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E-raamat: Examining the Impact of Real-World Evidence on Medical Product Development: Proceedings of a Workshop Series

  • Formaat: 230 pages
  • Ilmumisaeg: 05-Apr-2019
  • Kirjastus: National Academies Press
  • Keel: eng
  • ISBN-13: 9780309488327
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  • Formaat: 230 pages
  • Ilmumisaeg: 05-Apr-2019
  • Kirjastus: National Academies Press
  • Keel: eng
  • ISBN-13: 9780309488327
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Randomized controlled trials (RCTs) have traditionally served as the gold standard for generating evidence about medical interventions. However, RCTs have inherent limitations and may not reflect the use of medical products in the real world. Additionally, RCTs are expensive, time consuming, and cannot answer all questions about a product or intervention. Evidence generated from real-world use, such as real-world evidence (RWE) may provide valuable information, alongside RCTs, to inform medical product decision making.





To explore the potential for using RWE in medical product decision making, the National Academies of Sciences, Engineering, and Medicine planned a three-part workshop series. The series was designed to examine the current system of evidence generation and its limitations, to identify when and why RWE may be an appropriate type of evidence on which to base decisions, to learn from successful initiatives that have incorporated RWE, and to describe barriers that prevent RWE from being used to its full potential. This publication summarizes the discussions from the entire workshop series.

Table of Contents



Front Matter 1 Introduction 2 Perspectives on Real-World Evidence 3 Learning from Success 4 Barriers and Disincentives to the Use of Real-World Evidence and Real-World Data 5 Getting Unstuck: Mythbusting the Current System 6 When Is a Real-World Data Element Fit for Assessment of Eligibility, Treatment Exposure, or Outcomes? 7 How Tightly Should Investigators Attempt to Control or Restrict Treatment Quality in a Pragmatic or Real-World Trial? 8 Obscuring Intervention Allocation in Trials to Generate Real-World Evidence: Why, Who, and How? 9 Gaining Confidence in Observational Comparisons 10 Looking Ahead References Appendix A: Related Resources Appendix B: Workshop One Agenda Appendix C: Workshop Two Agenda Appendix D: Workshop Three Agenda
Acronyms and Abbreviations xix
1 Introduction
1(12)
Defining the Terms
6(2)
The U.S. Food and Drug Administration's Vision for the Future
8(2)
Fit-for-Purpose Evidence
10(3)
2 Perspectives on Real-World Evidence
13(12)
Payer Perspective
14(2)
Delivery Systems Perspective
16(3)
Patient Perspective
19(2)
Discussion
21(4)
3 Learning From Success
25(14)
Salford Lung Studies
26(6)
Sentinel
32(5)
Device Registries
37(2)
4 Barriers and Disincentives to the Use of Real-World Evidence and Real-World Data
39(12)
The Use of Real-World Evidence and Real-World Data in Product Development
40(2)
Making Choices About Research Design
42(1)
Accelerating Evidence Generation Through Defragmentation
43(2)
Evidence Hierarchies
45(1)
Opportunities to Integrate Real-World Data and Real-World Evidence in Research
46(3)
Discussion
49(2)
5 Getting Unstuck: Mythbusting the Current System
51(20)
From Precision to Reliability
52(4)
Integrating the New with the Old
56(10)
Regulatory Perspective
66(5)
6 When is a Real-World Data Element Fit for Assessment of Eligibility, Treatment Exposure, or Outcomes?
71(28)
Real-World Data Elements
72(1)
Illustrative Examples
73(5)
Discussion: Characterizing Real-World Data and Real-World Evidence
78(4)
Decision Aid
82(1)
"Fit for Purpose" and Relevance of Data
82(7)
Patient-Generated Data
89(4)
Discussion: Real-World Data Concerns for Future Research
93(6)
7 How Tightly Should Investigators Attempt to Control or Restrict Treatment Quality in a Pragmatic or Real-World Trial?
99(18)
Illustrative Examples
100(7)
Decision Aid
107(3)
Patient-Centered Research
110(1)
Context of the Decision
111(2)
Obligations to Patients
113(4)
8 Obscuring Intervention Allocation in Trials to Generate Real-World Evidence: Why, Who, and How?
117(16)
Illustrative Examples
118(3)
Decision Aid
121(4)
Discussion
125(8)
9 Gaining Confidence in Observational Comparisons
133(20)
Illustrative Examples
134(7)
Discussion: Observational Studies and Randomization
141(3)
Decision Aid
144(1)
Presentations: Observational Studies and Bias
145(6)
Discussion: The Future of Observational Studies
151(2)
10 Looking Ahead
153(28)
Real-World Evidence to Improve Health Technology Assessment
154(3)
Real-World Evidence to Turn Patients into Partners
157(3)
Real-World Evidence to Transform Research and Development
160(5)
Real-World Evidence to Inform Regulatory Decisions
165(9)
Final Thoughts
174(3)
References
177(4)
APPENDIXES
A Related Resources
181(2)
B Workshop One Agenda
183(8)
C Workshop Two Agenda
191(8)
D Workshop Three Agenda
199