1. Data Provenance Community Meeting September 11 th, 2014

2. Meeting Etiquette Click on the “chat” bubble at the top of the meeting window to send a chat. 2 Please mute your phone when you are not speaking to prevent background noise. – All meetings are recorded. Please do not put your phone on hold. – Hang up and dial back in to prevent hold music. Please announce your name before speaking Use the “Chat” feature to ask questions or share comments. – Send chats to “All Participants” so they can be addressed publicly in the chat, or discussed in the meeting (as appropriate).

3. Agenda Topic Time Allotted General Announcements3 minutes Data Provenance Initiative Overview10 minutes Use Case Discussion45 minutes Next Steps/Questions2 minutes 3

4. Thursday, September 18 th meeting is cancelled due to HL7 Meetings Next meeting: Extended All Hands: Thursday September 25th, 2014 – 2:30- 4:00 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 General Announcements 4

5. Review your status 5

6. S&I Framework Phases outlined for Data Provenance PhasePlanned Activities Pre-Discovery  Development of Initiative Synopsis  Development of Initiative Charter  Definition of Goals & Initiative Outcomes Discovery  Creation/Validation of Use Cases, User Stories & Functional Requirements  Identification of interoperability gaps, barriers, obstacles and costs  Review of Candidate Standards Implementation  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  Validation of aligned specifications, testing tools, and reference implementation tools  Revision of documentation and tools Evaluation  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 We are Here 6

7. S&I Data Provenance Initiative Presentation to the HITSC on Data Provenance September 10, 2014

8. Why do we need data provenance standards? Health care providers need confidence in the authenticity and integrity of health data they review/access/receive. Ever expanding role for individuals to contribute data toward their health and care through the use of health IT. Trends away from documents and toward “atomizing” data. 8

9. While there are several existing efforts to address data provenance, no authoritative specification, standard, or model for provenance has been universally adopted to- date, within the context of HIT. The variability in how HIEs, EHRs, and PHRs currently capture, retain, and display provenance is problematic for the interoperable exchange, integration, and interpretation of health data. 9 Challenge

10. To establish a standardized way for capturing, retaining, and exchanging the provenance of health information. What will the community create? – Technical specifications to standardize data provenance: At creation (i.e., point of origin); When its exchanged; and When data is integrated across multiple health information systems. – Guidance for handling data provenance in content standards, including the level to which provenance should be applied. – Establish the minimum set of provenance data elements and vocabulary. 10 Initiative Purpose and Goals

11. The scope of Data Provenance is broad and there are differing perspectives surrounding priorities and expectations for provenance capabilities. For Phase 1, we will tackle the following challenges: (1)When healthcare data is first created, what is the provenance information that should be created and persisted? (2)Can a receiving system understand and trust that provenance information? (3)Do we need to know who touched it along the way? (4)When the receiving system combines this information with data received from a third party, how do we persist the provenance from multiple sources? (5)When multi-sourced data is assembled and sent to another system, how do we convey the provenance of the multiple data sources as well as for the system doing the assembly? – Is this considered new data? – What if the assembling system “cherry picks” from multiple sources, or adds some new health information of its own? 11 Data Provenance – Phase 1

12. 12 Pre-step : Creation of the data and associated provenance information Initiative Activities: Use Case Scenarios (DRAFT) (1)When healthcare data is first created, what is the provenance information that should be created and persisted? Data Source A (e.g. Medical Device, Lab, PHR, EHR, etc.)

13. 13 Pre-step : Creation of the data and associated provenance information Initiative Activities: Use Case Scenarios (DRAFT) (1)When healthcare data is first created, what is the provenance information that should be created and persisted? (2)Can a receiving system understand and trust that provenance information? Data Source A (e.g. Medical Device, Lab, PHR, EHR, etc.) End Point (e.g. EHR, PHR) End Point (e.g. EHR, PHR) Data From Source A

14. 14 Pre-step : Creation of the data and associated provenance information Initiative Activities: Use Case Scenarios (DRAFT) (1)When healthcare data is first created, what is the provenance information that should be created and persisted? (2)Can a receiving system understand and trust that provenance information? (3)Do we need to know who touched it along the way? Transmitter ONLY (HIE, other systems) Transmitter ONLY (HIE, other systems) End Point (e.g. EHR, PHR) End Point (e.g. EHR, PHR) Data From Source A Data Source A (e.g. Medical Device, Lab, PHR, EHR, etc.)

