1. UK Ontology Network SNOMED CT Presenter: Dr Jeremy Rogers (UKTC) Date: April 12 th 2012 This powerpoint slidedeck has extensive speaker’s notes to explain each slide

2. About SNOMED CT 40 year old medical terminology –322,544 concepts (and growing) Attempting an ‘in situ’ migration to EL+ –And ‘seamless’ deployment into an industry based on enumerated classifications –18-country international effort, $9.3M annually

3. SNOMED CT in UK Many secondary care sites –Some primary care 13,353,775 Summary Care Records 33M Choose & Book referrals Electronic TFR of prescriptions Soon: Radiology & Pathology messaging

4. Issues Change management –Migration from/integration with legacy systems –Changes in SNOMED CT itself –Death by 1,000 mutual dependencies Implementation skills User interfaces (or, data repair) Tools –Time to load & classify –Content refactoring –‘Linkage’ to external resources Business case

5. SNOMED CT 39 months @ a busy UK A&E Department One ‘reason for encounter’ code per completed visit –408,823 coded episodes 39 months (Oct 2008 – Dec 2011) 12,323 distinct codes selected at least once 8,387 not coded (or uncodable?) = 1 in 50 episodes 20-50% miscoding rate

6. Relative code use

7. 7.8% ‘Ontology-driven’ miscoding… (disorder)234693(morphologic abnormality)17024 (finding)123430(qualifier value)4544 (procedure)6583(body structure)3517 (situation)6379(substance)2340 (event)4592(attribute)1293 (regime/therapy)1344(observable entity)1139 (physical object)746 (product)233 (cell)226 (navigational concept)206 (organism)199 (physical force)152 (record artifact)97 (ethnic group)17 (environment)15 (assessment scale)14 (person)10 (specimen)9 (administrative concept)6 (tumor staging)5 (social concept)4 (cell structure)3 (occupation)2 (inactive concept)1 TOTALS377021 31802

8. Miscoding examples 1097 Temperature 246508008|Temperature (attribute)| 17Drug used246488008|Drug used (attribute)| 373 ETOH - Alcohol intake 160573003|Alcohol intake (observable entity)| 136Nasogastric tube 17102003|Nasogastric tube, device (physical object)| 82 Catheter 19923001|Catheter, device (physical object)| 78 Dressing 37898001|Dressing, device (physical object)| 11053570002|Removal of foreign body from eye (procedure)| 83172828005|Removal of foreign body from nose (procedure)| 43172278002|Removal of foreign body from eyelid (procedure)| 29382576008|Retained foreign body in eye (disorder)| 166 74699008|Foreign body in nose (disorder) 725012008|Retained foreign body of eyelid (disorder)|

9. Variable Data Quality 23% of 74 abdominal aortic aneurysms miscoded as a Drug Trade Family (9192101000001100 AAA (product)); AAA make sore throat spray(and not much else) 25% of 939 stabbing victims miscoded as a qualifier value (‘stabbing sensation quality’, as in heart attack) 33% of 3771 patients with some form of high temperature miscoded as either an attribute, or a physical force 38% of 1101 failed consultations (patient left the department, or did not attend an appointment) miscoded as either a laterality (left) or as deoxyribonucleic acid (DNA = Did Not Attend) 44% of 575 patient attending with a fish bone stuck in their throat miscoded as the bone itself (7661006|Fish bone (substance)|) 49% of 5,062 alcohol-related attendances miscoded as either the substance (alcohol, ethyl alcohol) or just feeling elated/intoxicated but not necessarily involving alcohol intake at all

10. Not all bad news: Admissions for sickle cell Clinical impression – ‘They stop coming once they get older; most of the attendances will be in the 15-20 age group’ Clinical lore –Cold weather triggers attacks ‘People with sickle cell disease should try to avoid any potential triggers for a sickle cell crisis as much a possible. For example: try to keep warm in cold weather, try to avoid becoming dehydrated and take precautions if you undergo extreme exercise’ (patient.co.uk) Clinical Data…???

11. WINTER 2008-9 But: We could probably have got this particular result using ICD. Overall, is the ontology (as implemented) helping or hindering primary data capture and secondary data analysis?