The Challenges of Bridging HIS/EMRs and Research Information Systems

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James J. CiminoChief, laboratory for Informatics Development

NIH Clinical CenterBethesda, Maryland

Bridging Patient Care and Research at NIH

• The NIH Clinical Center and research

• The Biomedical Translational Research Information System (BTRIS)

• Technical Issues

• Policy Issues

The NIH Clinical Center

The Clinical Research Information System (CRIS)

• Patient data stored in EHR (Eclipsys)

• Need to extract individual data for analysis

• Need cross-patient queries for additional analysis

• Data may require transformation:– De-identification and Re-identification– Indexing– Aggregation by time– Abstraction by classification

What is BTRIS?• Biomedical data

– Research data collected using clinical information systems

– Clinical data collected using clinical information systems

– Research data from research information systems– Non-human data

• Reuse of data to support translational research

• Hence: Biomedical Translational Research Information System

The National Institutes of Health

O n t o l o g y

Data Acquisition ProcessesCoding Indexing De-Identifying Permission Setting

BTRISData Repository

Data Retrieval FunctionsAuthorization Subject-Oriented Cross-Subject Re-Identification NLP

Data Analysis ToolsSubject Recruitment Hypothesis Generation Hypothesis Testing

Technical Issues

• Data sources

• Data model integration

• Queries that are:– Cross-patient– Cross-protocol– Cross-source– Concept oriented

Data Sources

• Order entry system

• Ancillary systems

• Archived clinical data

• Institute and Center (IC) systems

• Individual researchers’ systems

• Notebooks

Data Model Integration

• Events and details

• Entity-relation vs entity-attribute-value

• Denormalization

Research Entities Dictionary (RED)

• Apelon’s Terminology Development Editor

• NCI/caBIG Thesaurus

• Apelon’s Terminology Development Editor

• NCI/caBIG Thesaurus

Research Entities Dictionary

• Content

• Organization

Access Policies

• Privacy Act, not HIPAA

• Policy Working Group

• Intellectual property vs. public domain

• Identifiers

• Unlinked, coded data

BTRIS Data Storage Policy

InactiveProtocols

ActiveProtocols

BTRIS Data Use Policy

InactiveProtocols

ActiveProtocols

PIs/AIs

InactiveProtocols

ActiveProtocols

PIs/AIsBlockedBy PI

Identifiers Coded Data

ActiveProtocols

InactiveProtocols

BlockedBy PI

PIs/AIs

Identifiers CodedResults

CodedEvents

ActiveProtocols

InactiveProtocols

Identifiers CodedResults

CodedEvents

ActiveProtocols

InactiveProtocols

PIOnly

RestrictedBy PI

SharableThrough PI

Identifiers

ActiveProtocols

InactiveProtocols

UnencumberedBy PI

BTRIS Data Use PolicyCodedResults

CodedEvents

PIOnly

RestrictedBy PI

SharableThrough PI

NoAccess

Identifiers

ActiveProtocols

InactiveProtocols

Sharablethrough PI

UnencumberedBy PI

CodedEvents

PIOnly

RestrictedBy PI

SharableThrough PI

NoAccess

Identifiers

ActiveProtocols

InactiveProtocols

Sharablethrough PI

UnencumberedBy PI

CodedEvents

PIOnly

RestrictedBy PI

SharableThrough PI

NoAccess

Identifiers

ActiveProtocols

InactiveProtocols

Sharablethrough PI

UnencumberedBy PI

CodedEvents

PIOnly

RestrictedBy PI

SharableThrough PI

NoAccess

PIs/AIs

Identifiers

ActiveProtocols

InactiveProtocols

Sharablethrough PI

UnencumberedBy PI

CodedEvents

PIOnly

RestrictedBy PI

SharableThrough PI

NoAccess

OtherResearchers

BTRIS Policy WG: Data Inclusion

1. All Data from CC (including historical archives) will be included

2. Data from institutes, centers, laboratories and investigators will be included on a voluntary basis

3. Other intramural data to be included as per NIH policy

BTRIS Policy WG: Data Access1. Investigators will have access to data in

their active protocols as per current policies and practices

2. All NIH personnel will have access to de-identified data for research purposes

3. Investigators will retain on-going rights to some data

BTRIS in the Research Process

Recruitment

PatientAccrual

Publications

IRBApproval

Write Protocol

HypothesisGeneration

Reporting

Data GatheringAnd Analysis

B RISB RIS

BTRIS Will:

• Be the preferred system to analyze NIH clinical and non-clinical data

• Aggregate and standardize disparate and isolated data sets

• Automate and streamline processes that are traditionally manual and cumbersome

• Prioritize data sources and functionality based on needs of user community

Remaining Challenges

• Can we scale up to handle all sources:– Data– Terminologies

• Incentive for researchers to contribute data

• Access to “involuntarily contributed” data

The Challenges of Bridging HIS/EMRs and Research Information Systems

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