Center of Excellence in Bioinformatics and Life Sciences GCRC SEMINAR Referent Tracking for Clinical and Translational Research Burlington, VT, USA, June 16, 2008 Werner CEUSTERS, MD Center of Excellence in Bioinformatics and Life Sciences

Short personal history 1959 - 2008 1977 2006 Short personal history 2004 1989 1992 2002 1995 1998 1993

‘The spectrum of the Health Sciences’ Turning data in knowledge ? http://www.uvm.edu/~ccts

Source of all data Reality !

Ultimate goal of Referent Tracking A digital copy of the world

Requirements for this digital copy R1: A faithful representation of reality R2 … of everything that is digitally registered, what is generic  scientific theories what is specific  what individual entities exist and how they relate R3: … throughout reality’s entire history, R4 … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, ...

In fact … the ultimate crystal ball

The ‘binding’ wall How to do it right ? A cartoon of the world

Structure of this presentation Problem statement: Today’s Health IT infrastructure is highly capable to communicate data and knowledge, but lacks reliable methods: a) to assess whether the information is any good, and b) to integrate data and knowledge. Proposed solutions: Realism-based ontology Referent Tracking Applications and projects.

Where is health IT now ?

Better information care A general belief: Better information care

‘Information’ versus ‘informing’ Being better informed Better information care

Being better informed Better Better information care A general belief: Being better informed Concerns primarily the delivery of information: Being better informed Better Better information care

A general belief: Being better informed pretty well covered Concerns primarily the delivery of information: Timely, Where required (e.g. bed-side computing), What is permitted, What is needed. Involves: Connecting systems, Making systems interoperable: Syntactically, Semantically. pretty well covered long way to go

“Better Information” must cover … Patient-specific information EHR-EMR-ENR-… PHR Various modality related databases Lab, imaging, … Textbooks Classification systems Terminologies Ontologies 1 3 Scientific “knowledge” 2

Key questions … What does ‘better’ information mean ? Is the current quality of health information not good enough ? If not, how to make it better ?

2 NCI Thesaurus (April 2008)

2 NCI Thesaurus (April 2008) ?

Diabetes Mellitus in MeSH 2008 ? Different set of more specific terms when different path from the top is taken.

Snomed CT (July 2007): “fractured nasal bones”

Cause: coding / classification confusion 2 Cause: coding / classification confusion A patient with a fractured nasal bone A patient with a broken nose A patient with a fracture of the nose =

Cause: coding / classification confusion 2 Cause: coding / classification confusion A patient with a fractured nasal bone A patient with a broken nose A patient with a fracture of the nose = A patient with a fractured nasal bone A patient with a broken nose A patient with a fracture of the nose =

MeSH: some paths from top to Wolfram Syndrome 2 Wolfram Syndrome All MeSH Categories Diseases Category Nervous System Diseases Cranial Nerve Diseases Optic Nerve Optic Atrophy Optic Atrophies, Hereditary Eye Diseases Eye Diseases, Hereditary Optic Nerve Diseases Male Urogenital Diseases Urologic Diseases Kidney Diseases Diabetes Insipidus Female Urogenital Diseases and Pregnancy Complications Neurodegenerative Diseases Heredodegenerative Disorders, Nervous System

What would it mean if used in the context of a patient ? ??? 3 Wolfram Syndrome All MeSH Categories Diseases Category Nervous System Diseases Cranial Nerve Diseases Optic Nerve Optic Atrophy Optic Atrophies, Hereditary ??? Eye Diseases Eye Diseases, Hereditary Optic Nerve Diseases Female Urogenital Diseases and Pregnancy Complications Male Urogenital Diseases Urologic Diseases Kidney Diseases Diabetes Insipidus Neurodegenerative Diseases Heredodegenerative Disorders, Nervous System … has has

How many disorders are listed ? The same type of location code used in relation to three different events might or might not refer to the same location. 1 How many disorders are listed ? 5572 04/07/1990 26442006 closed fracture of shaft of femur 81134009 Fracture, closed, spiral 12/07/1990 9001224 Accident in public building (supermarket) 79001 Essential hypertension 0939 24/12/1991 255174002 benign polyp of biliary tract 2309 21/03/1992 47804 03/04/1993 58298795 Other lesion on other specified region 17/05/1993 298 22/08/1993 2909872 Closed fracture of radial head 01/04/1997 PtID Date ObsCode Narrative 20/12/1998 255087006 malignant polyp of biliary tract Three references of hypertension for the same patient denote three times the same disease. If the same fracture code is used for the same patient on different dates, then these codes might or might not refer to the same fracture. If two different fracture codes are used in relation to observations made on the same day for the same patient, they might refer to the same fracture If two different tumor codes are used in relation to observations made on different dates for the same patient, they may still refer to the same tumor. The same fracture code used in relation to two different patients can not refer to the same fracure.

