1. Evaluating Devices Using Claims and Registry Data (EDUCATe)
VISION Meeting
September 10, 2018

2. Disclosures FDA U01FD005478-01 – (Sedrakyan PI)
National Institute on Aging U01AG – Skinner PI
NESTcc Demonstration Project – Goodney (PI)
These are our disclosures

3. Project Goals
To validate a novel mechanism using registry- linked claims data for long-term follow-up after EVAR validated by industry trials
To outline the potential regulatory and scientific utility of registry-linked claims data sources for pre and post-market assessment.

4. Assessing Reintervention After EVAR
is Difficult
Assessing reintervention after EVAR is difficult.

5. Assessing Reintervention After EVAR
is Difficult
Incomplete follow-up
It is limited by incomplete follow up

6. Assessing Reintervention After EVAR
is Difficult
Incomplete follow-up
Poor patient compliance
Poor patient compliance with follow up or imaging

7. Assessing Reintervention After EVAR
is Difficult
Incomplete follow-up
Poor patient compliance
Procedures performed at other centers
And procedures performed at outside other hospital centers

8. Compare the rate of reintervention after EVAR between 3 data sources
Prior Work: SVS 2017
Compare the rate of reintervention after EVAR between 3 data sources
Therefore, our objective was to compare the rate of reintervention after EVAR between 3 data sources

9. Compare the rate of reintervention after EVAR between 3 data sources
The vascular quality initiative, the VQI linked to medicare claims data, and clinical chart review.
VQI
VQI-Medicare
Chart Review

10. Reintervention After EVAR
Cumulative Reintervention Events
1 year
2 years
3 years
VQI-Medicare 6%
13%
18%
Sensitivity 92%
Specificity 96%
Chart Review 6%
11%
16%
Using a gold standard of chart review, VQI medicare linked data was 92% sensitive, and 96% specific to determine a true reintervention event.
VQI 3%
Years

11. 15,000 EVAR 5,000 Open. 10 Year Follow up (Data 11/16/17)

12. Implications
VQI data linked to Medicare claims closely mirrors the actual clinical event rate can be a scalable mechanism for device surveillance.
We wish to test this against an external validated data source – industry clinical trials and registry datasets.
In conclusion, VQI data linked to Medicare claims closely mirrors the actual clinical event rate. This may enhance surveillance for surgeons following patients after EVAR

13. Implications
VQI data linked to Medicare claims closely mirrors the actual clinical event rate can be a scalable mechanism for device surveillance.
We wish to test this against an external validated data source – industry clinical trials and registry datasets.
In conclusion, VQI data linked to Medicare claims closely mirrors the actual clinical event rate. This may enhance surveillance for surgeons following patients after EVAR

14. Implications
VQI data linked to Medicare claims closely mirrors the actual clinical event rate can be a scalable mechanism for device surveillance.
We wish to test this against an external validated data source – industry clinical trials.
In conclusion, VQI data linked to Medicare claims closely mirrors the actual clinical event rate. This may enhance surveillance for surgeons following patients after EVAR

15. Partner Organizations
Aortic endovascular graft manufacturers
Cook Medical, Endologix, Bolton Medical, Gore, Medtronic
Established registries
Society for Vascular Surgery Patient Safety Organization
FDA
MDEpiNet, NESTcc
CMS

16. Partner Organizations
Aortic endovascular graft manufacturers
Cook Medical, Endologix, Bolton Medical, Gore, Medtronic
Established registries
Society for Vascular Surgery Patient Safety Organization
FDA
MDEpiNet
CMS

17. Partner Organizations
Aortic endovascular graft manufacturers
Cook Medical, Endologix, Bolton Medical, Gore, Medtronic
Established registries
Society for Vascular Surgery Patient Safety Organization
FDA
MDEpiNet
CMS

18. Partner Organizations
Aortic endovascular graft manufacturers
Cook Medical, Endologix, Bolton Medical, Gore, Medtronic
Established registries
Society for Vascular Surgery Patient Safety Organization
FDA
MDEpiNet
CMS

19. 3-way linked patient-level dataset
Proposed Cohort: Patients who received EVAR and are captured in VQI, CMS and Pre-market trials
3-way linked patient-level dataset
N=3,000
VQI Registry
Pre-market trials
Medicare

20. Data Residence and Governance
Data are contributed into a Coordinating Center at Cornell Weill Medical Center
Goodney/Sedrakyan/Mell/Cronenwett direct use of shared data resources
Data Governance
Each industry partner retains control of their own data sources
Aggregate, de-identified data products would be primary deliverable

21. Milestones
Create a system to securely send PHI from industry trials to a clearing-house for matching at Cornell
Industry partners, Cornell/VQI team
Generate matched datasets (VQI / Cornell Team)
Industry
VQI
Medicare claims
Evaluate long-term outcomes (VQI / Cornell Team)
Share results with our governance structure

22. Operational Team Members
Executive Committee
Device Surveillance Foundation (Cornell/Dartmouth/VQI team)
Industry Leadership Board
Data oversight
Review of deliverables
Aggregate only
Blinded to data source

23. Data Sets and Matching Techniques
VQI data begins in 2002 (New England), expands nationally in 2010.
Matching
Indirect (DOB, gender, date of procedure, zip)
Direct (name, SSN, Gender, DOB)
We will take whatever years you can send.

24. Steering Committee Members
Status Report
Partners
Steering Committee Members
Milestones
Preparatory Meetings Attended
Review of Data (Elements Available/
Sharing Concerns)
Legal Contracts
Data Use Agreement Between Coordinating Center and Industry Partner
Cook
Scott Williams
Examined consent documents – only a subset can share data and no PHI;
zipcode not available; have study from 2002 which may not be represented in VQI
Agreement signed with SVS PSO, includes grant funding plus in-kind donation for data (total $23,000)
Agreement Executed
DATA RECEIVED 8/14/18
$20,000 Support
Endologix
Meredith Huetter
Matt Thompson
Endologix team discussed data elements with VQI team 
Still reviewing consents and determining which data can be shared
Reviewing materials
pending 
Medtronic
Kristel Wittebols
Tiessa Simoes
Phone discussion of data elements  
Reviewing materials 
Gore
Roberta Bloss, Keely Scamper
Confirmed data sharing ok from legal standpoint
Bolton Medical
Lea Doyle
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25. Communication Timeline
8/ /2017: 4 Steering Committee Meetings held via WebEx or in person at VEITH
1/2018: WCM Legal Team shared draft Data Use Agreements shared with Industry Partners
7/2017: Proposal sent to Industry Partners and MDEpiNet
2/ /2018: Approximately 60+ Individual follow-up s and phone calls
Cook Data Set Received to perform analytics
Time

26. Next Steps Using Data Use Agreement at CMS (Cornell)
Measure Outcomes in Claims
Compare Kappa (agreement) between Cook and Claims algorithm
Patients Present in Cook Data File
Find Cook Patients in Medicare Claims
Thank you for the privilege of the podium.
Measure Outcomes in Cook Data

27. Questions What can we do to expedite legal review in future projects
Who will have access to what kind of data
What Steps will NESTcc take with RWE like this?