Data Provenance Community Meeting
July 10th, 2014
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Agenda
Topic
General Announcements
Tiger Team report out
Use Case Discussion
Next Steps/Questions
Time Allotted
5 minutes
5 minutes
45 minutes
5 minutes
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General Announcements
Next meetings:
• HL7 DProv Joint Working Session: Monday July 14th , 2014 3:004:00pm ET
– New meeting information on wiki
• All Hands: Thursday July 17th, 2014 – 2:30-3:30 pm ET
• http://wiki.siframework.org/Data+Provenance+Initiative
• All meeting materials (including this presentation) can be found on
the Past Meetings page:
• http://wiki.siframework.org/Data+Provenance+Past+Meetings
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S&I Framework Phases outlined for Data
Provenance
Phase
Pre-Discovery
Discovery
We are Here
Implementation
Planned Activities
 Development of Initiative Synopsis
 Development of Initiative Charter
 Definition of Goals & Initiative Outcomes
 Creation/Validation of Use Cases, User Stories & Functional Requirements
 Identification of interoperability gaps, barriers, obstacles and costs
 Review of Candidate Standards
 Creation of aligned specification
 Documentation of relevant specifications and reference implementations
such as guides, design documents, etc.
 Development of testing tools and reference implementation tools
Pilot

Evaluation




Validation of aligned specifications, testing tools, and reference
implementation tools
Revision of documentation and tools
Measurement of initiative success against goals and outcomes
Identification of best practices and lessons learned from pilots for wider
scale deployment
Identification of hard and soft policy tools that could be considered for
wider scale deployments
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HL7 DProv Joint Working Session
Bob Yencha – Subject Matter Expert
Kathleen Connor – Subject Matter Expert
Ioana Singureanu – Subject Matter Expert
Neelima Chennamaraja – Subject Matter Expert
Johnathan Coleman- Initiative Coordinator
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Tiger Team Report
• Transitioned to joint HL7/S&I call
• Continued discussion on author types and
distinctions, requirements for each type
• Consensus on go-forward approach of
multiple templates, will review and collapse as
analysis dictates
Data Provenance –Use Case (Discovery)
Ahsin Azim– Use Case Lead
Presha Patel – Use Case Lead
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Proposed Use Case & Functional
Requirements Development Timeline
Week
Target Date
(2014)
1
6/12
Use Case Kick-Off & UC Process Overview
Introduce: In/Out of Scope & Assumptions
Review: In/Out of Scope & Assumptions
2
6/19
Review: In/Out of Scope & Assumptions
Introduce: Context Diagram & User Stories
Review: Context Diagram & User Stories
3
6/26
Review: Context Diagram & User Stories
Review: Continue Review of User Stories
4
7/3
Review: Finalize User Stories
Introduce: Pre/Post Conditions
Review: Pre/Post Conditions
5
7/10
Review: Finalize User Stories
Introduce: Pre/Post Conditions
Review: Pre/Post Conditions
6
7/17
Review: Pre/Post Conditions
Introduce: Activity Diagram, Functional Requirements &
Sequence Diagram
Review: Activity Diagram, Functional Requirements &
Sequence Diagram
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7/24
Review: Functional Requirements & Sequence Diagram
Introduce: Data Requirements
Review: Data Requirements
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7/31
Review: Finalize Data Requirements
Introduce: Risks & Issues
Review: Risks & Issues
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8/7
Review: Risks and Issues
Begin End-to-End Review
End-to-End Review by community
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8/14
End-to-End Comments Review & disposition
End-to-End Review ends
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8/21
Finalize End-to-End Review Comments & Begin Consensus
Begin casting consensus vote
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8/28
Consensus Vote*
Conclude consensus voting
All Hands WG Meeting Tasks
Review & Comments from Community via Wiki page
due following Tuesday by 8 P.M. Eastern
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Sections for Review
Today we will be reviewing:
1. Scenarios 3 along with
accompanying User Stories
Introduce:
1. Pre/Post Conditions
Double click the icon
to open up the Word
Document with the
sections for review
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Draft Use Case Information Interchange
per scenario
Pre-step – Creation of the data
and associated provenance
information
Data Source
(EHR, Lab,
Other)
Data Source
(EHR, Lab,
Other)
Data Source
(EHR, Lab,
Other)
Data Source
(EHR, Lab,
Other)
Scenario 1
Scenario 2
Scenario 3
Transmitter ONLY
(HIE, other systems)
End Point
(EHR)
Assembler
(EHR, HIE, other
systems)
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Scenarios
Based on the Context Diagram, we can break up our workflows into 3 different
scenarios:
1. Data Source End Point
2. Data Source Transmitter  End Point
3. Data Source Assembler End Point
Note – For each of the above, there is a pre-step associated with creation of the data and associated
provenance information
Draft Definitions:
• Data Source – Health IT System where data is created (the true source)
• Transmitter – A system that serves as a pass through connecting two or more
systems
• Assembler– A system that extracts, composes and transforms data from different
patient records
• End Point – System that receives the data
• Note: In this context, when say data we are referring to an atomic data element (a
piece of information)
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User Stories – Scenario 1
Scenario 1: Data Source End Point
User Story 1: A patient arrives at the ophthalmologists office for her annual eye exam.
