May 21, Moderator: Rachael Fleurence, PhD NESTcc Executive Director

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1 The Changing Landscape of Health Care Decision-Making How can we Leverage the use of Real-World Evidence for Regulatory, Coverage, and Clinical Decision-Making? May 21, 2018 M EET YOUR PANELISTS! Moderator: Rachael Fleurence, PhD NESTcc Executive Director Kathleen Blake, MD, MPH American Medical Association (AMA) NESTcc Governing Committee Member Owen Faris, PhD U.S. Food and Drug Administration (FDA) Center for Devices and Radiological Health (CDRH) Daniel Caños, PhD, MPH Center for Clinical Standards and Quality, Evidence and Analysis Group at Center for Medicare and Medicaid Services (CMS) 2 1

2 Establishing the National Evaluation System for health Technology Coordinating Center (NESTcc) 3 NESTcc S ROLE IN THE ECOSYSTEM NESTcc Mission Statement To accelerate the development and translation of new and safe health technologies, leveraging Real-World Evidence (RWE), and innovative research. Clinician Groups History of NESTcc Industry Payers NEST envisioned as a voluntary data network of collaborators by Planning Board FDA awarded grant for NESTcc to Medical Device Innovation Consortium (MDIC) Executive Director of NESTcc named NESTcc Governing Committee selected Patient Groups NESTcc Health Systems Regulators NESTcc Strategic and Operational Plan 4 2

3 NESTcc DEVICE NETWORK TIM ELINE 2018 Establish initial NESTcc Data Network with 11 collaborators Implement test-cases with manufacturers and NESTcc network collaborators Work with stakeholders to establish data quality and methods standards as well as operating processes Identify gaps in data infrastructure to support robust medical device studies and find solutions Expand NESTcc Data 5 ESTABLISH NESTcc GOVERNANCE The NESTcc Governing Committee represents stakeholders across the medical device ecosystem. NAOMI ARONSON Blue Cross Blue Shield Association (BCBSA) KATHLEEN BLAKE American Medical Association (AMA) MARK DEEM MDMA Nominee The Foundry, LLC PAMELA GOLDBERG Medical Device Innovation Consortium (MDIC) BILL HANLON ACLA Nominee LabCorp/Covance ADRIAN HERNANDEZ Duke Clinical Research Institute (DCRI) HARLAN KRUMHOLZ Yale University ELIZABETH MCGLYNN Kaiser Permanente MICHELLE MCMURRY-HEATH AdvaMed Nominee Interim Governing Committee Chair Johnson & Johnson Medical Devices VANCE MOORE Mercy Health JEFFREY SHUREN FDA, CDRH SHARON TERRY Genetic Alliance DIANE WURZBURGER MITA Nominee GE Healthcare MARC BOUTIN National Health Council TAMARA SYREK JENSEN Center for Clinical Standards and Quality, CMS Trade Association 6 3

4 ESTABLISH NESTcc GOVERNANCE: SUBCOM M IT TEES NESTcc is launching four subcommittees to achieve sustainability and establish its value in the medical device ecosystem. NESTcc GOVERNING COMMITTEE MEMBERS STAKEHOLDERS SELECTED THROUGH A PUBLIC CALL CHARTER SUSTAINAB ILITY DATA Q UA L I T Y M E T H O D S Make recommendations related to the NESTcc Charter and determination of roles and responsibilities between NESTcc governing and decision-making entities Provide strategic input to the development and implementation of the business, operating, and financial NESTcc sustainability models Establish data quality standards and address issues with data quality, particularly as they impact NESTcc s mission Develop a research agenda identifying critical issues in methods across the TPLC and establish methods standards to include device specific 7 DEVELOP NESTcc S ROLE: THREE- PRONGED APPROACH NESTcc is building a sustainable network of collaborators committed to advancing RWE generation. Engage 11 Demonstration Projects covering a range of uses of RWE 7 case-studies underway to describe the value for industry stakeholders of using RWE Leverage 11 NESTcc network collaborators are pioneering the establishment of NESTcc s Data Network. 7 RWE test-cases are launching to demonstrate proof of concept. Transform Continue to identify barriers for research-ready medical device data infrastructure with our partners Establish data quality and methods standards through subcommittees of 8 4

