Real-world evidence is defined as evidence generated from real-world data outside randomized controlled trials. As scientific discoveries and methodologies continue to advance, real-world data and their companion technologies offer powerful new tools for evidence generation. Real-World Evidence in a Patient-Centric Digital Era provides perspectives, examples, and insights on the innovative application of real-world evidence to meet patient needs and improve healthcare, with a focus on the pharmaceutical industry.
This book presents an overview of key analytical issues and best practices. Special attention is paid to the development, methodologies, and other salient features of the statistical and data science techniques that are customarily used to generate real-world evidence. It provides a review of key topics and emerging trends in cutting-edge data science and health innovation.
Features
Provides an overview of statistical and analytic methodologies in real-world evidence to generate insights on healthcare, with a special focus on the pharmaceutical industry
Examines timely topics of high relevance to industry such as bioethical considerations, regulatory standards, and compliance requirements
Highlights emerging and current trends, and provides guidelines for best practices
Illustrates methods through examples and use-case studies to demonstrate impact
Provides guidance on software choices and digital applications for successful analytics
Real-World Evidence in a Patient-Centric Digital Era will be a vital reference for medical researchers, health technology innovators, data scientists, epidemiologists, population health analysts, health economists, outcomes researchers, as well as policymakers and analysts in the healthcare industry.
Author(s): Kelly H. Zou, Lobna A. Salem, Amrit Ray
Series: Chapman & Hall/CRC Biostatistics Series
Publisher: CRC Press/Chapman & Hall
Year: 2022
Language: English
Pages: 208
City: Boca Raton
Cover
Half Title
Series Information
Title Page
Copyright Page
Table of Contents
Preface
Contributors
About the Editors
Disclaimer
1 Real-World Evidence Generation
1.1 Types of Real-World Data and the Generation of Real-World Evidence
1.2 The Evidence Hierarchy and Importance of RWE/Digital
1.3 Real-World Evidence and Its Relationship to Population Health, Epidemiology, and Observational Studies in Population ...
1.4 Randomized Controlled Trials and Pragmatic Clinical Trial Optimization Using RWE
1.4.1 Ethics
1.4.2 Randomization
1.4.3 Blinding
1.5 Improving Adherence Via Data-Driven Methods
Disclaimer
References
2 Applications of RWE for Regulatory Uses
2.1 Inroduction - RWE in the Pharmaceutical Industry
2.1.1 RWE and Regulatory Success
2.2 Pharmacovigilance and Safety Surveillance
2.3 Clinical Trial Optimization
2.4 RWE for HTA Purposes
2.5 Label Expansion & Drug Approvals
2.6 Health Authority Perspectives
Disclaimer
References
3 Patient Data Privacy, Protected Health Information, and Ethics of Real-World Evidence
3.1 Data Privacy Laws
3.2 Ethics of Real-World Evidence
3.3 Ethics Committee and Institutional Review Board
3.3.1 Historical Events Driving Ethical Research
3.3.2 Modern Governance for Ethical Research
3.4 Best Practices
3.4.1 Understand Data and Craft Analysis Plan
3.4.2 Share Data Via Distributed Research Network
3.4.3 Leverage Available Tools and RWE Guidance Documents
Remarks
Disclaimer
References
4 Real-World Data, Big Data, and Artificial Intelligence: Recent Development and Emerging Trends in the European Union
4.1 Introduction
4.2 Network Strategy
4.3 RWD, RWE, and RCTs
4.4 Big Data
4.5 DARWIN EU®
4.6 GDPR
4.7 Ethics and Informed Consent
4.8 EU PAS Register®
4.9 AI
Remarks
Disclaimer
References
5 Patient Centricity and Precision Medicine
5.1 Patient Voice
5.2 Patient Journey Mapping
Final Remarks
Disclaimer
References
6 Health Information Technology
6.1 Contemporary EHealth
6.2 Artificial Intelligence
6.3 Machine and Deep Learning
6.4 Personal Devices Augmenting User Experience
6.5 Process to Identify a Potential Technology Solution
Remarks
Disclaimer
References
7 Digital Health Technologies and Innovations
7.1 Digital Endpoints and Bring Your Own Device Model
7.2 Wearables and Sensors
7.3 Digital Therapeutics and Apps
7.4 Remote Patient Monitoring
Remarks
Disclaimer
References
8 Economic Analysis and Outcome Assessment
8.1 Economic Analysis
8.2 Outcome Assessment and Analysis of Outcomes
Remarks
Disclaimer
References
9 Partnerships and Collaborations
9.1 The Evolving Healthcare Landscape
9.2 Partnerships in Healthcare
9.3 Collaboration Amidst the COVID-19 Crisis
9.4 Innovation in a Post-Pandemic World
Summary
Disclaimer
References
10 Global Perspective: China Big Data Collaboration to Improve Patient Care
10.1 Big Data and Real-World Evidence in China
10.2 Digital Innovation During and Post-Pandemic
Summary
Disclaimer
References
11 The Future of Patient-Centric Data-Driven Healthcare
Disclaimer
References
Index