15. End Point (e.g. EHR, PHR) End Point (e.g. EHR, PHR) 15 Data Source with pre-existing data (e.g. EHR) Pre-step : Creation of the data and associated provenance information Initiative Activities: Use Case Scenarios (DRAFT) Data Source A (e.g. Medical Device, Lab, PHR, EHR, etc.) (1)When healthcare data is first created, what is the provenance information that should be created and persisted? (2)Can a receiving system understand and trust that provenance information? (3)Do we need to know who touched it along the way? (4)When the receiving system combines this information with data received from a third party, how do we persist the provenance from multiple sources? Transmitter ONLY (HIE, other systems) Transmitter ONLY (HIE, other systems) Data Source B (e.g. Medical Device, Lab, PHR, EHR, etc.) Transmitter ONLY (HIE, other systems) Transmitter ONLY (HIE, other systems) Data From Source A Data From Source B

16. End Point Start Point = Source C 16 Pre-step : Creation of the data and associated provenance information Initiative Activities: Use Case Scenarios (DRAFT) (1)When healthcare data is first created, what is the provenance information that should be created and persisted? (2)Can a receiving system understand and trust that provenance information? (3)Do we need to know who touched it along the way? (4)When the receiving system combines this information with data received from a third party, how do we persist the provenance from multiple sources? (5)When multi-sourced data is assembled and sent to another system, how do we convey the provenance of the multiple data sources as well as for the system doing the assembly? Data From Source A Data From Source B End Point

17. Start Point = Source C 17 Pre-step : Creation of the data and associated provenance information Initiative Activities: Use Case Scenarios (DRAFT) (1)When healthcare data is first created, what is the provenance information that should be created and persisted? (2)Can a receiving system understand and trust that provenance information? (3)Do we need to know who touched it along the way? (4)When the receiving system combines this information with data received from a third party, how do we persist the provenance from multiple sources? (5)When multi-sourced data is assembled and sent to another system, how do we convey the provenance of the multiple data sources as well as for the system doing the assembly? Data From Source A Data From Source B End Point - Is this considered new data?

18. End Point Start Point = Source C 18 Pre-step : Creation of the data and associated provenance information Initiative Activities: Use Case Scenarios (DRAFT) (1)When healthcare data is first created, what is the provenance information that should be created and persisted? (2)Can a receiving system understand and trust that provenance information? (3)Do we need to know who touched it along the way? (4)When the receiving system combines this information with data received from a third party, how do we persist the provenance from multiple sources? (5)When multi-sourced data is assembled and sent to another system, how do we convey the provenance of the multiple data sources as well as for the system doing the assembly? Data From Source A Data From Source B End Point - Is this considered new data? - What if the assembling system “cherry picks” from multiple sources, or adds some new health information of its own?

19. Achieved Consensus on Charter Working on Use Cases Formed Tiger Team and proposed the Data Provenance project in HL7: – HL7 Implementation Guide for CDA® Release 2: Data Provenance, Release 1 Worked with other HL7 workgroups on vocabulary harmonization 19 Initiative Progress

20. Initiative Activities: S&I Framework PhasePlanned Activities Pre-Discovery  Development of Initiative Synopsis  Development of Initiative Charter  Definition of Goals & Initiative Outcomes Discovery  Creation/Validation of Use Cases, User Stories & Functional Requirements  Identification of interoperability gaps, barriers, obstacles and costs  Review of Candidate Standards Implementation  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  Validation of aligned specifications, testing tools, and reference implementation tools  Revision of documentation and tools Evaluation  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 20

21. Data Provenance –Use Case (Discovery) Ahsin Azim Nisha Maharaja Presha Patel 21

22. 22 Week Target Date (2014) All Hands WG Meeting Tasks Review & Comments from Community via Wiki page due following Tuesday by 8 P.M. Eastern 108/21 Review: Scenario #1 and #2 Functional Requirements and Sequence Diagrams Introduce: Scenario #3 Functional Requirements and Sequence Diagrams Review Scenario #3 Functional Requirements and Sequence Diagrams 118/28 Review :Scenario #3 Functional Requirements and Sequence Diagrams Introduce: Dataset Requirements Review Dataset Requirements 129/4Review Dataset Requirements and Risks/Issues Review Data Set Requirements and Risks And Issues 139/11 Review Risks/Issues Begin End to End Review End to End Review 149/25 End-to-End Comments Review & disposition Begin Consensus Begin casting consensus vote 1510/2Address Consensus comments, if any Proposed Use Case & Functional Requirements Development Timeline

