Alan Rector & Luigi Iannone with thanks to Robert Stevens
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Transcript of Alan Rector & Luigi Iannone with thanks to Robert Stevens
© University of Manchester Creative Commons Attribution-NonCommercial 3.0 unported 3.0 license
Lexically Suggest, Logically Define:Lexically Suggest, Logically Define:
QA of Qualifiers & QA of Qualifiers & Expected Results of Post-CoordinationExpected Results of Post-Coordination
in SNOMED CTin SNOMED CT
Alan Rector & Luigi Iannone
with thanks to Robert Stevens
BioHealth Informatics GroupSchool of Computer Science &
Northwest Institute of BioHealth InformaticsUniversity of Manchester, Manchester M13 9PL
http://dx.doi.org/10.1016/j.jbi.2011.10.002
© University of Manchester Creative Commons Attribution-NonCommercial 3.0 unported 3.0 license
Pre-coordination and post-coordinationPre-coordination and post-coordination
► Pre-coordination►SNOMED authors define “Acute bronchitis”
• Classifier creates correct hierarchy
►Clinical user enters “Acute bronchitis” (or its code)
► Post-coordination►Clinical user enters “Bronchitis” + “Acute”
►Classifier finds any equivalent term or places the expression in the right place in the hierarchy
• Concept does not need to exist beforehand, e.g.Might define “Acute” + “Bronchitis” + “Right main stem bronchus”‣ Would still be in the correct place in hierarchy even if no term exists.
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Can SNOMED post-coordination work?Can SNOMED post-coordination work?Do SNOMED authors pre-coordinate consistently?Do SNOMED authors pre-coordinate consistently?
► Two related questions?►Are SNOMED qualified expressions expressed consistently?
• If SNOMED authors don’t do it consistently, can anyone else?
► Proxies: In either case►The definitions should allow the description logic classifier to
organize the hierarchies correctly• Includes determining equivalence between pre- and post- coordinated
forms‣ Necessary but not sufficient for post-coordination to work
►For post coordination, must be well defined consistent patterns that users & software develpers understand
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First tryFirst try
► Take a simple case: “acute” and “chronic”
► Look at the pattern SNOMED uses to defineAcute disease and Chronic disease
► Follow Campbell, Tuttle, & Spackman and see how many diseases named “Acute…” or “Chronic …” are retrieved under the pattern
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Definition of acute & chronicDefinition of acute & chronic
► Chronic disease == Disease & (RoleGroup some (Clinical course some Chronic))
broaden to
► Chronic finding == Clinical finding & (RoleGroup some (Clinical course some Chronic))
► … similarly for Acute► fully specified name: “Sudden onset AND/OR short duration”
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Write a script to check for Write a script to check for candidates in OPPL2candidates in OPPL2
► Requires ► Lexical match
► Description logic/OWL semantics -- open world, negation as provably false DL Reasoner
► Query semantics -- closed world, negation as failure over concepts in corpus
► Procedural semantics – add things to ontology
► ?C:CLASS=MATCH("'Chronic.*") LexicalSELECT ?C SubClassOf 'Clinical finding (finding)' DL SemanticsWHERE FAIL ?C SubClassOf ‘Chronic clinical finding (finding)’ Query SemanticsBEGIN
ADD ?C SubClassOf Candidate Procedural END;
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Next, classify candidates;Next, classify candidates;only top-level ones need be examinedonly top-level ones need be examined
► If a concept’s definition is changed, the change will be inherited by all descendants
► What did we find?►25%-30% of all lexical matches were “Candidate” errors,
but there were cases where • “Acute” and “Chronic” clearly no longer can be taken literally
‣ Chronic and acute leukemias and myeloproliferative disorders‣ So exclude them from candidates
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Then remaining candidates not Then remaining candidates not classified as classified as Chronic findingsChronic findings: :
► Why?►Systematic?
…or…
►Accidental?
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Look at definitionsLook at definitions
► Systematic► Chronic duodenal ulcer ==
Duodenal ulcer disease and RoleGroup some ( Associated morphology some Chronic ulcer (morphologic abnormality)
and Finding site some Duodenal structure)))
► Compare with► Chronic disease ==
Disease & (RoleGroup some (Clinical course some Chronic))
► Different qualifiers► Associated morphology
► Clinical course
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Different qualifiersDifferent qualifiers
► User guide says:►Acute & chronic may be morphological
• Chronic inflammation means mononuclear cell infiltration• Acute inflammation means polymorphonuclear cell infiltration
► For ulcers…► Chronic ulcer (morphological abnormality) is a kind of
Chronic inflammation (morphological abnormality)
► But users must understand► Acute and chronic ulcers are defined by Associated morphology,
► Acute obstruction is defined by Clinical course,
► Chronic cholecystitis by both!
