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BTRIS: The NIH Biomedical Translational Research Information System James J. Cimino Chief, Laboratory for Informatics Development NIH Clinical Center
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BTRIS: The NIH Biomedical Translational Research Information System

Jan 14, 2016

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BTRIS: The NIH Biomedical Translational Research Information System. James J. Cimino Chief, 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. - PowerPoint PPT Presentation
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Page 1: BTRIS: The NIH Biomedical Translational Research Information System

BTRIS: The NIH Biomedical Translational Research Information System

James J. CiminoChief, Laboratory for Informatics Development

NIH Clinical Center

Page 2: BTRIS: The NIH Biomedical Translational Research Information System

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

Page 3: BTRIS: The NIH Biomedical Translational Research Information System

Clinical Data at NIH

EHR

InstituteSystem

Lab System

Personal“System”

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Clinical Data at NIH

EHR

InstituteSystem

LabSystem

PersonalSystem

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Clinical Data at NIH

EHR

InstituteSystem

LabSystem

PersonalSystem

BTRIS

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Biomedical Translational Research Information System (BTRIS)

Database

DataStandards

(RED)

DataAccess

SecurityPreferences

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Architecture Overview• Generic data model in SQL-Server (Microsoft)

• Data acquisition: HL7, ODBC, batch

• Standard extraction-translation-loading

• Encoding with Research Entities Dictionary (RED)

• Terminology Development Editor (Apelon)

• National Cancer Institute extensions to TDE

• Cognos (IBM) business intelligence tool

• Javascript extensions to Cognos

• Home-grown system for user data entry

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CRIS, MIS

33NIAIDNIAAA

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BTRIS – Two Applications

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BTRIS – Two Applications

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BTRIS – Two Applications

BTRISData Access

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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

Page 18: BTRIS: The NIH Biomedical Translational Research Information System

BTRIS Data Growth

Millions

of

Rows

Page 19: BTRIS: The NIH Biomedical Translational Research Information System

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

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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)

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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

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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%)

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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”

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Re-using Data in De-Identified Form

• Look for unexpected correlations

• Pose hypothetical research questions

• Determine potential subject sample sizes

• Find potential collaborators

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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

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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

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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

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Data Available for De-Identified Reports

Available Subjects – 285,595 (66.4%)

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OHSR Exemption Process

• Required for all de-identified data queries

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

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Serum Albumin Trends

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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 SubjectCases with Phenomic and

Genomic Data

SpecimensObtained

from Pathology

Department

Send Case Numbers and MRNs to Pathology

SNPs SequencedDeidentify Cases

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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

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Capabilities of Data Model

• Storage of like data in meaningful model

• Preservation of original data details

• Can “promote” commonalities to main table

• Preservation of original meanings

• Queries based on users’ aggregations

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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

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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

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Future Directions

• Finish historical data• Add more institutes and centers

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CRIS, MIS

Radiology Images

Other CC Sources

33NIAIDNIAAA

NINDS

NIDDK

NINR

N HG

RI

NHLBI

NCI

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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

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btris.nih.gov

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btris.nih.gov