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

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

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

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

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

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

Data Characterization Queries OMOP PCORnet PCORnet PCORnet PCORnet OMOP PCORnet OMOP PCORnet OMOP PCORnet OMOP PCORnet OMOP PCORnet

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

Menu-Driven Queries OMOP PCORnet PCORnet PCORnet PCORnet OMOP PCORnet

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

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

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

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

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

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

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

Username Assigned by Portal Administrator Password

Setting Up an “On-Demand” Research Network

Specifying a new research network

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

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

Sending out a proposal for a network

Nest Step: Review the Study

On review of all details, submit the study

A study participation request is generated

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

Next: Create the analysis

Any metadata details are filled in, then saved

The analysis is populated, then saved

Details of the analysis

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

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

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).

Result – A single model across 3 sites

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