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SNOMED Training Workshop

Join Denise Downs, Ian Spiers, and Joe O'Dell for a comprehensive training workshop on SNOMED CT in primary care. Learn about data quality, existing searches, and supplier updates. No prior knowledge required.

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SNOMED Training Workshop

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  1. SNOMED Training Workshop SNOMED CT in primary care Denise Downs, Ian Spiers, Joe O’Dell

  2. Welcome to SNOMED Training Workshop Agenda 9.30 Registration 10.00 Welcome and Introductions 10.30 Training others on SNOMED CT 11.30 Tea/Coffee 11.50 Training Presentations 12.30 Data Quality 13.00 Lunch 13.45 Data Quality Continued 14.15 Existing Searches (Tea/Coffee at 3.00) 15.15 Supplier updates 16.00 End of workshop

  3. Housekeeping • Toilets • Fire • Refreshments • Introductions to NHSD team

  4. Don’t need to know anything about SNOMED CT Nothing will change I need to understand SNOMED CT Things will greatly improve

  5. Year 2000 again ??? Plan for the worst Hope for the best!

  6. Objectives Give you time to get more confident and ask questions Understand SNOMED and what is the key information for training practice staff Understand Data Quality and differences between Read and SNOMED Understand SNOMED Searches Update on suppliers

  7. Pre-workshop Requirements Webinars/Recorded Presentations • ‘Introduction to SNOMED CT for general practice’ • ‘Exploring Content in SNOMED CT’ Laptop or Smart device for Internet BrowsersExample templates and reports

  8. Ice Breaker

  9. Ice Breaker • In pairs, find five things you have in common with the other person (5 mins) • This does not include anatomy  • In your pairs, what is one thing you want to come away from today with ?

  10. Understanding SNOMED CT and training practice staff

  11. Quick Browser Demo • More advanced features (10 mins) • Inactivated concepts • Drag and drop • Description ids • Refsets Recommend you use the browser in Chrome or Firefox https://termbrowser.nhs.uk/

  12. Understanding SNOMED CT and training practice staff In pairs: • Workbook Sections 1-3 (30 mins) In groups of 4: • Design Training for a practice (20 mins) • Create bullet points of what are the key things to cover • Devise a10 min presentation Tea/Coffee Break 3 of the presentations will be chosen to present

  13. Data Quality/Term Text changes

  14. SNOMED CT is … • More precise and oriented to electronic patient records and patient care • The following slides highlight aspects of the mapped data but also highlight changes to the term text that users need to be aware of

  15. Inactive codes SNOMED CT can deal with inaccuracies in a way Read couldn’t: • Concepts can be made inactive • Descriptions can be made inactive • Inactive concepts/descriptions should not be visible for data entry • Inactive concepts can be used in searches

  16. In the browser Some Read codes are mapped to inactive SNOMED CT Descriptions Need to choose

  17. Inactive concepts

  18. Look-up for Read to SNOMED Browsers

  19. Some current maps are to inactive codes

  20. Inactive code - ambiguous Some Read codes are mapped to inactive SNOMED CT Bill/fee sent inactive in SNOMED CT It is ambiguous, do have Bill sent and Fee sent Need to choose

  21. Ambiguous codes Serum bilirubin borderline is inactive in SNOMED CT It is ambiguous, do have Borderline low and Borderline high Need to choose

  22. Not interoperable Terms with Clinic A / Clinic B have codes mapped to inactive SNOMED CT concepts These will map but to inactive codes; they are not interoperable, never went through GP2GP Different Practices will have different clinics Use specific clinic type administrative terms in future e.g. seen in asthma clinic, referral to asthma clinic

  23. NOS, NEC, unclassified … Classification Terms

  24. Maps to higher level terms

  25. Maps to different hierarchies Template Design This will mean you have to write cherry picked searches in SNOMED CT, ideally all should be Under of care terms so can interoperate (we’ll come back to this)

  26. Data Quality • Section 4 Workbook (30 mins) • In groups look at Data Quality Guidance • Will this effect your sample templates/reports? Review those you have brought with you. • What can you do ahead of time? • Lunch (13.00-13.45) • Q&A

