Terminological Systems in Medicine

1. Terminological Systems in Medicine Ronald Cornet, PhD Dept. of Medical Informatics Academic Medical Center – University of Amsterdam r.cornet@amc.uva.nl

2. Overview Part I – The role of Coding, Classification and Terminology in Registration of Patient Data Part II – SNOMED CT

3. Registration of Patient Data –The role of Coding, Classification and Terminology

4. Outline • Context • Coding & Classification • Coding Systems Overview • Coding in Practice • Coding Systems, the next generation • Types of systems & Requirements

5. Starting point: E-record • Cost of care • Quality of care

6. Motivation: cost of care • Digitizing medical records in the U.S. could save the health care industry as much as$81 billion a year and help medical practitioners avoid mistakes • The study found that electronic medical records systems save money by reducing redundant care, speeding patient treatment and improving safety. “Can Electronic Medical Record Systems Transform Healthcare? An Assessment of Potential Health Benefits, Savings, and Costs” - Sep. 14, 2005 Hillestad R, Bigelow J, Bower A, Girosi F, Meili R, Scoville R, and Taylor R (Rand Corp.) Health Affairs, Vol. 24, No. 5.

7. Motivation for Clinical Terminology • Costs • Terminology use benefits entire health system • Save as much as 5% of total healthcare costs* • up to $100 Billion per year in US * Source - Walker J et al., Market Watch 2005:19th January;10-18

8. Direct Indirect Use of Patient Data • Documentation in the EPR/EHR • Decision support • Clinical audit • Reporting • Summaries • Administrative & management information • Epidemiology • Billing • Resource management [National Health Services – United Kingdom]

9. Documentation of Patient Data • Free text • Expressive, Maximal freedom, Precise • Ambiguous • Hardly computer-processable • Coded • Limited expressiveness • Potentially less ambiguous • Computer-processable

10. Outline • Context • Coding & Classification • Coding Systems Overview • Coding in Practice • Coding Systems, the next generation • Types of systems & Requirements

11. Why using codes • Data reduction • Standardization • Avoiding problems with natural language • Acute heart attack • Acute myocardial infarct • Acute myocardial infarction • Myocardial infarction acuta • Acute coronary thrombosis Solution: 410 Acute myocardial infarction

12. Coding • A code is a sequence of symbols which refers to a concept and which can be used for identification and selection

13. Coding • Example: coding gender Male = m Female = f

14. Principles for defining Codes • Explicit eligibility criteria (definitions) • E.g. genotypic, phenotypic gender • Disjoint categories • male, female • Exhaustive categories • male, female, other, unknown • Reasonable… • Klinefelter's syndrome (XXY) ?

15. Types of Codes • Significant • Mnemonic • Juxtaposition • Hierarchical • Non-significant / context free • Random • Sequential

16. Mnemonic Codes • Formed from one or more of the characters of its related class • M = Male, F = Female • KL204 = KLM flight 204

17. Juxtaposition Codes • Composite codes consisting of segments • Room J-1B-115 building floor location

18. Hierarchical Codes Example from ICD-9-cm: • 003 Other Salmonella Infections • 003.0 Salmonella Gastroenteritis • 003.1 Salmonella Septicemia • 003.2 Localized Salmonella Infections • 003.20 Localized Salmonella Infection, unspecified • 003.21 Salmonella Meningitis • 003.22 Salmonella Pneumonia • Aggregation, retrieval on different levels

19. Reasons for using significant codes • Codes can be remembered • Meaning can be derived from code • (Juxtaposition and hierarchical) codes can be used for aggregation

20. KLM Kenya Airways Malaysia Airlines Northwest Airlines Problems with significant codes • Mnemonics 07.45 KL 1124 Copenhagen Arrived 07.4107.45 KQ 1124 Copenhagen Arrived 07.4107.45 MH 9264 Copenhagen Arrived 07.4107.45 NW 8400 Copenhagen Arrived 07.41 1 flight, 4 codes!