5 9 The Changing Landscape of Health Care Decision-Making: How can we Leverage the use of Real-World Evidence for Regulatory, Coverage, and Clinical Decision-Making? Kathleen Blake, MD, MPH Vice President, Healthcare Quality at the American Medical Association (AMA) 10 5

6 The Changing Landscape of Health Care Decision-Making How can we Leverage the use of Real-World Evidence for Regulatory, Coverage, and Clinical Decision-Making? Kathleen Blake, MD, MPH May 2018 The innovation pathway to clinical integration of new technology... Will this fundamentally transform my practice? Does it work? Will I get paid? Will I get sued? Will it work in my practice? Innovation Coding Coverage Clinical Practice Regulation Pricing Liability Training Organizing to address barriers to innovation, approval, coverage, adoption and surveillance American Medical Association. All rights reserved. 6

7 NEST : 21 st Century medical device decision-making (clinician perspective) Multiple sources of evidence throughout the Total Product Life Cycle Randomized controlled trials Registries Electronic health records Claims data Adverse event reporting New methods and analyses of RWE Timely safety signal reporting by a trusted entity American Medical Association. All rights reserved. Innovation/ Modification Does it work? Training/ Professional Development Data EHRs and Registries Data - UDI Regulation/QA Will I get paid? Will I get sued? Interoperability /Infrastructure Data Administrative Claims Data Administrative Codes Coding Coverage Pricing American Medical Association. All rights reserved. 7

8 The Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices Owen Faris, PhD Director, Clinical Trials Program Office of Device Evaluation Center for Devices and Radiological Health Food and Drug Administration 15 The Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices Owen Faris, Ph.D. Director, Clinical Trials Program Office of Device Evaluation Center for Devices and Radiological Health Food and Drug Administration 16 8

9 Some RWE Recent History CDRH Strategic Priorities National Evaluation System for health Technology (NEST) FDARA (including MDUFA IV) commitment to use of real-world evidence to support device pre/postmarket decisions Guidance issued to clarify how RWE may be used to support regulatory decisions. Issued August 31, Devices Are Different from Drugs Many devices are highly dependent on clinician knowledge, experience, and skill Devices and techniques iteratively and rapidly improve (sometimes even during a trial) Gold-standard RCT often not practical = 18 9

10 What are the opportunities? Flexibility Can t always get what you want. But if we are flexible, we can get what we need Innovation Modeling Adaptive designs Real-world evidence Collaborations NEST Industry groups Patient and clinician groups 19 Clinical Trial Innovation 20 10

11 Evidence in Regulatory Decisions Traditional Regulatory Pathway Pre-Clinical Testing Clinical Studies Pre-Market Application Post-Market Hypothesis Generation Device Innovation Informed Clinical Decision Making Claims Databases Laboratory Tests Pharmacy Data Patient Experience Social Media Healthcare Information Registries Electronic Health Records Hospital Visits Real-World Device Use Physician and Patient Experience Non-Traditional Clinical Data Generation 21 Data Quality Fit for Purpose Data should be assessed for completeness, consistency, accuracy, and whether it contains all critical data elements needed to evaluate a medical device and its claims. Relevant & Reliable Benefit Risk 22 11

12 Some Regulatory Uses for RWE Control arm for pivotal clinical study New indications for approved devices Studying new improvements to devices Replacing post approval study Adverse event reporting Shifts to prepostmarket balance 23 Some Non-Regulatory Uses for RWE Informing the community on optimal care Identifying needs and gaps Market analysis Assessing quality of care 24 12

13 CDCRN A Reusable Infrastructure for Clinical and Regulatory Evidence Generation Laschinger JC * Identifiable Personal Information; + Unique Device Identifier # Continue to operate independently to fulfill their current individually designed, essential and sustainable missions # CDCRN Results In: NO CHANGE to current governance or business models of any registry NO DISRUPTION of current clinical uses or utility of registries to end users Positions Academic Societies & Registries at the center of the clinical trial enterprise CDCRN Allows: Prospective collection of uniform trial/rx data Programmed passive longitudinal data and evidence acquisition Production of Dynamic CLINICAL/REGULATORY evidence over TPLC 25 Longitudinal Data Generation & Acquisition Important Hard Outcomes Continuously Tracked Over Time Index Procedure Passive Follow-up: Acquisition of Normally Generated Longitudinal Data *Success = alive with well functioning device and no life altering cx, re-intervention or re-hospitalization Administrative Records Event Generated Government/Payer Datasets* Laschinger JC Registry Records: Procedure Generated Reoperation Reintervention New Intervention or Surgery Longitudinal data acquired Yearly or as RDCF # Entered Longitudinal data acquired Yearly (e.g. anniversary date of index procedure) *pre-specified ICD-10 Codes # RDCF = Registry Data Collection Form + Life altering complications = effecting long term outcomes/qol e.g. Disabling stroke, Dialysis, AMI, etc

