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Formal Ontology in Information Systems (FOIS 2008). Introducing Realist Ontology for the Representation of Adverse Events Saarbrucken, Germany, Nov 2, 2008. Werner CEUSTERS, MD Center of Excellence in Bioinformatics and Life Sciences, and
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Formal Ontology in Information Systems (FOIS 2008).Introducing Realist Ontology for theRepresentation of Adverse EventsSaarbrucken, Germany,Nov 2, 2008 Werner CEUSTERS, MD Center of Excellence in Bioinformatics and Life Sciences, and National Center for Biomedical Ontology, University at Buffalo, NY, USA Ceusters W, Capolupo M, De Moor G, Devlies J. Introducing Realist Ontology for the Representation of Adverse Events. In: Eschenbach C, Gruninger M. (eds.) Formal Ontology in Information Systems, IOS Press, Amsterdam, 2008
What is an adverse event ? • We asked Google • We asked the experts • And as is often the case in biomedical terminology, … • … we obtained many distinct and mutually incompatible answers!
a reaction … an effect … an event … a problem … an experience … an injury … a symptom … an illness … an occurrence … a change … and also: something … an act … an observation … as well as … a term !!! What is an adverse event ?
Clearly, confusion reigns … The question “What are adverse events?” cannot be answered directly, but needs to be reformulated as “What might the author of a particular sentence containing the phrase ‘adverse event’ be referring to when he uses that phrase?”.
At least one argument • There is no entity which would be such that, were it placed before these authors, they would each in turn be able to point to it and respectively say – faithfully and honestly – • “that is an observation” (definition D4), • “that is an injury” (definition D9), • “that is a laboratory finding” (definition D6). • Clearly, • nothing which is an injury can be a laboratory finding, although, of course, laboratory findings can aid in diagnosing an injury or in monitoring its evolution. • nothing which is a laboratory finding, can be an observation, although, of course, some observation must have been made if we are to arrive at a laboratory finding.
Current approaches to bring clarity • Classification: • e.g. Chang et al. developed – based on a set of criteria – a classification schema consisting of five root nodes: • Impact, Type, Domain, Cause, and Prevention and Mitigation • Building a consensus definition (and reject the others): • e.g. BRIDG • is very reductionist • the other definitions do not disappear and will still be used • Building ontologies • But thus far, unfortunately, by using the very weak principles underlying ‘concept’-orientation such that in some cases ‘age’ and ‘gender’ become a subclass of ‘patient’.
Our research questions • Can it be done ‘right’ ? • Would realism-based ontology be of value ? • To identify the different sorts of entities that all can be denoted by the term ‘adverse event’ ? • To find out how these entities relate to each other and to use these relationships to identify to what extent the various definitions overlap ? • To describe the portion of reality that is covered by all entities denoted by the terms that appear in the various defintions for ‘adverse event’ ?
Hypothesis • Because … • all the authors of the mentioned definitions use the term ‘adverse event’ in some context for a variety of distinct entities, and • these contexts look quite similar • in each of them, more or less the same sort of entities seem to be involved • … there is some common ground (some portion of reality) which is such that the entities within it can be used as referents for the various meanings of ‘adverse event’.
Study design • Goal: • to bring clarity in the terminological wilderness that grew out of all current efforts. • Methods: • analyze the literature and collect all relevant definitions. • study a variety of relevant classification systems, taxonomies, terminologies and concept-based ontologies, • apply the realism-based principles advocated in • Basic Formal Ontology (BFO) • Referent Tracking (RT) • build a representation for the relevant portion of reality • assess whether the representation covers what is (or might be) expressed in the various definitions
Realism-based ontology • Basic assumptions: • reality exists objectively in itself, i.e. independent of the perceptions or beliefs of cognitive beings; • reality, including its structure, is accessible to us, and can be discovered through (scientific) research; • the quality of an ontology is at least determined by the accuracy with which its structure mimics the pre-existing structure of reality.
Basic Formal Ontology • The world consists of • universals, • particulars that are • either occurrents or continuants, • the latter being either dependent or independent, • relationships of the form: • <particular , universal> e.g. is-instance-of, • <particular , particular> e.g. is-part-of • <universal , universal> e.g. isa (is-subtype-of) Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, November 8, 2006, Baltimore MD, USA
Three levels of reality • The world ‘as it is’ prior to a cognitive agent’s perception thereof; • Cognitive representations of the world build up cognitive agents ‘in their minds’; • Representational artifacts designed to make these representations publicly accessible in some enduring fashion. Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, November 8, 2006, Baltimore MD, USA
e.g. human extension-of universal instance-of e.g. all humans class member-of P P P P P P P P P P P P Level 1: universals, particulars and classes e.g. : me, you, George W. Bush
Sorts of classes (1) • Extension of a universal • e.g. all humans • Defined class • a subset of the extension of a universal defined as being such that the members of this class exhibit an additional property which is • (a) not shared by all instances of the universal, and • (b) also (can be) exhibited by particulars which are not instances of that universal. • e.g. all human beings that suffer from pneumococcal pneumonia
Sorts of classes (2) • Compositional class (or ‘ad hoc class’) • an ad hoc collection of particulars such that some particulars are instances of a universal which is not instantiated by other particulars of that class • e.g. all sick human beings and polar bears
Referent Tracking (RT) • Purpose: • explicitreference to the particulars denoted by terms in descriptions of portions of reality Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform. 2006 Jun;39(3):362-78.
