Shared Health Research Information Network

buninnateΛογισμικό & κατασκευή λογ/κού

18 Νοε 2013 (πριν από 3 χρόνια και 10 μήνες)

81 εμφανίσεις


Shared Health Research Information Network

Andrew McMurry

Sr. Research Software Developer

Harvard Medical School Center for BioMedical Informatics

Children's Hospital Informatics Program at Harvard
-
MIT HST

Andrew_McMurry(@) hms.harvard.edu

https://catalyst.harvard.edu/shrine





Three axis for rapid production grade deployment:


1. POLICY

2. TECHNOLOGY

3. RESEARCH SCENARIOS

Outline of topics covered


Policy


History of success cross
-
institutional IRB agreements




Integrated health care entities




Across independent HIPAA covered entities


Technology


SHRINE Architecture


Current status and roadmap


Development Challenges and Opportunities


Intended

future

translational

research

scenarios



for Translational Research Requiring Human Specimens


for Population Health Surveillance


for Observational Studies of Genetic Variants




History of cross
-
institutional IRB agreements


Integrated

health

care

entities


Partners RPDR


i2b2 Clinical Research Chart


Everyday patient encounters


huge research cohorts


Shawn Murphy et all (wont steal their thunder here)



Centralized
Research Patient Data Repository shared among


Massachusetts General Hospital (MGH),

Brigham and Women's Hospital (BWH),

Faulkner Hospital (FH),

Spaulding Rehabilitation Hospital (SRH), and

Newton Wellesley Hospital (NWH)

History of cross
-
institutional IRB agreements

http://spin.chip.org/irb.html


Across

independent

HIPAA

covered

entities



SPIN: Federated query over
locally controlled

de
-
identified databases



Distributed

pathology database shared by





Brigham & Women's Hospital*

Beth Israel Deaconess Medical Center*

Cedars
-
Sinai Medical Center

Dana
-
Farber Cancer Institute*

Children's Hospital Boston*

Harvard Medical School*

Massachusetts General Hospital*

National Institutes of Health

National Cancer Institute

Olive View Medical Center

Regenstrief Institute

University of California at Los Angeles Medical Center

University of Pittsburgh Medical Center

VA Greater LA Healthcare System


* Participate in live “Pathology Specimen Locator” collaboration

History of cross
-
institutional IRB agreements


SHRINE

approach

:

leverage

has

worked

in

the

past


Secure IRB approvals for I2b2 local database at each site


Separate set of approvals for federated queries across sites


SHRINE

governance

principles


Hospital Autonomy: each site remains in control over all disclosures


Patient privacy: no attempts to re
-
identify patients


Non compete: no attempts to compare quality of care across sites



SHRINE Technical Architecture


Bird’s

Eye

View


Leverage local i2b2 deployments



Broadcast queries and aggregate responses across autonomous sites as
if they were “one clinical data warehouse”



There is no central database



Connect sites in a peer
-
to
-
peer or hub
-
spoke fashion




SHRINE Technical Architecture





Architecture

Technical Architecture, “cell” view

2009 deliverable

Architecture, sequence diagram view

SHRINE Technical Architecture


Current

Status




Harvard Effort


Prototype system running live

at Harvard across BIDMC, Children’s,
and Partners representing both BWH and MGH.


Uses 1 year of real patient data

Demographics and diagnosis

Under tight IRB control







SHRINE Technical Architecture


Current

Status





National Effort: west coast partners


University of Washington

UCSF

UC Davis

Recombinant


End
-
to
-
End Demo March 18
th

(3 week turn around time)







SHRINE Technical Architecture


Current

Status





National Effort: sleep study partners


Case Western Reserve Institute

University of Washington
-
Madison

Marshfield Clinic

(potentially others as well)


I2B2 users interested in using SHRINE for sleep studies





SHRINE Technical Architecture



I
2
b
2

single

site

query

demo



http://I2b2.org/software


SHRINE

multi
-
site

demo


http://cbmi
-
lab.med.harvard.edu:8443/i2b2


SHRINE Technical Architecture


Timeline

and

Roadmap



By end of 2009, Harvard SHRINE queries for aggregate counts

Demographics + ICD9 Diagnosis



Current work

Polishing demostration software for relase

Medications and Labs



Next Steps

Browseable random LDS datasets

Downloadable LDS

No plans for PHI






Development Challenges and Opportunities


1.
Grid computing makes multi
-
threading look
simple by comparison



Politically impossible to send patient data to each ‘grid’ node


Grid computing and federated queries are VERY different


Pre
-
processing can be used effectively as shown in our use cases


2.
Open

Source

strategy



1.
Writing plug
-
ins for the SHRINE network


Development Challenges and Opportunities


1.
Grid

computing

makes

multi
-
threading

look

simple

by

comparison


2.
Hosted

retreat

to

address

Open

Source

strategy


Harvard CTSA, CHIP, I2B2, Partners, DFCI, private companies


Science Commons, jQuery


Actively launching an open source portal



Test driven development with continuous integration


Release early release often




All milestones measured by what we can get IRB approved and
deployed with real clinical data