Realism-based Ontology Major problems Solutions A mismatch between what is - and has been - the case in reality, and representations thereof in: (generic) Knowledge repositories, and (specific) Data and Information repositories. An inadequate integration of a) and b). P h i l o s p y H I T Philosophical realism Realism-based Ontology Referent Tracking

Requirements for a digital copy of the world R1: A faithful representation of reality R2 … of everything that is digitally registered, what is generic  scientific theories what is specific  what individual entities exist and how they relate R3: … throughout reality’s entire history, R4 … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, ...

Realism-based Ontology

Get down that wall Realism-based Ontology: teaches us how to build an adequate grid. Granular Partition Theory: relates the copy to reality.

‘Ontology’: one word, two meanings In philosophy: Ontology (no plural) is the study of what entities exist and how they relate to each other; In computer science and (biomedical informatics) applications: An ontology (plural: ontologies) is a shared and agreed upon conceptualization of a domain; Our ‘realist’ view within the Ontology Research Group combines the two: We use realism, a specific theory of ontology, as the basis for building high quality ontologies, using reality as benchmark.

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.

Three major views on reality Realism Conceptualism Nominalism Basic questions: What does a general term such as ‘diabetes’ refer to? Do generic things exist? Universal Concept Collection of particulars yes: in particulars perhaps: in minds no

Dominant view in computer science is conceptualism Realism Conceptualism Nominalism Basic questions: What does a general term such as ‘tree’ refer to? Do generic things exist? yes: in particulars perhaps: in minds no Universal Concept Collection of

Dominant view in computer science is conceptualism Realism Conceptualism Nominalism Semantic Triangle concept object term Embedded in Terminology

‘Terminology’: one word, two meanings Terminology is the study of identifying and labelling ‘concepts’ pertaining to a subject field. Terminology related activities: analysing the concepts and concept structures, identifying the terms assigned to the concepts, establishing correspondences between terms, possibly in various languages, compiling a terminology, on paper or in databases, managing terminology databases, creating new terms, as required.

Why this interest in biomedical terminologies? ‘Nuances in the English language can be both challenging and amusing, however, when variants in language impact treatment, safety and billing, it is all challenge and no humor. Although English contains a reasonable degree of conformity, divergence in phrasing and meaning can compound comprehension problems and impact patient safety. These language "woes" can be minimized through the use of sophisticated healthcare IT systems with terminology management services.’ Schwend GT. The language of healthcare. Variance in the English language is harming patients and hospitals' bottom lines. Is healthcare IT the solution? Health Manag Technol. 2008 Feb;29(2):14, 16, 18

This is the ‘terminology / ontology divide’ However … Terminology: solves certain issues related to language use, i.e. with respect to how we talk about entities in reality (if any); Relations between terms / concepts does not provide an adequate means to represent independent of use what we talk about, i.e. how reality is structured; Women, Fire and Dangerous Things (Lakoff). Ontology (of the right sort): Language and perception neutral view on reality. Relations between entities in first-order reality This is the ‘terminology / ontology divide’

The semantic triangle revisited Representation and Reference First Order Reality concepts about terms concepts objects terms

Terminology Realist Ontology Representation and Reference concepts terms representational units universals particulars about objects First Order Reality

Terminology Realist Ontology Representation and Reference concepts terms representational units about objects universals particulars First Order Reality

Terminology Realist Ontology Representation and Reference representational units concepts terms cognitive units communicative units about objects universals particulars First Order Reality

Three levels of reality in Realist Ontology Terminology Realist Ontology Representation and Reference Representational units in various forms about (1), (2) or (3) representational units cognitive units communicative units (2) Cognitive entities which are our beliefs about (1) (1) Entities with objective existence which are not about anything universals particulars First Order Reality

The three levels applied to diabetes management Generic Specific 3. Representation ‘person’ ‘drug’ ‘insulin’ ‘W. Ceusters’ ‘my sugar’ 2. Beliefs (knowledge) DIAGNOSIS INDICATION my doctor’s work plan diagnosis 1. First-order reality me my blood glucose level my NIDDM my doctor my doctor’s computer MOLECULE PERSON DISEASE PATHOLOGICAL STRUCTURE PORTION OF INSULIN DRUG