78 235 5678 321 322 666 427 Numbers instead of words • Method: • Introduce an Instance Unique Identifier(IUI) for each relevant particular (individual) entity
Realism-based Ontology instance-of at t caused by #105 Combining Referent Tracking with Ontology RT-based Data model
Representations for portions of reality Level 2 or 3 Level 1
Representations for portions of reality Level 2 or 3 Level 3 Level 1
Why does this matter ? • Be precise about what representational units in either an ontology or data repository stand for. • Each such unit in an ontology should come with additional information on whether it denotes: • an entity at level 1, level 2 or level 3 and • a universal, or a defined or composite class
Detailed example: Subject of Care • Index: C1 • For purposes of the paper only. Will be replaced by a CUI in the published ontology • Denotation: subject of care • Suitable term to denote any particular that is member of the class • ClassType: Defined Class • It is not a universal because the particulars have a property that is not exclusive to them • Particulartype: independent continuant • Supertype, either internal, in BFO, or in any other realism-based ontology • Description: person to whom harm might have been done through an act under scrutiny • provides association with other classes or universals.
Representing particular cases • Is the generic representation of the portion of reality adequate enough for the description of particular cases? • Example: a patient • born at time t0 • undergoing anti-inflammatory treatment and physiotherapy since t2 • for an arthrosis present since t1 • develops a stomach ulcer at t3.
Anti-inflammatory treatment with ulcer development NB: Time stamp format follows CEN EN 12388:2005. Health informatics - Time standards for healthcare specific problems.
At t0, the patient is born, and since that time, his stomach is part of him and a structure integrity inheres in it: #1 instance-of personsince t0 #7 part-of #1since t0 #8 instance_of C8 since t0 #8 inheres_in #7 since t0 t0 t1 t2 t3 #7 #1’s stomach C8 structure integrity #8 #7’s structure integrity #1 the patient who is treated Time line and dependencies (1)
t0 t1 t2 t3 C5 underlying disease #7 #1’s stomach C8 structure integrity #8 #7’s structure integrity #1 the patient who is treated #4 #1’s arthrosis Time line and dependencies (2) • At t1, the patient acquires arthrosis: • #4 member_of C5 since t1 • #4 inheres_in #1 since t1
C1 subject of care C3 act of care t0 t1 t2 t3 C4 care giver C5 underlying disease C6 involved structure #7 #1’s stomach C8 structure integrity #8 #7’s structure integrity #2 #1’s treatment #1 the patient who is treated #5 #1’s anti-inflammatory treatment #3 the physician responsible for #2 #6 #1’s physiotherapy #4 #1’s arthrosis Time line and dependencies (3) • At t2, the patient consults #3 who starts treatment. It is then that the patient becomes a member of subject of care (C1) and his stomach a member of involved structure (C6)
C1 subject of care #13 #11 cognitive representation in #3 about #9 change brought about by #9 C2 act under scrutiny #12 noticing #9 C3 act of care t0 t1 t2 t3 C4 care giver C5 underlying disease C6 involved structure #7 #1’s stomach C8 structure integrity #8 #7’s structure integrity #2 #1’s treatment #1 the patient who is treated #5 #1’s anti-inflammatory treatment #3 the physician responsible for #2 #6 #1’s physiotherapy C10 harm #4 #1’s arthrosis #9 #1’s stomach ulcer Time line and dependencies … and so forth
Advantage 1: reduce ambiguity in definitions • E.g. ‘adverse drug reaction: an undesirable response associated with use of a drug that either compromises therapeutic efficacy, enhances toxicity, or both.’ (Joint Technical Committee) • May denote something on level 1, e.g. a realizableentity which exists objectively as an increased health risk; in this sense any event ‘that either compromises therapeutic efficacy, enhances toxicity, or both’ is undesirable; • May denote something on level 2, so that, amongst all of those events which influence therapeutic efficacy or toxicity, only some are considered undesirable (for whatever reason) by either the patient, the caregiver or both; or • May denote something relating to level 3, so a particular event occurring on level 1 is undesirable only when it is an instance of a type of event that is listed in some guideline, good practice management handbook, i.e. in some published statement of the state of the art in relevant matters.
Advantage 2: reveal hidden assumptions • E.g.: ‘adverse event: an event that results in unintended harm to the patient by an act of commission or omission rather than by the underlying disease or condition of the patient’ (IOM) • But: • An ‘act of omission’ is under the realist agenda not an entity that exist at level 1, but rather a level 3 entity denoting a configuration in which not was done what good practice requires to be done, • Something what not exist at level 1, cannot cause harm by itself, • Thus it must be the underlying disease.
Better definition for the latter • An event that results in unintended harm to the patient either • (1) through an act of commission rather than through some underlying disease or condition of the patient, or • (2) through an underlying disease or condition of the patient in the absence of appropriate actions which should have been taken in line with the state of the art in dealing with the disease. • Examples: • (1) leaving instruments in the body after surgery • (2) not reducing excessive bleeding during surgery • It is the bleeding that eventually will kill the patient, not the ‘not stopping the bleeding’