OpenEHR Terminology binding Thomas Beale. © Ocean Informatics 2010 Problem overview.

Slides:



Advertisements
Similar presentations
Testing Relational Database
Advertisements

Semantic Interoperability in Health Informatics: Lessons Learned 10 January 2008Semantic Interoperability in Health Informatics: Lessons Learned 1 Medical.
Archetypes in HL7 v2 Andrew McIntyre Medical-Objects HL7 International May 2009.
Archetypes in HL7 2.x Archetypes in HL7 Version 2.x Andrew McIntyre Medical Objects 9 th HL7 Australia Conference, 8.
Archetypes in HL7 2.x Archetypes/Structure in HL7 Version 2.x Andrew McIntyre Medical-Objects 10 th HL7 Australia Conference,
Health IT Workforce Curriculum Version 1.0 Fall Networking and Health Information Exchange Unit 4e Basic Health Data Standards Component 9/Unit.
CIMI Modelling Taskforce Workshop (Groningen) Dr Linda Bird 2 nd – 4 th December 2012.
openEHR The Reference Model
Data Standards The use of data structures and OpenEHR Richard Kavanagh, Head of Data Standards, HSCIC.
Catalina Martínez-Costa, Stefan Schulz: Ontology-based reinterpretation of the SNOMED CT context model Ontology-based reinterpretation of the SNOMED CT.
HISI Conference – 18 th November 2010 Towards use of OpenEHR Archetypes to support views of Cystic Fibrosis Review Records Derek Corrigan.
Thomas Beale CTO, Ocean Informatics Copyright 2012 Ocean Informatics Tromso 27 May 2014.
CIMI Modelling Taskforce Progress Report
HSCIC Data Dictionary for Care Modelling Approach Dr. Rahil Qamar Siddiqui Health and Social Care Information Centre, NHS, England.
Introduction to openEHR
NHS Modelling Efforts – ISO13606 adoption and beyond Dr. Rahil Qamar Siddiqui Health and Social Care Information Centre, NHS, England.
OASIS Reference Model for Service Oriented Architecture 1.0
Archetypes in HL7 2.x Snomed-CT “Computable Medical Records” Andrew McIntyre Medical-Objects NEHTA Snomed-CT Workshop.
July 11 th, 2005 Software Engineering with Reusable Components RiSE’s Seminars Sametinger’s book :: Chapters 16, 17 and 18 Fred Durão.
Implementing a Clinical Terminology David Crook Subset Development Project Manager SNOMED in Structured electronic Records Programme NHS Connecting for.
Integrating disease and diagnosis semantics in clinical archetypes Leonardo Lezcano Miguel-Ángel Sicilia {leonardo.lezcano, University.
Software Requirements
6/8/991 Analysis Tuesday 09/14/99 Revised: September 11, 2000 (APM)
Creating Architectural Descriptions. Outline Standardizing architectural descriptions: The IEEE has published, “Recommended Practice for Architectural.
HL7 RIM Exegesis and Critique Regenstrief Institute, November 8, 2005 Barry Smith Director National Center for Ontological Research.
IT 244 Database Management System Data Modeling 1 Ref: A First Course in Database System Jeffrey D Ullman & Jennifer Widom.
RDF (Resource Description Framework) Why?. XML XML is a metalanguage that allows users to define markup XML separates content and structure from formatting.
Concept Model for observables, investigations, and observation results For the IHTSDO Observables Project Group and LOINC Coordination Project Revision.
NHS CFH – Approach to Data Standards Interoperability Laura Sato Informatics Standards Lead, Data Standards & Products Chair, NHS CFH EHR Content Technical.
An Introduction to Design Patterns. Introduction Promote reuse. Use the experiences of software developers. A shared library/lingo used by developers.
Detailed design – class design Domain Modeling SE-2030 Dr. Rob Hasker 1 Based on slides written by Dr. Mark L. Hornick Used with permission.
This material was developed by Duke University, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information.
Modeling Options HSPC Meeting June 17, 2015 Washington DC.
This chapter is extracted from Sommerville’s slides. Text book chapter
