Trust in Regional Exchange Supports Patient-Centered Research

April 16, 2015

Thomas F. Check, President & CEO

Healthix, Inc.

Lorraine Fernandes, RHIA, Global Ambassador, Information Management

IBM

DISCLAIMER: The views and opinions expressed in this presentation are those of the author and do not necessarily represent official policy or position of HIMSS.

Thomas F. Check, MA, No real or apparent conflicts of interest to report

Lorraine M. Fernandes, RHIAVery limited IBM shareholder

© HIMSS 2015

Conflict of Interest

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1. Explain how HIE patient-matching technology supports the innovative research infrastructure of NYC-CDRN.

2. Identify privacy issues addressed by HIE participants including how the NYC-CDRN infrastructure supports patient privacy.

3. Describe how consumer, patient consent and other concerns of community stakeholders are addressed.

4. Discuss the value of re-using data from Healthix and the Bronx RHIO including costs and technology infrastructure.

5. Illustrate the information data model’s use within NYC-CDRN and its connection to the PCORnet.

Learning Objectives

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Savings

Re-purpose, re-use data and the underlying

HIE infrastructure; potential to expedite

research dissemination and save costs

http://www.himss.org/ValueSuite

Benefits Realized from Health IT in Patient-Centered Research: STEPS

Satisfaction

Multi-stakeholder collaborative

approach drives governance,

consensus building and trust and

save costs

Treatment/Clinical

Transform research to generate

and disseminate results more

quickly to inform clinical

practice and benefit patients

Electronic Information/Data

Build on millions of electronic patient

records; innovate solutions to link

patient records across stakeholders

Prevention & Patient Education

Consumer centricity is core

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• Healthix: Enabling Secure Access to Millions of Patient Records

• New York City Clinical Data Research Network (NYC-CDRN)

• Creating a Model of Trust

• Technical Approach

• Progress to Date

• Closing and Key Takeaways

Agenda

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Healthix is a Regional Health Information Organization (RHIO) regulated by the New York State Department of Healthto facilitate the secure exchange of patient information among disparate providers to

• support care coordination

• improve clinical outcomes

• promote efficiency

• reduce healthcare costs

Healthix: Enabling Secure Access to Millions of Patient Records

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Healthix Holds Records of +10 Million People from Greater New York Area

2 Million Patients Have Given Consent to at Least One Provider

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150+ healthcare organizations with 550+ facilities, across the continuum of

care

Healthix Services and Available Data

• Clinical Event Notifications

• Consent Management

• Consulting Services

• EHR Integration and Single Sign-on

• Patient Record Look-up

• Reporting and Analytics

• Secure Messaging - Direct

• Allergies• Demographics• Diagnoses / Problem Lists• Encounters• Insurance• Lab Results• Medications• Plans of Care• Radiology Reports• Summary Documents

Healthix Services and Available Data

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Bronx RHIO

Creates Universal Interoperability of Bronx Healthcare Information:

patients’ medical records follow them

throughout their care in the Bronx

Participants Include:

hospitals, health systems, ambulatory care centers, individual physician offices,

long-term care, home care, and community organizations

Progress Thus Far:

Consents collected for 865,000 Data on 2.4 million patients

650,000 patients seen at multiple sites Users accessing data +2,600

70+ Members 200+ Bronx Practices

Supporting population health improvement and delivery system reform

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Operates a Secure Clinical HIE:

Offers registration alerts, clinical results delivery, Direct messaging, provider

portal, and advanced analytics

New York State’s HIE Landscape

RHIOs in New York State are adopting common standards to exchange data in the State Health Information Network of New York(SHIN-NY)

New York State’s HIE Landscape

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Dec. 2013: Patient-Centered Outcomes Research Institute (PCORI) awarded contract to Weill Cornell Medical College for NYC-CDRN to:

New York City Clinical Data Research Network (NYC-CDRN)

Build infrastructure to perform comparative effectiveness research

Facilitate patient- centered research that can be linked to a national network

Collaborate nationally with 10 other CDRNS to develop best practices and support joint studies

Perform two observational studies on diabetes and cystic fibrosis, May 2014 – October 2015 (contract period)

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Create an accessible, sustainable, scalable clinical data network to facilitate: patient-centered

research; a national research network; and a learning healthcare system

NYC-CDRN MISSION

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Organization Type NYC-CDRN Members

Health System • Weill Cornell Medical College• Columbia University College of Physicians and Surgeons• NewYork-Presbyterian Hospital• Montefiore Medical Center and Albert Einstein School of Medicine• Mount Sinai Health System and Icahn School of Medicine• NYU Langone Medical Center and School of Medicine• Clinical Directors Network (of FQHCs)

Research Infrastructure • Biomedical Research Alliance of New York (BRANY)• New York Genome Center (NYGC)• Cornell NYC Tech Campus