14 Daniel Arthur Caños, PhD, MPH Director, Evidence Development Division Coverage and Analysis Group Center for Clinical Standards and Quality CMS 14

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16 CMS Coverage Decisions CMS was an early supporter for postmarket real world data collection October 2003: Ventricular Assist Devices NCD January 2005: Implantable Cardioverter Defibrillator NCD MDEpiNet Claims Validation Brennan et al, QCOR 2014 MDEpiNet Funded Similar event rates and treatment effects for Claims-based vs Trialsbased AE detection for select CV endpoints: Myocardial Infarction Heart Failure Repeat Procedure 16

17 Registries and Longitudinal Data Collection Primary outcomes included death, stroke, and combined death and stroke at 30 days and 1 year and days alive and out of the hospital at 1 year. In-hospital outcomes were collected from the TVT Registry Medicare in-hospital administrative claims files were used for detection of rehospitalization events (ICD-9-CM) codes: =For stroke, 433.x1, 434.x1, , 436, 437.1, 437.9, 430, 431, and 432.x; =For heart failure, 398.x, 402.x1, 404.x1, 404.x3, and 428.x; and =For aortic valve reintervention, 35.11, 35.21, Holmes DR Jr JAMA Mar 10;313(10): , 35.01, 35.05, 35.06, and Months of Patient Follow-up TVT-R Medicare Claims Linkage Stroke All cause mortality TIAs Major vascular events Acute kidney injury Repeat procedures Quality of Life (QoL) All cause mortality Repeat Procedures Rehospitalizaton for stroke or heart failure 17

18 Linked registries FDA/ Sentinel: Identified 20 HOIs Examined identified algorithms and the test characteristics of those algorithms were synthesized. ABO incompatibility; anaphylaxis; atrial fibrillation; cardiac arrhythmias; congestive Heart Failure; CVA/TIA; Depression; erythema multiforme; gap analysis; hypersensitivity reactions; lymphomas; operational framework; orthopedic implant removal; pancreatitis; pulmonary fibrosis; respiratory failure; seizures; suicide; transfusion/graft infections; transfusion sepsis; venous thromboembolism. Three validated outcomes: acute kidney injury, acute myocardial infarction cases; anaphylaxis cases; severe liver injury cases Observational Medical Outcomes Partnership (OMOP): Established an open-source library of 10 HOI definitions for use in observational studies due to associations with drug toxicities, their medical significance, and/or public health implications. acute liver injury; acute myocardial infarction; acute renal failure; angioedema; aplastic anemia; bleeding; GI ulcer hospitalization; hip fracture; hospitalization; mortality after myocardial infarction. In the absence of validation studies supporting the accuracy of adjudicated for primary outcomes, big data efforts need to incorporate adjudication into the endpoint ascertainment methodology. Leadless Pacemaker FDA Post Approval Study Clinically rich data with a focused sample size Claims Based Study Larger sample size for detecting rarer events 18

19 Leadless Pacemaker FDA Post-approval Studies N = 2450 Acute complication rate [30-days] Long-term complication free survival [9 years] Complications stratified by implant type [Up to 9 years] Micra System revision rate [Up to 9 years] System Longevity [Up to 9 years] Claims Based CED Studies All Medicare Beneficiaries Acute complication rate [30-days] Survival Rate [2 years] Chronic complicatons [6-months] Device-related re-intervention rates [2 years ] Conclusion CMS has been an early and consistent adopter of postmarket real world data collection Real world data is not a one-size fits all approach Utilization of real world evidence would be expedited with: Centrally located validated health outcomes of interest for medical devices Core data elements and definitions across real world data sources Extant registry infrastructure certified as fit for purpose 19