BTRIS: The NIH Biomedical Translational Research Information System

James J. CiminoChief, Laboratory for Informatics Development

NIH Clinical Center

National Institutes of Health Clinical Center

In-patient beds - 234

Day hospital and out-patient facilities

Active protocols - 1800

Terminated protocols - 7100

Clinical researchers - 4700

All patients are on a protocol

Clinical Data at NIH

EHR

InstituteSystem

Lab System

Personal“System”

Clinical Data at NIH

EHR

InstituteSystem

LabSystem

PersonalSystem

Clinical Data at NIH

EHR

InstituteSystem

LabSystem

PersonalSystem

BTRIS

Biomedical Translational Research Information System (BTRIS)

Database

DataStandards

(RED)

DataAccess

SecurityPreferences

CRIS, MIS

33NIAIDNIAAA

Architecture

• Data acquisition

• Database

• Controlled terminology

• User data entry

• Search tool

Data Model

• Store similar data in main tables

• Store extra data in generic tables

• Can “promote” from generic to main table

• Preserve original meanings

• Queries based on concepts of the users

Research Entities Dictionary (RED)

Research Entities Dictionary (RED)

Research Entities Dictionary (RED)

Research Entities Dictionary (RED)

BTRIS – Two Applications

BTRIS – Two Applications

BTRIS – Two Applications

BTRISData Access

What is in BTRIS?• Clinical Center MIS (1976-2004) and CRIS (2004-)

• Demographics• Vital signs• Laboratory results• Medications (orders and administration)• Problems and diagnoses• Reports (admission, progress, discharge,

radiology, cardiology, PFTs)• National Institute of Allergy and Infectious Disease

• Medication lists• Laboratory results• Problems

• National Institute of Alcohol Abuse and Alcoholism• Clinical assessments

BTRIS Data Growth

Millions

of

Rows

BTRIS Data AccessReports

• IRB Inclusion• CBC Panel• Chem 20• Microbiology• Demographics• Individual Lab• Lab Panels• Medications• Vital Signs• Diagnoses/Problems

Lists• Individual Lab Test• Lab Panels• Medications• Subjects• Vital Signs

33 years of Data

0

50

100

150

200

250

300

350

400

6/1/

1976

6/1/

1978

6/1/

1980

6/1/

1982

6/1/

1984

6/1/

1986

6/1/

1988

6/1/

1990

6/1/

1992

6/1/

1994

6/1/

1996

6/1/

1998

6/1/

2000

6/1/

2002

6/1/

2004

6/1/

2006

6/1/

2008

Albumin (g/dL)

Alkaline Phosphatase (U/L)

ALT/GPT (U/L)

Lactate Dehydrogenase (U/L)

0

200

400

600

800

Aug-09

Sep-0

9

Oct-0

9

Nov-09

Dec-0

9

Jan-1

0

Feb-1

0

Mar

-10

Apr-10

BTRIS Reports per Week

BTRIS Users and Subjects

115 BTRIS Users thru March 2010

130 Non-BTRIS PIs+ =

245 BTRIS Beneficiaries

619 UniqueProtocols

80,073AttributedSubjects

(of 395,005attributions,or 20.27%)

Subject-Protocol Attributions

• 395,005 total attributions

• 126,533 verified by Medical Records

• 44,142 verified by IC systems

• 1,966 verified by users

• 363 unverified subjects “not on protocol”

• 236 verified subjects “not on protocol”

Re-using Data in De-Identified Form

• Look for unexpected correlations

• Pose hypothetical research questions

• Determine potential subject sample sizes

• Find potential collaborators

Access to De-identified Data

• De-identified data available to NIH intramural research community

• NIH researchers wanted access policy to ensure protection of intellectual property and first rights to publication

• Resolved through three means:– Association of data with an NIH PI– Status of protocol– Age of data

d) Active Protocol

Access to De-identified (Coded) Data

a) Data Outside Any Protocol

Period

b) Terminated Protocol – PI Gone

c) Terminated Protocol –

PI at NIH

d) Active Protocol

Data Available for De-Identified Reports

Total Subjects: 430,196

Not attributed to any protocol: 249,128

Attributed to Protocol: 181,068

Terminated > 5 yrs: 36,467

Data Available for De-Identified Reports

Available Subjects – 285,595 (66.4%)

OHSR Exemption Process

• Required for all de-identified data queries

• Automated process replaces OHSR “Form 1” paper process for exemption

Serum Albumin Trends

Using BTRIS For Clinical ResearchIdentify

Potential Subjects

IdentifyPotential Controls

Include Cases with Pathology Specimens

SubjectCases

ControlCases

Assign Case Numbers

Potential SubjectCases

Potential ControlCases

Obtain Clinical Data

Deidentified SubjectCases with Phenomic and

Genomic Data

Deidentified ControlsCases with Phenomic and

Genomic Data

SpecimensObtained

from Pathology

Department

Send Case Numbers and MRNs to Pathology

SNPs SequencedDeidentify Cases

De-identifiedText Reports

and Other Data

Merging Records Manual Scrubbing

De-identifiedText Reports

Obtain Clinical Data

DeidentifiedSubject

Data

IdentifiedText

Reports

Perform Query in Identified

Form

Trusted Broker

Re-using BTRIS For Clinical Research

Office of Human Subjects Research

Develop Deidentified

Query

Investigator

Informatics Challenges

• Understanding data sources• Finding the right balance for unified data model• Modeling in the Research Entities Dictionary• Organizing the Research Entities Dictionary• Understanding researchers’ information needs• User interface (including Cognos customization)• Keeping up with report requests• Integration into multiple research workflows• Access to deidentified data• New policies on contribution and use

So What?• Easier access to protocol data from EHR• Easier access to archived data• Protocol data integrated from multiple sources• User empowerment• Concept-based queries• Data feeds to institute systems• Data model flexible but not too flexible• Rapid development timeline (under budget)• User adoption can be considered good• High user satisfaction• Success with NIH policy• Success with data sharing

Future Directions

• Finish historical data• Add more institutes and centers

CRIS, MIS

Radiology Images

Other CC Sources

33NIAIDNIAAA

NINDS

NIDDK

NINR

N HG

RI

NHLBI

NCI

Future Directions

• Images• “-omic” data• Specimen identification and location• New reports and analytic tools• Clinical Trials.gov reporting• Beyond NIH

• Finish historical data• Add more institutes and centers

btris.nih.gov

btris.nih.gov