Overview, Benefits and how to approach Implementing - Robyn Richards (NEHTA)
OHTO -99 SOFTWARE ENGINEERING “SOFTWARE PRODUCT QUALITY” Today: - Software quality - Quality Components - ”Good” software properties.
©2001 Sowerby Centre for Health Informatics at Newcastle Progress on Virtual Medical Record HL7 Salt Lake City.
1 Relational Databases and SQL. Learning Objectives Understand techniques to model complex accounting phenomena in an E-R diagram Develop E-R diagrams.
BAA - Big Mechanism using SIRA Technology Chuck Rehberg CTO at Trigent Software and Chief Scientist at Semantic Insights™
CS 4850: Senior Project Fall 2014 Object-Oriented Design.
CDE to RIM semantics Mapping Process. Steps Read the definition of the CDE Determine if the CDE represents an Act, Entity, Role Determine if there are.
Standards Analysis Summary vMR –Pros Designed for computability Compact Wire Format Aligned with HeD Efforts –Cons Limited Vendor Adoption thus far Represents.
EuroRec Annual Conference 2006 EHR systems and certification Archetypes: the missing link? Dr Dipak Kalra Centre for Health Informatics and Multiprofessional.
1 Tutorial 14 Validating Documents with Schemas Exploring the XML Schema Vocabulary.
Part4 Methodology of Database Design Chapter 07- Overview of Conceptual Database Design Lu Wei College of Software and Microelectronics Northwestern Polytechnical.
This material was developed by Duke University, funded by the Department of Health and Human Services, Office of the National Coordinator for Health Information.
1 CS 430: Information Discovery Sample Midterm Examination Notes on the Solutions.
SNOMED Bound to (Information) Model Putting terminology to work… Koray Atalag MD, PhD, FACHI Senior Research Fellow (NIHI & ABI)
Copyright ©2004 Virtusa Corporation | CONFIDENTIAL Requirement Engineering Virtusa Training Group 2004 Trainer: Ojitha Kumanayaka Duration : 1 hour.
Metadata By N.Gopinath AP/CSE Metadata and it’s role in the lifecycle. The collection, maintenance, and deployment of metadata Metadata and tool integration.
© University of Manchester Creative Commons Attribution-NonCommercial 3.0 unported 3.0 license Lexically Suggest, Logically Define: QA of Qualifiers &
CSIS 4850: CS Senior Project – Spring 2009 CSIS 4850: Senior Project Spring 2009 Object-Oriented Design.
Fusion Design Overview Object Interaction Graph Visibility Graph Class Descriptions Inheritance Graphs Fusion: Design The overall goal of Design is to.
SNOMED CT Family of Languages Dr Linda Bird, IHTSDO Implementation Specialist.
IHTSDO Education & Implementation Update Dr Linda Bird Implementation Specialist.
C-CDA Scorecard Rubrics Review of CDA R2.0 Smart C-CDA Scorecard Rules C. Beebe.
Transforming CIMI into SNOMED expressions Source model Target model Model mapping Source file Target file XSLT Issues.
Attributes and Values Describing Entities. Metadata At the most basic level, metadata is just another term for description, or information about an entity.
The Quality Gateway Chapter 11. The Quality Gateway.
A Proposed Approach to Binding SNOMED CT to HL7 FHIR Dr Linda Bird Senior Implementation Specialist.
LOINC – SNOMED CT Cooperation on Content
11th HL7 Australia Conference, 13th December 2006
CIMI Semantics Roundup
Distribution and components
Requirements Analysis and Specification
Clinical Assessment Instruments and the LOINC/SNOMED CT Relationship
Functional status and activities of daily living concepts
Object-Oriented Design
A bit more about Read Codes and SNOMED CT
Model ID: Model to represent entire statement including context
Presentation transcript:

openEHR Terminology binding Thomas Beale

© Ocean Informatics 2010 Problem overview

© Ocean Informatics 2010 What is ‘terminology binding’? A formally expressible connection between information model representation and terminology representation of clinical statements recorded in the EHR