The three levels applied to cancer cell identification Generic Specific 3 ‘cancer cell’ ‘cell 1’ #6: #5’s belief that #1 is a cancer cell #6: #4’s belief that #1 is not a cancer cell 2 diagnosis #3: image of #1 in #2 #1: that debris #2: framelet 40 #4: that pathologist #5: this algorithm debris image cancer cell framelet 1 Weaver DL, Krag DN, Manna EA, Ashikaga T, Harlow SP, Bauer KD. Comparison of pathologist-detected and automated computer-assisted image analysis detected sentinel lymph node micrometastases in breast cancer. Mod Pathol. 2003 Nov;16(11):1159-63. Links

Terminology is too reductionist What concepts do we need? How do we name concepts properly?

The power of realism in ontology design Reality as benchmark ! 1. Is the scientific ‘state of the art’ consistent with biomedical reality ?

The power of realism in ontology design Reality as benchmark ! 2. Is my doctor’s knowledge up to date?

The power of realism in ontology design Reality as benchmark ! 3. Does my doctor have an accurate assessment of my health status?

The power of realism in ontology design Reality as benchmark ! 4. Is our terminology rich enough to communicate about all three levels?

The power of realism in ontology design Reality as benchmark ! 5. How can we use case studies better to advance the state of the art?

Realist ontology: a modern version of Alberti’s grid !

Referent Tracking

Requirements for a digital copy of the world R1: A faithful representation of reality R2 … of everything that is digitally registered, what is generic  scientific theories  realism-based ontologies what is specific  what individual entities exist and how they relate R3: … throughout reality’s entire history, R4 … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, ...

The reality: a digital copy of part of the world Applying the grid should not give a distorted representation of reality, but only an incomplete representation !!!

Key issue: keeping track of what the bits denote

Fundamental goal of Referent Tracking explicit reference to the concrete individual entities relevant to the accurate description of each patient’s condition, therapies, outcomes, ... Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform. 2006 Jun;39(3):362-78.

Method: numbers instead of words Introduce an Instance Unique Identifier (IUI) for each relevant particular (individual) entity 235 78 5678 321 322 666 427 Ceusters W, Smith B. Strategies for Referent Tracking in Electronic Health Records. J Biomed Inform. 2006 Jun;39(3):362-78.

IUI: Instance Unique Identifiers denotes Relationship managed in the RTS 5241 89023 109427

Three basic sorts of relationships humans are mammals universal universal Werner Ceusters instance-of at t human particular particular Werner Ceusters’ nose part-of Werner Ceusters

The principle of Referent Tracking ‘John Doe’s liver tumor was treated with RPCI’s irradiation device’ ‘John Doe’s ‘John Smith’s liver liver tumor tumor was treated was treated with with RPCI’s RPCI’s irradiation device’ irradiation device’ #1 #3 #2 #4 #5 #6 instance-of at t1 instance-of inst-of at t2 treating person liver tumor clinic device #10 #30 #20 #40 #5 #6

EHR – Ontology “collaboration”

Reasoning over instances and universals instance-of at t #105 caused by

Essentials of Referent Tracking Theory Generation of universally unique identifiers; deciding what particulars should receive a IUI; finding out whether or not a particular has already been assigned a IUI (each particular should receive maximally one IUI); using IUIs in the EHR, i.e. issues concerning the syntax and semantics of statements containing IUIs; determining the truth values of statements in which IUIs are used; correcting errors in the assignment of IUIs.

Requirements for a digital copy of the world R1: A faithful representation of reality R2 … of everything that is digitally registered, what is generic  scientific theories what is specific  what individual entities exist and how they relate R3: … throughout reality’s entire history, R4 … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, ...

Eternal memory

Accept that everything may change: changes in the underlying reality: Particulars come, change and go

Identity & instantiation child adult person t Living creature animal caterpillar butterfly

Accept that everything may change: changes in the underlying reality: Particulars come, change and go changes in our (scientific) understanding: The plant Vulcan does not exist

Reality and representation: both in evolution IUI-#3 O-#0 O-#2 Repr. O-#1 = “denotes” = what constitutes the meaning of representational units …. Therefore: O-#0 is meaningless

Accept that everything may change: changes in the underlying reality: Particulars come, change and go changes in our (scientific) understanding: The plant Vulcan does not exist reassessments of what is considered to be relevant for inclusion (notion of purpose). encoding mistakes introduced during data entry or ontology development.