  27. Data Quality Data Quality : Questions and Answers • Any questions/observations?

  28. Collaborative space - Delen • Area specifically for trainers to share information • If you don’t have access email: snomedprimarycare@nhs.net

  29. Searches

  30. Searches • Designing Searches Presentation • Convert one of your searches (Use look up tables and Browser) • Questions and Answers (1 hour) (tea and coffee at 15:00 )

  31. Concepts and descriptions Synonyms are truly synonymous Searches are done on the concept id FSN is often the term provided in search definitions • Fully specified name • Preferred term • Acceptable synonyms • Preferred term is usually the description seen in the system

  32. Language of SNOMED CT specifications Operators in SNOMED CT - Expression Constraint Language (ECL) conceptid just this concept <conceptid the descendants of this concept <<conceptid this concept and all its descendants ^refsetId members of refset Then any of the above preceded by MINUS exclude concepts (s) OR include concepts(s) or concept(s) AND include concept(s) AND concepts(s)

  33. Expressing a search We can express a search in two ways: Use ECL and the hierarchy structure : Concept and all of its descendants <<233838001 | Acute posterior myocardial infarction (disorder) | Cherry pick the codes (cluster list): List each concept seperately 233838001 | Acute posterior myocardial infarction (disorder) | 70998009 | Acute myocardial infarction of posterobasal wall (disorder) | 15713201000119105 | Acute ST segment elevation myocardial infarction of posterobasal wall (disorder) | Although these produce the same result, that may only be true for a particular release. We’ll see that using the hierarchy is a better way to write the searches when we can.

  34. Walkthrough – Example 1 • Hip replacement

  35. Search for hip replacement Total Revision Partial

  36. Where in the hierarchy do we search:

  37. Walkthrough – Example 2 • Contraception – comparison with Read • If we searched on children of Contraception 61…

  38. Would get patients on contraception …

  39. Would get patients Not on contraception

  40. Would get patients Not actually person of record term Unknown whether on contraception or not

  41. Have a go yourselves • Either do some you brought with you (either looking for data items for a template or a search) OR • Try the following: • All patients who have had a stroke • All obese patients

  42. Moving to SNOMED CT – things to be aware of • Searches will continue to work once moved to SNOMED CT UNTIL someone starts recording data that does not have a Read code equiv. • Two ways to approach migrating a search from Read v2/CTV3 to SNOMED CT • Take the previous search definition and write a new SNOMED CT search from scratch • This may include SNOMED CT concepts that do not have a Read v2/CTV3 equivalent • Take the previous search codes and map these to SNOMED CT • This will need extending and reviewing in future as SNOMED CT concepts without a Read v2/CTV3 equivalent are used

  43. Approach 2: Not fully automatic A previous search cannot not be converted automatically as contains content not in Read, this needs a human to check Example: C10..% Diabetes mellitus TO << 73211009 | Diabetes mellitus (disorder) | Maybe ok Example: H33..% Asthma TO << 195967001 | Asthma (disorder) | For example include Exercise induced Asthma , which may not wish to include

  44. Steps for Approach 2 • Expand current query to all Read codes • Expand list to all terms for all codes • Map each to SNOMED CT • Reduce to the list of unique SNOMED CT concepts • Are there any other Read codes that map to these concepts ? • How do we then extend this to be a SNOMED CT search?

  45. Look-up for Read to SNOMED Browsers

  46. Approach 2: example Take the previous search codes and map these to SNOMED CT Following example illustrates the approach and why some results may be different once data entry moves to SNOMED CT How can this be transformed into SNOMED CT?

  47. Approach 2: term level and map Expanded to 73 Read codes Which map to 67 SNOMED CT concepts Notice two different Read codes go to the same SNOMED CT concept

  48. Existing searches: term level Concept Id Description Id

  49. Considering historical data • In simple terms we have performed the following: • Are there any other Read codes that map to our list of SNOMED CT concepts? • We can use the Delen look-up to find out Original search

  50. Back to the example of Diabetes mellitus When checking the forward mapping tables for the 67 concepts in the converted search we find there are other Read codes not in the original specification • Original Read v2 specification: 73 codes • Converted SNOMED CT specification: 67 concepts • Review codes that also map to these: 138 codes

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