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The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

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Page 1: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

The ORCHID project

Dr Ian Gaywood, NUH

Dr Ira Pande, NUH

Professor John Chelsom, City University London

Page 2: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

So much information……so little use

Clinical care generates enormous amounts of information which is difficult to use when caring for the individual and impossible to use for any secondary purpose

Page 3: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

The origins of ORCHID

• Better organised information has the potential to provide an enormously valuable resource but must be achieved without additional onerous burden at the clinical coalface

• The greatest impediment to extended uses of clinical records, including research, is not lack of data. It is lack of useable data

• It should be possible to organise data in ways which allow any plausible question to be answered

Page 4: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London
Page 5: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

Stratified medicine

• Treatment decisions in all but the simplest conditions increasingly rely on knowledge of the patient’s disease phenotype in several domains

• Current methods of gathering and organising data don’t place information in its correct context

• The relationships among pieces of information are at least as important as the information itself.

• It is no longer enough to simply ‘name the beast’

Page 6: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

What clinicians want ….

• A way of organising data which:

– Identifies patient phenotypes to any degree of detail

– Produces untainted cohorts

– Is multidisciplinary

– Can include or exclude individual disease characteristics

– Can include or exclude treatment details

– Records and assesses outcomes

– Can be searched in real time

– Maps to existing coding systems

Page 7: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

The ORCHID information model

• The two central tools of ORCHID are hierarchies and core data sets

• Together they provide a rich data architecture which can be applied to all data sets across all specialties

• ORCHID hierarchies cross-map to existing coding systems but overcame many of their limitations

• ORCHID hierarchies can be rapidly amended to reflect changes in knowledge and understanding without compromising the value of existing data

• Existing data sets can be embedded in ORCHID hierarchies and will inherit the richness of those structures

Page 8: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

An ORCHID hierarchy

Rheumatoid arthritis

Rheumatoid arthritis - seropositive

Rheumatoid arthritis - seronegative

Rheumatoid arthritis - NOS

Inflammatory arthritis

Autoimmune disease

Bespoke cohort

SLE, PBC etc

Psoriatic arthropathy Other conditions

of interest

Page 9: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

An ORCHID hierarchy

Page 10: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

Core data sets

• ORCHID hierarchies place individual diseases, events etc in their

correct relationships with other entities

• They do not capture the finer details of complex diseases which

say something about subtype, severity, prognosis, treatment

choices

• Core data sets capture these data items in a searchable form and

provide a very detailed patient phenotype

• Can be either static or dynamic

Page 11: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

An ORCHID Core Data Set

Page 12: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

ICD-10 and patient phenotyping

• Requires separate codes for each manifestation

• Contains misclassifications

– Adult Still’s disease as type of rheumatoid arthritis

• Contains detailed codes of no clinical value

– M05.631 Rheumatoid arthritis of right wrist with involvement of other organs and systems

• Does not reflect recent developments

Page 13: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

SNOMED and patient phenotyping

• SNOMED contains almost all of the codes required to capture diagnostic data to the required level

• But…. It also contains a very large number of redundant codes, duplications and non-existent entities

• Coding detailed phenotypes requires the use of multiple codes – usually one code for each disease manifestation

• Clinicians should agree a subset of SNOMED with careful moderation of additions and amendments

Page 14: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

Implemented using Open Health Informatics principles

• Open standards

• Open source software

• Open systems interfaces

• Open development processes

Builds upon work in the Open Health Informatics research programme at City University

Maximises the potential for reuse and wider roll out

Implementation

Page 15: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

ORCHID Architecture

• Standards based

• Ontology driven

• Clinician led

Information Architecture

Information Architecture

OntologyOntology

OWL (XML)

ISO 13606HL7 CDA

OWL (XML)

ISO 13606HL7 CDA

Information Model

Information Model

Clinical Coding

Clinical Data Sets

Clinical Coding

Clinical Data Sets

OWL (XML)

SNOMED CTICD-10LOINCdm+d

OWL (XML)

SNOMED CTICD-10LOINCdm+d

Art

efac

tIm

plem

ents

Sta

ndar

dsSystem

Configuration

System Configuration

Messages

Forms

Views

Messages

Forms

Views

HL7 v2/v3HL7 CDA

SNOMED CTXFormsXHTML

PDF

HL7 v2/v3HL7 CDA

SNOMED CTXFormsXHTML

PDF

Clinical System

Clinical System

Electronic Health Records

Electronic Health Records

XML

HL7 CDA

SNOMED CT

ISO 13606

XML

HL7 CDA

SNOMED CT

ISO 13606

Page 16: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

ORCHID Platform

• Open source

• Standards based

• Enterprise Java

• No compiled code

IntegrationInterfaces

Access Control

OrbeonMVC Framework

eXist Native XML Database

Tom

cat

Ap

plic

atio

n S

erve

r/F

ram

ewor

k

Mirt

hIn

tegr

atio

n/M

ess

agin

g E

ngin

e

Application Logic

OrbeonXForms

ProtégéOntology Services

JFreeChartVisualisation

User Interfaces Service Interfaces

RESTful Web ServicesWeb Browser

Page 17: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

Deployment of ORCHID

• A web based application with a common look and feel across specialties but specialty and disease specific forms and summaries

• Linked to Trust information systems for automatic download of demographics, laboratory data….

• Custom search engine allowing any finding within the ORCHID ontology to be used as a search term

• Can be deployed in modular form with all modules moderated for consistency allowing easy combining of modules and sharing of data among modules

• Moderated updates to take account of new knowledge, terminologies and classifications

Page 18: The ORCHID project Dr Ian Gaywood, NUH Dr Ira Pande, NUH Professor John Chelsom, City University London

Uses of ORCHID

• Routine clinical care• Automated HES / SUS reporting• Feasibility testing – research ideas, trial design• Phenotype pattern analysis• Registry data including possibility of cross-registry data

sharing• Generation of combined primary and secondary care data

sets