Health Information Exchange

• Healthix • Bronx RHIO

Other Stakeholders • American Diabetes Association• Center for Medical Consumers• Consumer Reports• Cystic Fibrosis Foundation• New York Academy of Medicine• NYS Department of Health• Rockefeller University

NYC-CDRN Research Partners

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Goals that Drive NYC-CDRN’s Approach

Create infrastructure for strong

governance and business operations

Ensure accountability

and coordination

Develop overarching

vision

Establish a legal foundation that

protects privacy

Build technical

infrastructure

Embed research into

practice

Engage patients and

clinicians

Goals that Drive NYC-CDRN’s Approach

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Prioritizing collaboration, efficiency, patient and clinician centeredness, NYC-CDRN turned to Healthix and the Bronx RHIO as key resources.

With most of the region’s health care providers connected to them, Healthix and the Bronx RHIO met technical and privacy challenges.

Health Information Exchange as Key Enabler of Patient-Centered Research

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It is mutual trust, even more than mutual interest that holds human associations together.

Creating a Model of Trust

- H. L. Mencken

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Health Information Exchange as a Solution

Master Patient Index (MPI) of Healthix (IBM-Initiate) and Bronx RHIO (Optum-Axolotl) link the patient’s records from multiple providers into a de-identified data set for research while protecting patient identities

Health Information Exchange as a Solution

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NYGC performs patient-centered research using the patient record aggregated from providers

NYC-CDRN participants then sends fully de-identified data to NYGC

Identifying and Minimizing Risk

• Agree on process to de-identifydata that would be sent to a trusted partner (NYGC)

• Frame the relationship among all parties and stakeholders

• Establish governance structure to oversee challenging issues

• Create transparency, especially for consumers and clinicians

Identifying and Minimizing Risk

In addition to executing Business Associate Agreements, collaboration was needed to:

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Considerations

Existing Healthix Agreements with its Participants:

• Allow data use primarily for treatment and care coordination.

• Specify guidelines to share data for research.

Recognized need to:

• Build HIE usage into IRB research approval process• Establish a HIPAA privacy review board

• Draft agreements or amendments between and among Participants, stakeholders and trusted agents

• Establish parameters for handling research data through HIE

Considerations

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Collaboration and Consensus

Through rigorous governance and collaborative process, NYC-CDRN, RHIOs and research partners:

• Amended Healthix Participant Agreements to authorize using data for research in NYC-CDRN

• Designated Biomedical Research Alliance of New York (BRANY) IRB as HIPAA reviewer, and obtained IRB approval

• Identified NYGC as trusted agent to hold data and house overall technical infrastructure

• Executed agreements, contracts and sub-contracts

‒ between NYGC and RHIOs documenting processes for transmitting and protecting data

‒ between NYGC and NYC-CDRN participants

‒ with Weill Cornell (lead investigator and primary contractor with PCORI)

Collaboration and Consensus

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Healthix and the Bronx RHIO Collaborate to:

• Reconcile patient identities across their Participants

• De-identify data by:

– mapping patient identities to Proxy IDs

– shifting patient dates (of birth, encounters and death)

Technical Approaches

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Matching Proxy IDsTechnical Approach

MSMC

NYULMC

NYP

William H. Ryan

Montefiore / Einstein

Columbia Doctors

Charles B. Wang

CHN

Lutheran

Patient MRNs, Demographic and Clinical data &MRN/Proxy ID Crosswalk tables

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Healthix

MPI - InfoSphere

MDM

Bronx RHIO (BRIC)

Separate

instance of

Healthix MPI

Matching Proxy IDsTechnical Approach

Patient MRNs, Demographic and Clinical data &MRN/Proxy ID Crosswalk tables

File of Matched Proxy IDs that identify same patient

New York

Genome

Center(NYGC)

MSMC

NYULMC

NYP

William H. Ryan

Healthix

MPI - InfoSphere

MDM

Montefiore / Einstein

Columbia Doctors

Charles B. Wang

CHN

Lutheran

Separate

instance of

Healthix MPI

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Bronx RHIO (BRIC)

Matching Proxy IDsTechnical Approach

Patient MRNs, Demographic and Clinical data &MRN/Proxy ID Crosswalk tablesFile of Matched Proxy IDs that identify same patient

Date shift values

Separate

instance of

Healthix MPI

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MSMC

NYULMC

NYP

William H. Ryan

Montefiore / Einstein

Columbia Doctors

Charles B. Wang

CHN

Lutheran

Matching Proxy IDsMatching Proxy IDsTechnical Approach

Date shift values

MSMC Research database

NYULMCResearch database

NYP Research database

Charles B. Wang Research database

Montefiore / EinsteinResearch database

Columbia Docs Research database

Weill Cornell Research database

William H. Ryan Research database

CHN Research database

Lutheran Research database

Clinical data with Proxy IDs and dates shifted

New York

Genome

Center(NYGC)

