phuse 2010 conference - cdisc and industry standards discussion club - tuesday, october 19th 2010...

PhUSE 2010 Conference - CDISC and Industry Standards Discussion Club - Tuesday, October 19th 2010

Empowering Translational ResearchEmpowering Translational Researchthroughthrough

Distributed Collaborative ComputingDistributed Collaborative Computing

Dr. Ed ConleyDr. Ed Conley

Distributed Collaborative Computing Research1 &Severnside Translational Research Alliance

Schools of Computer Science1 and Medicine2

Cardiff and Bristol Universities, UK

[email protected]


Sintero Server is a prototype distributed clinical computing platform funded by Wellcome Trust Translational Programme

It tries to Simplify INTEROperability in large-scale healthcare & clinical research applications

It aims to be highly cost-efficient with low ‘footprint’to ‘defragment’ collaborative processes

It is based on an internationalised software “stack” intended to work the same way everywhere


Sintero is an internationally-distributed collaborative computing platform. For assisting translation, it is targeted equally into two areas:

1. Affordable healthcare initiatives - providing new “low-cost and scalable” options for open source clinical data “node” infrastructures and patient-centred service hosting. For example, “commodity interoperability” solutions that are portable. Through internationalised software “stack” implementations they work the same way everywhere.

2. Standard computational workflows for translational research – i.e. chained blocks of standard executable server code harmonising multi-site (especially international) clinical research collaborations. These absolutely depend on assisting the collaboration “nodes” to use single semantic/syntax standards. Sintero is designed to implement/deploy any externally defined semantic model and work with multiple EHR’s and EDC systems.

Distributed Collaborative Computing

Low-costreplicable‘STACK’

~creates‘LOCAL’

TRUSTEDSERVER‘NODES’

e.g. Collaboration Ae.g. Collaboration B

Trusted nodes are portable:

and reconfigurable:

…and scalable:LOCAL DATA STORAGE NODE


‘Nodes’ Can Improve Interoperability

Sets InternalINTER-NODE

TRANSACTIONSEMANTICS

External (global)SEMANTIC

REFERENCESTANDARD(S)

…to deploy at scale:


AIM is a COMMODITY solution for

(1) AFFORDABLE HEALTHCARE I.T.

OUTCOMESOUTCOMESMONITORINMONITORIN

GG& RISK& RISK

ANALYSISANALYSIS

DIRECTDIRECTPATIENTPATIENT

CARECARE

PATIENTPATIENTPATHPATH

e.g. @homee.g. @home& mobile& mobile

Monitor timelineMonitor timelineINTERVENTIONSINTERVENTIONS

Centred onCentred onPATIENTPATIENT

PATIENT IDENTIFIABLE DATA USES

CLINICALCLINICALRESEARCHRESEARCH

distributeddistributedcollaborationscollaborations

AUDITAUDIT&&

GOVERNANCEGOVERNANCE

e2ee2eQUALITYQUALITY

e.g. ‘lean e.g. ‘lean clinics’clinics’

VALIDATEVALIDATECOHORTCOHORT

OUTCOMEOUTCOMESS

e.g. for e.g. for efficacyefficacy

& toxicity& toxicity

Modelling & Modelling & DISCOVERYDISCOVERY

PATIENT NON-IDENTIFIABLE DATA USES

ComparativeComparativePERFORMANCPERFORMANC

EE

SemanticSemanticAGGREGATIONAGGREGATION

(2) EHR LINKED-OUTCOMES (PSEUDONYMISED) STUDIES

CONTINUOUS WITH

e.g. TIMELINEe.g. TIMELINEMONITORINGMONITORING


etc.

COMMUNITY

SOCIALCARE

INDEPENDENTCLINIC

GYM

HOSPITAL‘P

atie

nt p

ath’

MOBILE

Mobile hubs

WORK ID data PPBIND

ID data PPBIND

ID data PPBIND

ID data PPBIND

ID data PPBIND

ID data PPBIND ID data PP

BIND

HOME

DEVICES

HL7 CONSENT DIRECTIVE – PRIVACY POLICIESHL7 CONSENT DIRECTIVE – PRIVACY POLICIES

‘Dat

a P

ath

’

+ IDdata

BINDDATA

Devicedata

Patient consentto Privacy Policy

Home hubs

Consistent Timeline Monitoring(incl. data format, HL7 Consent Directive, CDA release 2, CDISC ODM)


Sintero Node Interoperability Layers

Replicated in each server node

L1: data documents (CDA, ODM)

L2: Internationalised XDS

ID’s’, timestamps, ID’s’, timestamps, codes/values, consentcodes/values, consent

Stream Inferable DataStream Inferable DataDocuments Documents RDBMSRDBMS

L3: Semantic Aggregation

L4: Executable Code WorkflowsRe-stream Aggrg. DataRe-stream Aggrg. Data

RBAC Boolean queriesRBAC Boolean queries

INPUTSINPUTS

OUTPUTS


STUDYFEASIBILITY

STUDYFEASIBILITY

LOCAL Aggregation Layer 3

(EHR-linked-pseudonymised)

BENEFIT: Attribute-level subject recruitment

SECOND STREAMSECOND STREAM

= Limited complexity database

STREAMINFERABLEDATA L2-L3

STREAMINFERABLEDATA L2-L3

Globally consistent syntax (Boolean)Inclusion, Exclusion on Code/Value

Globally consistent syntax (Boolean)Inclusion, Exclusion on Code/Value

LAYER 1 VERBOSEDATA DOCUMENTS

CDA / ODMON TIMELINE

L2


BENEFIT: EHR outcomes modelling

Compute Y = function (X) Rank variables

Rank variables

nodeID’s,PSID’s,codes,values,timestamps

TimeXDS XDS

Longitudinalentries

MEASURES= X-variables

XDS

OUTCOME = Y-variable

X YX

Model for Outcome Y


Summary

DCC Group

2011-Q1 2011-Q22010-Q4TIMELINE

Firstrelease

NEXT STEPS• Community of practice funding for internationally-distributed computing• esp. Pharma programmers who analyse results of clinical trials• Regulatory developments (end-to-end)• Information governance for research networks (pseudonymisation)

Funded by

Acknowledgements - Sintero Team

STEERING & ADVISORY GROUP

Charlie McCayHL7 UK

Dave Iberson-HurstCDISC

Prof. FoxCancer ResearchUK + Infermed

Graham Kennedy NWIS

Malcolm NewburyIHE-UK

Funded by

THANKS to PhUSE!THANKS to PhUSE!

Dr. Ed ConleyDr. Ed Conley

Distributed Collaborative Computing Research1 &Severnside Translational Research Alliance

Schools of Computer Science1 and Medicine2

Cardiff and Bristol Universities, UK

[email protected]

phuse 2010 conference - cdisc and industry standards discussion club - tuesday, october 19th 2010...

Documents

conference cdisc

stack slide

clinical computing platform

collaborative processes

collaboration nodes

local data storage node

sintero server

local trusted server