23. Agenda Topic Time Allotted General Announcements10 minutes Use Case Discussion Discuss Timeline/Progress to Date2 minutes Review Risks and Issues5 minutes Comments and Dispositions32 minutes Overview of End to End Review10 minutes Next Steps1 minutes 23

24. 24 Progress to Date Use Case SectionsStatus In Scope Out of Scope Assumptions Context Diagram User Stories Pre Conditions Post Conditions Actors & Roles Activity Diagrams Base Flows Functional Requirements Sequence Diagrams Dataset Requirements Risks & Issues = section developed = section under development(% completed) = indicates there are 3 sections for development (1 for each of the scenarios identified)

25. Sections for Review 25 Today we will be reviewing: 1.Review Risks & Issues 2.Comments and Dispositions 3.Begin End to End Review Double click the icon to open up the Word Document with the sections for review

26. 1.0 Preface and Introduction 2.0 Initiative Overview – 2.1 Initiative Challenge Statement** 3.0 Use Case Scope – 3.1 Background** – 3.2 In Scope – 3.2 Out of Scope – 3.3 Communities of Interest (Stakeholders)** 4.0 Value Statement** 5.0 Use Case Assumptions 6.0 Pre-Conditions 7.0 Post Conditions 8.0 Actors and Roles 9.0 Use Case Diagram Use Case Outline Tailored for each Initiative 10.0 Scenario: Workflow –10.1 User Story 1, 2, x, … –10.2 Activity Diagram o 10.2.1 Base Flow o 10.2.2 Alternate Flow (if needed) –10.3 Functional Requirements o 10.3.1 Information Interchange Requirements o 10.3.2 System Requirements –10.4 Sequence Diagram 11.0 Dataset Requirements 12.0 Risks, Issues and Obstacles Appendices –References ** Leverage content from Charter 26

27. End to End Review of Use Case We are kicking off the “End to End” review process – Starts September 11 th and goes through 8pm ET September 18 th End to End review is open to all members of the DPROV community – We encourage everyone to review the Use Case and provide tangible, actionable comments – All comments will be dispositioned and discussed on the All Hands call September 25 th

28. End to End Review: 1.Locate the Use Case and End To End Review Comment Form: http://wiki.siframework.org/Dat a+Provenance+End+to+End+Revi ew http://wiki.siframework.org/Dat a+Provenance+End+to+End+Revi ew 2.Review the Posted Use Case 3.Complete the Comment Form 4.Submit the Comment Form 1 4 3 2

29. A look ahead: Data Provenance Next Week 29 Begin End to End Review – The End to End Review comment period will end on Thursday, September 18 th, 2014 at 8:00 P.M. ET The next Data Provenance Community Meeting will be on September 25 th, 2014 – Note: The September 18 th, 2014 meeting is cancelled due to HL7 Provide your comments on the bottom of this page http://wiki.siframework.org/Data+Provenance+Use+Cases http://wiki.siframework.org/Data+Provenance+Use+Cases

30. 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.comjc@securityrs.com OCPO Sponsor: Julie Chua: julie.chua@hhs.govjulie.chua@hhs.gov OST Sponsor: Mera Choi: mera.choi@hhs.govmera.choi@hhs.gov Subject Matter Experts: Kathleen Conner: klc@securityrs.com and Bob Yencha: bobyencha@maine.rr.comklc@securityrs.com bobyencha@maine.rr.com Support Team: – Project Management: Jamie Parker: jamie.parker@esacinc.comjamie.parker@esacinc.com – Use Case Development: Presha Patel: presha.patel@accenture.com, Ahsin Azim: ahsin.azim@accenturefederal.com and Nisha Maharaja: nisha.maharaja@accenturefederal.compresha.patel@accenture.comahsin.azim@accenturefederal.com nisha.maharaja@accenturefederal.com – Harmonization: Rita Torkzadeh: rtorkzadeh@jbsinternational.comrtorkzadeh@jbsinternational.com – Standards Development Support: Amanda Nash: amanda.j.nash@accenturefederal.com amanda.j.nash@accenturefederal.com – Support: Lynette Elliott: lynette.elliott@esacinc.com and Apurva Dharia: apurva.dharia@esacinc.comlynette.elliott@esacinc.com apurva.dharia@esacinc.com 30