3.
Writing analysis plug
-
ins for the SHRINE network


Development Challenges and Opportunities


1.
Grid

computing

makes

multi
-
threading

look

simple

by

comparison


2.
Open

Source

strategy



1.
Writing analysis plug
-
ins for the SHRINE network


Using I2b2 Java Workbench

(Shawn Murphy et all)


Using I2b2 Web Querytool

(Griffin Weber et all)



By pre
-
processing results when required for patient privacy *


* http://www.jamia.org/cgi/content/abstract/14/4/527



SHRINE:
Intended Investigation Use Cases

For

translational

studies

requiring

human

specimens


For

Population

Health

Surveillance


For

Observational

Studies

of

Genetic

Variants*



Examples shown here reflect current projects which will use the
SHRINE infrastructure

for Translational Research Requiring Human Specimens

NCI

vision

2001
:


Vast

collections

of

human

specimens

and

relevant

clinical

data

exist

all

over

the

country,

yet

are

infrequently

shared

for

cancer

research
.



Challenges
:



How to link existing pathology systems for cancer research?


How to ensure patient privacy in accordance with HIPAA?


How to encourage hospital participation?


Availability

Millions

of

Paraffin

Embedded

Tissues

Smaller

Collections

of

Fresh

/

Frozen

Tissues


for Translational Research Requiring Human Specimens

Shared

Pathology

Informatics

Network



National prototype including HMS, UCLA, Indiana, UPMC, …


Live Production instance at HMS including 4 hospitals


Created Open Source Tools


caBIG adopted caTIES from SPIN


Influenced Markle’s Common Framework federated query


TMA construction using specimens from four sites



http://spin.chip.org

for Translational Research Requiring Human Specimens

for Translational Research Requiring Human Specimens

For Population Health Surveillance

For

translational

research

requiring

human

specimens

For

Population

Health

Surveillance



Geotemporal cancer disease incidence rates


Seasonal infectious diseases such as influenza


Disease flares such as Irritable Bowel Disease (IBD)


Other use cases exist, these are the ones under concentrated study




For Population Health Surveillance:

disease outbreaks

For Population Health Surveillance:

seasonal influenza

http://aegis.chip.org/flu

For Population Health Surveillance: pharmacovigilance

http://www.plosone.org/article/info:doi%2F10.1371%2Fjournal.pone.0000840

SHRINE: Intended Investigation Use Cases

For

translational

research

requiring

human

specimens

For

population

health

surveillance

For

Observational

Studies

of

Genetic

Variants*


High throughput
genotyping



+


High throughput
phenotyping


+


High throughput
sample acquisition

=


Orders of magnitude

Faster to obtain huge populations for genomic studies

Cheaper





*Courtesy of Zak Kohane

For observational studies of genetic variants

High

throughput

sample

acquisition


CRIMSON


High

throughput

genotyping





CRIMSON samples


SNP arrays


High

throughput

phenotyping


Natural language processing “smoking status”


Orders

of

magnitude



Faster to obtain huge populations for genomic studies


Cheaper


“disruptive technology”





*Courtesy of Zak Kohane

Lynn Bry, MD, PHD et all

Summary of topics covered


Overcome statistical noise and reproducibility with large
patient populations


Policy


History of cross
-
institutional IRB agreements


Technology


Architecture


Current status and roadmap


Development Challenges and Opportunities


Intended

future

translational

research

scenarios



for Translational Research Requiring Human Specimens


for Population Health Surveillance


for Observational Studies of Genetic Variants




Acknowledgements: Core SHRINE team


Zak

Kohane



(SHRINE

Lead

/

HMS)

Griffin

Weber



(HMS

CTO

/

bidmc)

Shawn

Murphy



(I
2
B
2

CRC

/

partners)


Dan

Nigrin



(Children’s

CIO)

Ken

Mandl


(Public

Health

Use

Cases/

CHIP

IHL)

Sussane

Churchill


(I
2
B
2

Executive

director)

Doug

Macfadden


(HMS

CBMI

IT

Director)

Matvey

Palchuck



(Ontology

Lead

/

HMS)

Andrew

McMurry


(Architect

/

HMS)


Could give an entire talk on all the collaborators, multi
-
institutional
effort. Asking forgiveness from those not listed



Acknowledgements: Core SPIN team


Zak

Kohane



(SPIN

PI

/

HMS)

Frank

Kuo



(PSL

Program

Director

/

BWH)

John

Gilbertson


(PSL

Pathologist

/

MGH)

Mark

Boguski



(PSL

Pathologist

/

BIDMC)

Antonio

Perez


(PSL

Pathologist

/

Children’s)

Mike

Banos



(PSL

Developer

/

BWH

)

Ken

Mandl




(Biosurviellance

PI/

Children’s)


Clint

Gilbert



(Biosurviellance

Dev

Lead

/

Children’s)


Greg

Polumbo


(SPIN

Developer/

HMS)


Ricardo

Delima



(SPIN

Developer

/

NCI

at

HMS)


Britt

Fitch




(SPIN

Developer

/

HMS


http
:
//spin
.
chip
.
org/community
.
html


Acknowledgements: Core I2b2 team


https
:
//www
.
i
2
b
2
.
org/about/structure
.
html

Thank You



http://catalyst.harvard.edu/shrine




Andrew_McMurry (@) hms.harvard.edu