesets to SNOMED CT are -Prone to information loss -Expensive to build and -Require ongoing maintenance and review -Recommend the use of a mapping as a migration tool

39. Type 1 Should be regarded as migration  Take the old termset content  Map it once, properly, to SNOMED CT content (RefSet?)  And then ‘switch’ to the SNOMED CT for continued use Similar approach to the upgrade and switch over from:  Analogue to digital television signal service  Leaded to unleaded to E10 petrol For instance: Emergency Department Reference Set Example: 1234 | Chronic bronchitis migrates to 63480004 | Chronic bronchitis Old termset content mapped to SNOMED CT content

40. Perceived as semi-automation of traditional ICD coding More accurately regarded as transformation Take SNOMED CT content Find suitable ICD candidate Include ICD rules – NOTE INCLUDES, EXCLUDES, NOS, NEC Assign ICD-10 code for use in reporting Type 2

41. Try under a different name or wording Contact the service desk (terminologies@nehta.gov.au)terminologies@nehta.gov.au Submit a request submission to NEHTA (terminologies@nehta.gov.au)terminologies@nehta.gov.au

42. Robyn.Richards@nehta.gov.au Thanks and any Questions?  Acknowledge challenges and the journey to implementation that we all face