21. Problems with significant codes Hierarchical codes: • 003 Other Salmonella Infections • 003.0 Salmonella Gastroenteritis • 003.1 Salmonella Septicemia • 003.2 Localized Salmonella Infections • 003.20 Localized Salmonella Infection, unspecified • 003.21 Salmonella Meningitis • 003.22 Salmonella Pneumonia • No other aggregation than “Salmonella infections”, e.g. “Meningeal infections”

22. Non-significant codes • Random: pick any (unique) number • Sequential: number consecutively, e.g., start by 1 and increase • Such meaningless codes should NOT be presented to users

23. Outline • Context • Coding & Classification • Coding Systems Overview • Coding in Practice • Coding Systems, the next generation • Types of systems & Requirements

24. Classification Classifying: • Designing a classification • Assigning a class to an object

25. Classes of Objects • How many classes do you see below? • Eagle • Elephant • Shark • Telephone • Television • Videocamera

26. Classes of Objects • How many classes do you see below?

27. Classification Principles • Aristoteles (384BC - 322BC): “definitio per genus proximum et differentia specifica“(definition by the nearest higher class and differentiating properties). • Classes fulfill criteria of superclasses • Classes are more specific than superclasses

28. Classification example: Biology African Elephant Taxonomy • Kingdom: Animal • Phylum: Chordata / Craniata / Vertebrata • Class: Mammalia / Theria / Eutheria / Afrotheria • Order: Proboscidea • Family: Elephantidae * Genus: Loxodonta (African elephants) + Species: Loxodonta africana Full lineage is over 20 levels! http://www.ncbi.nlm.nih.gov/Taxonomy/taxonomyhome.html/

29. Example: ICD-10 • Certain Infectious and parasitic diseases • Viral infections of central nervous system • A87 Viral meningitis • A87.2 Lymphocytic choriomeningitis Systems such as ICD-10 typically contain 10.000s to 100.000s of terms (codes)

30. Classification “Chapters” ICD-10 (1) • Certain Infectious and parasitic diseases • Neoplasms • Diseases of the blood and blood forming organs and certain disorders involving the immune mechanism • Endocrine, nutritional and metabolic diseases • Mental and behavioural disorders • Diseases of the nervous system • Diseases of the eye and adnexa

31. Classification “Chapters” ICD-10 (2) • Diseases of the ear and mastoid process • Diseases of the circulatory system • Diseases of the respiratory system • Diseases of the digestive system • Diseases of the skin and subcutaneous tissue • Diseases of the musculoskeletal system and connective system • Diseases of the genitourinary system

32. Classification “Chapters” ICD-10 (3) • Pregnancy, childbirth and the puerperium • Certain conditions originating in the perinatal period • Congenital malformations, deformations and chromosomal abnormalities • Symptoms, signs and abnormal clinical and laboratory findings, n.e.c. • Injury, poisoning and certain other consequences of external causes • External causes of mortality • Factors influencing health status and contact with health services

33. Single ordering (monohierarchy) • Pros • Categories are mutually exclusive (disjoint) •  No double counts • Straightforward, understandable • Cons • Only 1 supported categorization • Disjointness often “artificial”

34. Multiple Ordering (polyhierarchy) • Pros • Multiple aspects (“axes”) for ordering, e.g.:Anatomic location, Etiology, Morphology • Multiple ‘paths’ to items • Cons • Double counts (e.g. “Viral Meningitis” is both “Infectious disease” and “Meningeal disease”) • More complex

35. Single or Multiple Classification? Coding • Documentation in the EPR/EHR • Decision support • Clinical audit • Reporting • Summaries • Administrative & management information • Epidemiology • Billing • Resource management Classification [National Health Services – United Kingdom]