The ophthalmologist conducts an eye exam and captures all of the data from that visit
in his EHR. The ophthalmologist electronically sends the information back to the
patient’s PCP (where all data in the report sent was created by the ophthalmologist).
User Story 2: A patient wishes to transmit the Summary of Care Document she
downloaded from her PCP to her Specialist. Rather than downloading and sending it
herself, she requests that the PCP transmits a copy of the document on her behalf to
her Specialist. PCP is the only author of the Summary of Care Document and also the
sender of the information to the Specialist. The Specialist understands from the
document’s provenance that it is authentic, reliable, and trustworthy.
Note: Provenance for the request made to the PCP is not in scope for this user story.
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User Stories – Scenario 2
Scenario 2: Data Source  Transmitter  End Point
User Story 1 (no alteration in exchange): While training for a marathon, a patient
fractures his foot. The patient’s PCP conducts a foot exam and captures all of the data
from that visit in his EHR. The PCP also calls in a referral for the patient to an
orthopedic specialist for further treatment. After the PCP calls in the referral, the
summary of care information is made available to the specialist, by passing through a
transmitter, before being received by the orthopedic specialist’s system. The
orthopedic specialist receives the summary of care with provenance information and
an indication that the data passed through a transmitter.
User Story 2 (modification): Drafted by community members – absorbed into Scenario
#3 User Story 2
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User Stories – Scenario 3
Scenario 3: Data Source  Assembler  End Point
Note: A community of providers have established a data use agreement that allows
them to upload data to an HIE repository. When data is sent to the repository, the
provenance information is also included.
User Story 1: A patient is rushed to the Emergency Department due to a car accident.
The physician on hand wants to obtain the patient’s summary record before
administering care. The physician queries the HIE repository and receives a summary
record from the past six months. The data received includes the provenance
information from the originating sources and also information that identifies the
assembler and the actions they have taken.
User Story 2: A patient with diabetes goes to Lab A to have his blood drawn. Lab A
sends the lab results in a standard lab format to the PCP’s EHR with provenance
information attached. Upon reviewing the lab results, the PCP decides to refer the
diabetic patient to a specialist for consultation. The PCP electronically sends the
referral to the specialist with the lab results transformed into a Referral Document
from Lab A along with relevant data originating in the PCP’s own EHR.
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User Stories – Scenario 3 (cont.)
Scenario 3: Data Source  Assembler  End Point
User Story 3: A PCP tethered PHR enables patient to download and transmit
Summary of Care records to anyone she chooses. Patient downloads full Summary
of Care Document, disaggregates the medications, problems, and vital signs in the
document and then copies these into her PHR along with medications, problems
and vital signs added previously. Patient then sends selected medications, vitals,
and problems from PHR to her Fitness Trainer in a mobile device friendly format
using different terminology for expressing vital sign measures. The Fitness Trainer
understands that the information received has been assembled by the patient and
that it was authored by various other clinical staff.
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Pre/Post Conditions
Preconditions
• Where it exists, the assembling software, is
integrated into systems such as EHRs, PHRs,
and HIEs – indicating the type of
information for a receiver to use as
provenance for calculating reliability, and
the organization or person responsible for
deploying it
• There exists an Access Control System that
allow the assembler to perform necessary
tasks for predecessor artifacts and newly
assembled artifacts
• All systems generating or consuming any
artifact are capable of persisting the
security labels received and data
segmentation based the security labels
assigned by the artifact generator, which
may be an assembler
Post Conditions
• Receiving system has incorporated
provenance information into its system
and association of the provenance
information to the source data is persisted
• Sending and receiving systems have
recorded the transactions in their security
audit records
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A look ahead: Data Provenance
Next Week
• July 17th, 2014 – All Hands Community Meeting (2:30-3:30)
– Review Pre/Post conditions
Provide your comments on the bottom of this page
http://wiki.siframework.org/Data+Provenance+Use+Cases
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Support Team and Questions
Please feel free to reach out to any member of the Data Provenance
Support Team:
•
•
•
•
Initiative Coordinator: Johnathan Coleman: jc@securityrs.com
OCPO Sponsor: Julie Chua: julie.chua@hhs.gov
OST Sponsor: Mera Choi: mera.choi@hhs.gov
Subject Matter Experts: Kathleen Conner: klc@securityrs.com and Bob
Yencha: bobyencha@maine.rr.com
• Support Team:
– Project Management: Jamie Parker: jamie.parker@esacinc.com
– Use Case Development: Presha Patel: presha.patel@accenture.com
and Ahsin Azim: ahsin.azim@accenturefederal.com
– Harmonization: Rita Torkzadeh: rtorkzadeh@jbsinternational.com
– Standards Development Support: Amanda Nash:
amanda.j.nash@accenturefederal.com
– Support: Lynette Elliott: lynette.elliott@esacinc.com and Apurva
Dharia: apurva.dharia@esacinc.com
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