Patient MRNs, Demographic and Clinical data &MRN/Proxy ID Crosswalk tablesFile of Matched Proxy IDs that identify same patient

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New York

Genome

Center(NYGC)

Healthix

MPI - InfoSphere

MDM

Matching Proxy IDsTechnical Approach

MSMC

NYULMC

NYP

William H. Ryan

Montefiore / Einstein

Columbia Doctors

Charles B. Wang

CHN

LutheranBronx RHIO (BRIC)

Separate

instance of

Healthix MPI

MSMC Research database

NYULMCResearch database

NYP Research database

Charles B. Wang Research database

Montefiore / EinsteinResearch database

Columbia Docs Research database

Weill Cornell Research database

William H. Ryan Research database

CHN Research database

Lutheran Research database

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Patient Healthix: NYULMC Proxy ID

Healthix:MSMC Proxy ID

Bronx RHIO:Montefiore / Einstein Proxy ID

1 123 456 555

2 789 666

3 987 654

File of matched Proxy IDs indicates which Proxy IDs of Healthix and Bronx RHIO participants are linked by IBM’s Initiate EMPI as the same person, but does not contain MRNs, demographic or clinical data:

Matching Proxy IDsMatching Proxy IDs

Healthix sends this table to NYGC, NOT to the Participants

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Date Shifting to De-identify Data

• HIPAA de-identification requires patient identity not to be deducible by dates

of birth, encounters and death.

• Healthix assigns a random number from 1 to 365 (Date Shift Value) to each

person in the Consolidated Proxy ID File

• Proxy IDs from multiple facilities that represent

the same person receive the same Date Shift Value

• Healthix sends each facility a table indicating the

Date Shift Value for each Proxy ID of that facility

• Facility applies this Date Shift Value to all

records it sends NYGC for that patient

Date Shifting to De-identify Data

Healthix sends this table to Participants, NOT to the NYGC

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Additional Elements

• Confidentiality Code

• Creation Date

• Death Indicator

• Drivers License

• Drivers License State

• Facility

• Insurance Numbers, additional

• Mother’s Birth Name

• Race

• Surviving MRNNote--Does NOT include all data elements

Select data elements that support patient linking for Healthix and NYC CDRN

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Algorithm Considers

• Name

• Address

• Birthday

• Day Phone

• Night Phone

• Facility EID

• Gender

• Insurance Number

• SSN

Matching Algorithm Considerations

Fuzzy matches are scored against probabilistic weights based

on value frequencies in the Healthix and Bronx data

Phonetics

Mohammed vs.Mahmoud

Synonyms

Andrew = AndyGeorge = Jorge

1st = FirstNYC = Queens

Abbreviations

IBM = International Business Machines

Rd = Road

Concatenation

Van de Velde =Vandevelde

Misalignment

Kim Jung-il =Kim il Jung

Edit Distance

867-5309 ~ 876-5309

Tokenization

Ibrahim Mohamed =Mohamed Ibrahim

Date Similarity

01/01/1973 ~01/02/1973

Proximity

Geocodes and great-circle

distance

Noise Words

IBM Co. =IBM

Matching Algorithm Considerations

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Match Rates Across NYC CDRN

Health System

A B C D E F

A 2,624 41 65 121 44 22

B 41 404 36 327 42 20

C 65 36 1,049 77 94 54

D 121 327 77 1,249 95 43

E 44 42 94 95 1,147 64

F 22 20 54 43 64 560

O V E R L A P C O U N T (In Thousands)

Match Rates Across NYC-CDRN

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Progress to Date

• Created a separate instance of Healthix MPI; added records from Bronx RHIO; created file of matched Proxy IDs for NYGC; created date shift values for Participants

• Currently working to amplify and refresh the data feeds to NYGC

• All research committees, NYC-CDRN and national, are robust, active and cross pollinating

• Health systems that were not already participating in Healthix are becoming members

• Existing members are looking at the capabilities of HIE with “fresh eyes,” buying into HIE and how it can support research use cases

Progress to Date

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Privacy Issues Are Manageable• De-identification requirements met with Proxy IDs and date shifting• A trust agent may be key to ensuring privacy, stakeholder concerns• Research and technology can be the bond for trust today and tomorrow

HIE Linkages Inform Research• Existing HIE linkages can be re-purposed, saving time and money• Research use case may require further adjustments to technology• HIE participation can be expanded, yet isolated

Trust and Collaboration Can Flourish with Innovation• Use a flexible technology model that can be re-used and adapted• National initiatives can ignite collaboration and innovation

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Closing/Key Takeaways

Questions

Thomas F. Check, President and CEOHealthix, Inc.40 Worth StreetNew York, NY 10013tcheck@healthix.org / 646-432-3672

Lorraine M. Fernandes, RHIA, Global HC Industry AmbassadorIBM Information Managementlfernand@us.ibm.com

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