1. Phase II – Data & Technical Objectives
Achieve interoperability between research and care by 2019

2. Data Harmonization Team
Daniella Meeker, USC Michael Matheny, VA Lisa Schilling, U of Co Rob Follett, UCLA Tara Knight, USC Michael Hogarth, UCD Calvin Chang, UCD Vijay Rayanker, UCSF Zhen Wu, UCD Lisa Dahm, UCI Martha Michel, UCSF Dax Westerman, VA Ray Pablo, UCI Dave Anderson, San Mateo Amy Perkins, VA Ayan Patel, UCI Claudiu Farcas, UCSD Paulina Paul, UCSD Fern Fitzhenry, VA Spencer Soohoo, Cedars Don Torok, Ephir Jessica Bondy, U of Co Mark Khayter, Ephir Javier Sanz, UCLA Brian Tep, Cedars Srivatsa Hura, San Mateo

3. Data Harmonization Team
Daniella Meeker, USC Michael Matheny, VA Lisa Schilling, U of Co Rob Follett, UCLA Tara Knight, USC Michael Hogarth, UCD Calvin Chang, UCD Vijay Rayanker, UCSF Zhen Wu, UCD Lisa Dahm, UCI Martha Michel, UCSF Dax Westerman, VA Ray Pablo, UCI Dave Anderson, San Mateo Amy Perkins, VA Ayan Patel, UCI Claudiu Farcas, UCSD Paulina Paul, UCSD Fern Fitzhenry, VA Spencer Soohoo, Cedars Don Torok, Ephir Jessica Bondy, U of Co Mark Khayter, Ephir Javier Sanz, UCLA Brian Tep, Cedars Srivatsa Hura, San Mateo

4. Network – 14 Source Systems
VA Data Mart (All VA Facilities)
USC Data Mart (5 sources)
UCI
UCSF
UCSD
UCD
UCLA
San Mateo
Cedars Sinai

5. pSCANNER GitHub 36 Users 10+ Repositories Shared ETL Programs
Research Queries for Distribution
pSCANNER Methods for integration with PopMedNet
Distributed Analytics - Generalized Linear Models
Record Linkage Methods
Quality Measures

6. PCORnet Deliverables Since Last Year
Update PCORnet CDM
Implement and Test SAS Environment
Update Data Mart Client Software
Data Characterization 1
Coordinating Center
Approves
Prep To Research
Ready
Data Characterization 2
Coordinating Center Approves
Research
Ready
Research
Ready
“Query 1”
Menu Driven Query

7. Data Characterization Queries
OMOP
PCORnet
PCORnet
PCORnet
PCORnet
OMOP
PCORnet
OMOP
PCORnet
OMOP
PCORnet
OMOP
PCORnet
OMOP
PCORnet

8. Data Characterization
30 Pages of Instructions
30 Page Report
Meeting with CC
All Sites
Multiple Iterations
Thanks to Colorado Team for help reviewing

9. Menu-Driven Queries OMOP PCORnet PCORnet PCORnet PCORnet OMOP PCORnet

10. Menu Driven Queries from PCORnet
Intended to give an “i2b2” like experience to query authors
Participants
UCI
Cedars Sinai
UCLA
USC
Debugging –configurations

11. PCORNet-OMOP Harmonization WG
PCORNet Data Characterization Queries
PCORNet Preliminary Research Queries
OMOP
PCORnet
OMOP
PCORnet
OMOP
PCORnet
OMOP
PCORnet
OMOP
PCORnet
OMOP
PCORnet

12. PCORNet-OMOP Harmonization WG
Objective: Maintain interoperability between OMOP and PCORnet CDMs
Maintain OMOP-to-PCORnet Data Transformations
Manage new vocabulary and track conventions
Participants
PedsNet & NYC CDRN
Don Torok
Rob Follett
Lisa Schilling

13. Projects on our To-Do List
Create network-wide identifier
Record Linkage Algorithms need to be integrated into the pSCANNER Query Distribution Framework
Update remaining sites to OMOP V5
UCSF Leading
Claims Data Integration
USC Leading CMS (Jason Doctor)
pSCANNER Queries for Quality Measures and OHDSI Studies

14. pSCANNER Data Harmonization for HL7 APIs ONC Pilot with REACHnet
OMOP
FHIR HL7
DAF
OMOP
PCORNet CDM
OMOP
OMOP
OMOP
OMOP

15. Dax Westerman, Lead Developer Bill Clarke, PopMedNet Developer
Technical Update
Dax Westerman, Lead Developer
Bill Clarke, PopMedNet Developer

16. Overview of the PopMedNet pSCANNER Adapter
Create “on demand” networks with any sites that have PopMedNet Data Mart Clients
No “Coordinating Center” – a network can be proposed by anyone
Opt-In by Data Mart Administrator
Analysis Queries
“SHRINE” like queries (on hold - seeing how MDQ works)
REST-ful Framework for Analysis Queries
Distribute Analysis Programs from GitHub or other repositories

17. Username Assigned by Portal Administrator
Password

18. Setting Up an “On-Demand” Research Network

21. Specifying a new research network

23. pSCANNER “special sauce” is the ability to obtain an analysis result that combines data from across sites without requiring transfer of row-level data

31. Agnostic to data model as long as methods match model
Next Release: These Drop-Downs will come from GitHub and other code repositories
Agnostic to data model as long as methods match model

32. Sending out a proposal for a network

34. Nest Step: Review the Study

35. On review of all details, submit the study

36. A study participation request is generated

37. Make sure all the sites are selected, then approve the study

38. Next: Create the analysis

39. Any metadata details are filled in, then saved

40. The analysis is populated, then saved

41. Details of the analysis

42. The analysis is then set for distribution, and results will appear here upon receipt from site DMCs

43. The site DMC pulls the list of analyses to run, and on selection loads the analysis

44. The site user reviews the analysis, and if manual, runs the process
The site user reviews the analysis, and if manual, runs the process. On completion results are uploaded. The user may also choose to Hold, acknowledging receipt but refraining from processing, to Reject (not participate), or to add or remove files from the response (e.g., run the analysis outside the DMC and upload the results).

45. Result – A single model across 3 sites

46. To Do
Development and testing environment so that any developer can contribute and test methods to distributed query framework
Integrate OHDSI tools and WebAPI to Portal Visualizations
some method require sharing row-level data
Implement web service for methods repository
Conformance checks for methods
“Task-lists” for multi-step projects using FHIR Task Resource