In John Smith’s Electronic Health Record: What are the possibilities ? Changes over time In John Smith’s Electronic Health Record: At t1: “male” at t2: “female” What are the possibilities ? Change in reality: transgender surgery change in legal self-identification Change in understanding: it was female from the very beginning but interpreted wrongly Correction of data entry mistake: it was understood as male, but wrongly transcribed (Change in word meaning)

Requirements for a digital copy of the world R1: A faithful representation of reality R2 … of everything that is digitally registered, what is generic  scientific theories what is specific  what individual entities exist and how they relate R3: … throughout reality’s entire history, R4 … which is computable in order to … … allow queries over the world’s past and present, … make predictions, … fill in gaps, … identify mistakes, ...

Referent Tracking System

Referent Tracking System Components Referent Tracking Software Manipulation of statements about facts and beliefs Referent Tracking Datastore: IUI repository A collection of globally unique singular identifiers denoting particulars Referent Tracking Database A collection of facts and beliefs about the particulars denoted in the IUI repository Manzoor S, Ceusters W, Rudnicki R. Implementation of a Referent Tracking System. International Journal of Healthcare Information Systems and Informatics 2007;2(4):41-58.

Place in the Health IT arena

Assertion of assignments IUI assignment is an act of which the execution has to be asserted in the IUI-repository: Di = <IUId, Ai, td> IUId IUI of the registering agent Ai the assertion of the assignment < IUIp, IUIa, tap> IUIa IUI of the author of the assertion IUIp IUI of the particular tap time of the assignment td time of registering Ai in the IUI-repository Neither td or tap give any information about when # IUIp started to exist ! That might be asserted in statements providing information about # IUIp .

Elementary RTS tuple types Relationships between particulars taken from a realism-based relation ontology Instantiation of a universal Annotation using terms from a non-realist terminology ‘Negative findings’ such as absences, missing parts, preventions, … Names for a particular

RTS architecture

Data store

RT templates RDFS schema diagram

RTS example graph

RT applications

eyeGENE (June 2008 - …)

Ontology for Risks Against Patient Safety

REMINE: RT-based adverse event analysis

Ontology-based IT support for large scale field studies in Psychiatry assess the functional and technical requirements to be fulfilled by a data management system able to do justice to both the dimensional and categorical approach in psychiatric diagnosis; design an implementation and funding plan for the technical infrastructure to be built in order to support data collection and analyses in large-scale field studies in psychiatry, and; initiate the collaborations needed to deliver data collection and analyses services to provide the answers to the questions raised in the DSM-V research agenda.

Making existing EHR systems RT compatible

RT and student, employee tracking (InfoSource) Primary goal: to integrate in stepwise fashion a functional RT system with a set of data from the UB Infosource repository in order to achieve the highest levels of quality and completeness of the data on which the administrative and business needs of the university depend. Secondary goals: 1) use this experience to optimize the RTS, 2) refine the methodology of deploying the RTS in an enterprise. 3) demonstrate that a limited application of RT is better than no application at all 4) develop an Ontology for Higher Education

Semantic integration of the CCW data Purpose: Better comparability of Chronic Condition Warehouse data Statistical validation of the ontology Explanation of observed correlations between assessment data elements Finding patient subpopulations exhibiting correlations which are near-significant without the ontology, but significant with the ontology Two level integration: Type level : poor man’s linkage Particular level: rich man’s linkage

Codes for types AND identifiers for instances 5572 04/07/1990 26442006 closed fracture of shaft of femur 81134009 Fracture, closed, spiral 12/07/1990 9001224 Accident in public building (supermarket) 79001 Essential hypertension 0939 24/12/1991 255174002 benign polyp of biliary tract 2309 21/03/1992 47804 03/04/1993 58298795 Other lesion on other specified region 17/05/1993 298 22/08/1993 2909872 Closed fracture of radial head 01/04/1997 PtID Date ObsCode Narrative 20/12/1998 255087006 malignant polyp of biliary tract IUI-001 IUI-003 IUI-004 IUI-005 IUI-007 IUI-002 IUI-012 IUI-006 7 distinct disorders

Summary (1) Referent Tracking: Particulars include: Uses IUIs to denote particulars, Uses realism-based ontologies (3D and 4D) to describe these particulars in relation to each other and to universals. Particulars include: Me, this laptop, this room My beliefs and wishes about the former Statements registered in the RT Datastore

An RT system comes with services to: Summary (2) An RT system comes with services to: Assign IUIs Annotate reality Track changes in reality, in our beliefs, and in the status of the RT Data store itself Reason over instances with or without additional use of computable ontologies.