36. Coding: which information? Shortly after dinner on the day before admission to the hospital, this 48-year-old obese woman developed a cramping, epigastric pain that radiated to the back, followed by nausea and vomiting. The pain was not relieved by position or antacids. The pain persisted, and 24 hours after onset, the patient sought medical consultation. The patient was admitted to the hospital with a diagnosis of acute pancreatitis. Radiological findings included widening of the duodenal “C” loop and blurring of the left psoas muscle margin. Serum amylase was 1120 units per liter. The day after admission, the patient seemed to improve. However, that evening she became disoriented, restless, and hypotensive. Despite intravenous fluids and norepinephrine, the patient remained hypotensive and died 8 hours later. Lu TH, Shih TP, Lee MC, Chou MC, Lin CK. Diversity in death certification: a case vignette approach. J Clin Epidemiol. 2001 Nov;54(11):1086-93.

37. Classification: cause of death? Shortly after dinner on the day before admission to the hospital, this 48-year-old obese woman developed a cramping, epigastric pain that radiated to the back, followed by nausea and vomiting. The pain was not relieved by position or antacids. The pain persisted, and 24 hours after onset, the patient sought medical consultation. The patient was admitted to the hospital with a diagnosis of acute pancreatitis. Radiological findings included widening of the duodenal “C” loop and blurring of the left psoas muscle margin. Serum amylase was 1120 units per liter. The day after admission, the patient seemed to improve. However, that evening she became disoriented, restless, and hypotensive. Despite intravenous fluids and norepinephrine, the patient remained hypotensive and died 8 hours later. Lu TH, Shih TP, Lee MC, Chou MC, Lin CK. Diversity in death certification: a case vignette approach. J Clin Epidemiol. 2001 Nov;54(11):1086-93.

38. Outline • Context • Coding & Classification • Coding Systems Overview • Coding in Practice • Coding Systems, the next generation • Types of systems & Requirements

39. Overview of Coding Systems • Large number of systems • Unified Medical Language System (UMLS) Metathesaurus 1 includes over 100 systems, totaling more than 1.000.000 medical concepts • Systems are large • Number of concepts has increased from ~ 100 to > 100.000 1 http://www.nlm.nih.gov/pubs/factsheets/umlsmeta.html

40. Overview of Coding Systems • Diseases • ICD • Specialties • Anatomy • Literature • Genomics

41. ICD • London Bills of Mortality(16th century) • 60 disease categories • Collected by parish clerks • International List of Causesof Death (19th century) – ICD • International Classificationof Diseases (20th century) –ICD-10, tenth revision of ICD

42. Overview of Coding Systems • Diseases • SNOMED – Systemized Nomenclature of Medicine • Specialties • Anatomy • Literature • Genomics

43. 1965 SNOP 1974 SNOMED 1998 SNOMED Version 3.5 2000 SNOMED RT (= 3.5 + READ) 2002 SNOMED CT SNOMED CT • Aims at coding of detailed information“first episode of severe, acute E-coli pneumonia with sudden onset” • Formal definitions provide multiple classifications

44. Overview of Coding Systems • Diseases • Specialties • DSM – Mental Health • ICPC – Primary Care • Anatomy • Literature • Genomics

45. Overview of Coding Systems • Diseases • Specialties • Anatomy • Terminologia Anatomica • FMA – Foundational Model of Anatomy • Literature • Genomics

46. Overview of Coding Systems • Diseases • Specialties • Anatomy • Literature • MeSH – Medical Subject Headings • Genomics

47. Overview of Coding Systems • Diseases • Specialties • Anatomy • Literature • Genomics • GO – Gene Ontology

48. Overview of Coding Systems • And many, many more… CDT5 CPT WHOART ICD-9-CM NANDA ICD10 NIC DSM4 MedDRA Loinc Omaha NOC COSTAR UltraSTAR OMIM http://www.nlm.nih.gov/research/umls/sources_by_categories.html

49. Outline • Context • Coding & Classification • Coding Systems Overview • Coding in Practice • Coding Systems, the next generation • Types of systems & Requirements

50. Coding in Practice, scenario 1 • Clinician records items as codes • By entering (recollected) codes • e.g. gender • By using a pick list • By searching for phrases • e.g. “meningo”