© Ocean Informatics 2010 What is the ‘binding problem’? We need to know how to control the use of terminology within structured data so that it achieves what we want: Provides basis for querying Economically feasible First, we need to know how to structure data so it: Doesn’t violate ontological truths; Is mappable to ontological concepts; Supports data entry, storage, querying, reuse

© Ocean Informatics 2010 Which ‘structured’ data? Two kinds: Legacy proprietary: structures are all different Shared, standardised: agreed structures and information model, within a community of users (can be more than one such community). The second kind we can standardise on. Shared clinical data generally include structure and many data types.

© Ocean Informatics 2010 Data are structured Clinical statements are naturally structured, e.g. lab results: list / tree structure; normal ranges; Microbiology is usually a large tree structure vital signs: timing and multiple data points; BP: (2 data points + patient state) x time-series physical examination: structured by anatomy E.g. Endoscopy of colon assessments: structured according to e.g. temporal model of disease course; orders: timing info, structured medication info; actions: timing, medication structured info

© Ocean Informatics 2010 Other sources of structure Data capture: at the user interface, the elements of a clinical statement are naturally distinct, e.g. procedure, site, protocol, time... Document structures: reports, referrals etc are also structured, including audit info, sections. For querying: data items that are queried for separately are usually separated, e.g. procedure type and body site.

© Ocean Informatics 2010 Data have many types Clinical statement data includes instances of: Text Coded terms Quantity, including units, proportions, counts, etc URIs Booleans Date, time, date/time, duration Parseable text, e.g. Units, medication timing Other more complex types

© Ocean Informatics 2010 What should be SNOMED-coded? Answers which are: textually expressible whose value range is Best modelled by as ontological description (i.e. discrete categorisation), likely to be independently queried later on. E.g. types of disease; blood types; but not general patient story (not expressible as just concepts) I.e. a subset of textual data, which are a subset of all data

© Ocean Informatics 2010 What could be SNOMED-coded? Questions which: Need to be queried on using an agreed reference coding standard. Example: ‘serum sodium’ (in context of blood film result of patient) does not need any coding to be 100% reliably queryable in openEHR environment. However, for the data to be re-usable by ANYONE later on, SNOMED-coding makes sense.

© Ocean Informatics 2010 Understanding the binding problem One thing complicates the task...SITUATION Examples: list of body positions is not the same as list of body positions pertinent to measuring BP; valid Rh blood types differs depending on whether for blood collection or transfusion; almost all scales, e.g. Apgar, GCS, Borg, Barthel etc define their own value sets for common phenomena, which differ from contextless value sets of the same / similar phenomena in naming and number of divisions.

© Ocean Informatics 2010 Value sets in scales

© Ocean Informatics 2010 Binding and openEHR

© Ocean Informatics 2010 Where is binding relevant in openEHR? openEHR Archetypes - essentially, maximum data sets, i.e. all data points for a given domain ‘recording’ concept (not its ontological ‘description’). Examples: Vitals signs: BP, Heart-rate etc Labs – very structured, well understood Physical exam – e.g. Pain, symptom....numerous! Scales, e.g. GCS, Apgar, Barthel – ordinal data Terminology need: globally invariant mappings; broad value sets e.g. ‘infectious agent’

© Ocean Informatics 2010 Where is binding needed? openEHR Templates - essentially, use-case specific content specifications; consist of data points from archetypes Examples: Discharge summary Lab report Encounter note Terminology need: define local / region-specific or specialty-specific value sets and constraints, e.g. ‘lung infection’ NOT JUST TO SNOMED CT!