► Are these the consequences we want?►Does this correspond to use in clinical care?
• Do we have evidence?• Should pathology take precedence over clinical observation?
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Late discovery:Late discovery:
Chronic inflammatory diseaseChronic inflammatory diseaseis defined as have both qualifiers! is defined as have both qualifiers!
► Chronic inflammatory disease == Chronic disease & RoleGroup some ( Associated morphology some Chronic inflammatory morphology) & RoleGroup some ( Clinical course some Chronic )
► Means:
►Classifier will chronic inflammatory disease only if you have both • Or that author asserts directly is a descendant of Chronic inflammatory
disease
►To get post-coordination to work you have to use both!• Will anyone remember to do so?• Obviously not all SNOMED authors,
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… … but even authors don’t, so but even authors don’t, so Many inflammations (…itis) are missed Many inflammations (…itis) are missed
► Authors have done some directly and not others►“Helter skelter” / “Mish mash” modelling
• Systematic inconsistency• What using a description logic is meant to avoid
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One solutionOne solution
► Change the axioms so that any disease with chronic inflammatory morphology has a chronic course
►Still within SNOMED’s DL EL++/OWL-EL• SNOROCKET still classifies it efficiently
► Or vice versa for all inflammatory diseases with chronic course
►Chronic course & inflammatory morphology Chronic inflammatory morphology
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How should the decision be made?How should the decision be made?How monitored?How monitored?
► New axiom may or may not be strictly “true”, but…
► What are the consequences?►For accuracy of authoring?
►For accuracy of retrieval?
►For consistency of setting value sets?
►For post-coordination?
►For meaninful use?
► Base decisions on evidence of consequences►Evidence-based terminologies / ontologies
► Whatever the decision, need a QA process to enforce and check it
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How big is the problem?How big is the problem?
► In a “module” based on the UMLS CORE Problem list subset:
►368 total chronic; 450 total acute
►103 (28%) chronic / 92 ( 20%) Acute were “candidates”,of these:
• Due to use of morphology only85 (83%) chronic / 92 (85%) Acute
• Due to simple errors and omissions18 (17%) chronic / 14 (15%)
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Other issues (See paper)Other issues (See paper)
► Hierarchy of qualifiers►Should Intermittent (course) be a kind of chronic (course)?
• What about “intermittent acute pain”?
►Pressure ulcers and decubitous ulcers are all chronic by definition
• Can there be an acute pressure ulcer?
► Odd anatomy►Lower back pain is a kind of Abdominal pain
• Because the lower back is part of the abdominal wall is part of the abdomen‣ (Anatomy under review by SNOMED)
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You have to use a classifierYou have to use a classifier
► This work can only be done by using a classifier to find inferences
►Post-coordination depends on the classifier
► To work efficiently, the classifier must be fast►For iterative analysis, < 1 min
► SNOROCKET in Protege is very fast and reliable►But still works better on modules than all of SNOMED
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Use of “modules” makes this possibleUse of “modules” makes this possible
► A “signature” is a subset of the entities in a description logic/OWL KB
► A “module” for a “signature” is a subset of the axioms & entities in the KB such that
► All inferences amongst entities in the signature can be inferred from the module
► For the UMLS CORE Problem List Subset► SNOMED Size ~300,000
• Classification time 2-8 minutes
► Signature (UMLS CORE Subset) ~8500
► Module extracted ~35,000• Classification time .25 – 2 minutes
► Also methods for extracting the changes and applying them to the whole
► Re-apply final methods to whole corpus if require
► Total effort for this study =< 2 person weeks
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SummarySummary► Lexical suggest, semantically define works to raise issues
► Post coordination of acute and chronic unlikely to workreliably, unless
►SNOMED makes pattern consistent
►Bases decisions on consequences for use in patient care• Are patient care clinicians likely to align with pathology in the ED?
► Other Findings►Working on modules makes analysis of SNOMED practical
►There are problems in the anatomy and qualifier hierarchies
► Questions►How many other such problems are there?
• How do they affect post-coordination?
►How to establish QA procedures to find out and prevent recurrence?
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http://dx.doi.org/10.1016/j.jbi.2011.10.002