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, policymakers, and analysts in the healthcare industry.
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