© Ocean Informatics 2010 Kinds of binding - today Compositional expressions already used Direct binding to concept points Archetype local value sets  direct binding – value set specific to archetype Ref set binding for data points that correspond to reusable value sets Templates can have direct binding to SCT terms, with static value set defined in archetype or ref set reference

© Ocean Informatics 2010 Kinds of binding - future Context-dependent bindings SCT Compositional constraints SCT Composition pattern mapping?

© Ocean Informatics 2010 Type 1 binding – direct

© Ocean Informatics 2010 Direct binding WHEN: we want to associate a terminology concept with a data item that we want to be able to query Ex: systolic BP Generally an archetype path  code binding Each path acts like a post-coordination E.g. 24 hour average systolic pressure

© Ocean Informatics 2010 Which SCT concept do we pick? If we bind |systolic blood pressure| (usually means instantaneous), SNOMED-driven queries would pick up 24h av, max, min etc

© Ocean Informatics 2010 can ‘systolic’ be post-coordinated?

© Ocean Informatics 2010 |Bp| v |bp finding|

© Ocean Informatics | Average 24hour systolic blood pressure| |systolic blood pressure| OR |systolic arterial pressure| OR |Systolic blood pressure on admission| OR.... Archetype paths

© Ocean Informatics 2010 Considerations Many parts of SNOMED, excessive precoordination makes it difficult to know what to choose Basic problem: whatever binding modeller chooses, query author might choose a different concept, and the results may not be correct.

© Ocean Informatics 2010 Type 2 binding – Compositional expressions

© Ocean Informatics 2010 openEHR supports expressions = , = } =procedure:{method = excision – action, procedure site = appendix structure}

© Ocean Informatics 2010 Considerations What if information system uses pre- coordinated term? A different post- coordination? Will querying work? Relies heavily on normal form & equivalence working correctly.... and being economic to implement!

© Ocean Informatics 2010 Type 3 binding – archetype internal value set

© Ocean Informatics 2010 Internal value set WHEN: situationally dependent values, e.g. Position of patient for blood pressure measurement E.g. Set of breathing values for Apgar WHEN: poor/no matches available in SCT OR: good matches available, but no refset/subset available or desired, e.g. local use only Currently VERY COMMON in archetypes, including for scales

© Ocean Informatics 2010 Adverse reaction (mindmap view)

© Ocean Informatics 2010 Attribute view

© Ocean Informatics 2010 ADL view

© Ocean Informatics 2010

Agent category binding... Archetype termSCT candidates at0011|food| |food allergen|, |Foods| Note 149 top-level concepts containing ‘food’ at0012|animal| |animal| Note 241 top-level concepts containing ‘animal’; no ‘animal allergen’ at0013|medication|119 top-level terms containing ‘medication’ (heavily pre-coordinated), but no |medication|...! at0014|Other chemical or substance| |chemical agent| ??? 167 top-level concepts containing ‘chemical’ at0031|Non-active ingredient of medication| Nothing with ‘ingredient’ at0032|imaging dye or media| Nothing suitable at0033|environmental|Some approximate matches...

© Ocean Informatics 2010 Considerations Should we bind to SNOMED at all? Codes could be useful, since we might want to find adverse reactions caused by ‘environment’ or ‘food’ How to bind, or model? Currently, the archetype defines the value set Could bind each internal code to an SCT code Difficulties finding candidate concepts Could we use a ref set instead? This archetype has 4 internal coded value sets...what happens with 2000 archetypes?

© Ocean Informatics 2010 Type 4 binding – ref set

© Ocean Informatics 2010 Ref set binding This is for data points that correspond to context-independent domain concepts, e.g. Pain character Infectious agent The archetype or template can include an ac- code that binds to an external resource, such as a ref-set id/URI.

© Ocean Informatics 2010 Problem/diagnosis

© Ocean Informatics 2010 constraint_bindings = < [“SNOMEDCT”] = < items = < [“ac0.1”] = >

© Ocean Informatics 2010 All Infectious Agents ref set  Definition Result 

© Ocean Informatics 2010 Future approaches

© Ocean Informatics Compositional constraints WHEN: we already agree on using single post-coordinated code phrase E.g. Want to force information capture of site to include laterality, where it is defined. Can express a SNOMED constraint for this that forces laterality to exist. This capability does not yet exist in openEHR, but is very easy to add into the C_CODE_PHRASE constraint class Requires a solid definition of SNOMED constraint grammar

© Ocean Informatics Context-dependent bindings WHEN: terminology codes incorporate contextual value, e.g. patient sex, pathology challenge, time, etc E.g. Bindings to LOINC codes can depend on ‘protocol’, i.e. LOINC ‘challenge’ Some SNOMED concepts are specific to patient gender or other attributes

© Ocean Informatics 2010 E.g. Lying systolic bp The following not legal ADL today, but it could be.... /data/events[at0006|any event|]/data/items[Systolic] WHEN /data/events[at0006|any event|] /state /items[at0008|Position|] = at1003|Lying|  |Lying systolic blood pressure|

© Ocean Informatics Context-dependent bindings Would need small syntax addition in ADL to connect a condition (FOPL expression on archetype data) to a concept in terminology. Considerations for SNOMED: Excessive precoordination makes concept selection difficult; query author might select another concept

© Ocean Informatics Compositional pattern approach WHEN: there are multiple attributes in IM (some may be post-coordinated), that we want to code together rather than separately The emergence of patterns for Compositions of complex clinical statements may be useful in solving the binding problem Beginning looks promising Questions: how will this work evolve? HOW MUCH COMPOSITION IS ENOUGH?

© Ocean Informatics 2010 Clinical finding present + site + side Situation Associated finding Finding context Known present Finding-site Group Temporal context Current or specified time Subject relationship context Subject of record Laterality Clinical-finding-present-with-site-and-side (,, )

© Ocean Informatics 2010 Bleeding of left index finger present Situation Associated finding Finding context bleeding Known present Finding-site index finger structure Group Temporal context Current or specified time Subject relationship context Subject of record Laterality left Clinical-finding-present-with-site-and-side (bleeding, index finger structure, left)

© Ocean Informatics 2010 Inspection archetype

© Ocean Informatics 2010

Binding.... Archetype(s) are far more detailed (but mostly optional data points) Two data points match: /items[Clinical description] = Finding /items[Findings]/items[Location]/items[Description] = Site Mismatches: Second is 0..* - e.g. a burn could be in multiple locations  pattern only allows 1 location Archetype location assumes laterality included – needs variant pattern?

© Ocean Informatics 2010 Possible general approach Map pattern parameters to content model data points; add following to archetype: Concept_bindings = < [“SNOMEDCT”] = < patterns = < [“clinical finding”] = < name = mappings = < [ |finding|] = [ |site] = >

© Ocean Informatics 2010 Potential? Could this work generally? Could avoid full Compositional code strings in data, and instead map pattern parameters to IM data points  reduces dependence But how stable are the parameters? Will there be enough patterns?

© Ocean Informatics 2010 Summary openEHR archetype/template approach provides a semantic framework for capturing, representing and querying any data BIG ADVANTAGE: bindings are expressde in archetypes and templates, NOT THE DATA; can be added AFTER initial deployment Initial binding approaches are working, but are incomplete, and may be out of date, e.g. Internal value sets  Ref sets in the future?

© Ocean Informatics 2010 Challenges When to code.... and not How to ensure binding assumption matches query authors (there will be many of the latter) How to choose SCT concepts.... pre- coordination problem Need for SCT post-coordination expression equivalence to work Solution that handles ICDx, LOINC, local terminologies

© Ocean Informatics 2010 Questions? Resources - archetypes Other – see e.g. D Markwell’s CFH report 2009 Acknowledgements: Kent Spackman – pattern slides