Real-World Evidence in a Patient-Centric Digital Era

You must be logged in to access this title.

Sign up now

Already a member? Log in

Synopsis

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.

Book details

Series:
Chapman & Hall/CRC Biostatistics Series
Author:
Kelly H. Zou, Lobna A. Salem, Amrit Ray
ISBN:
9781000613407
Related ISBNs:
9781003017523, 9781032303628, 9780367861810
Publisher:
CRC Press
Pages:
190
Reading age:
Not specified
Includes images:
No
Date of addition:
2022-08-02
Usage restrictions:
Copyright
Copyright date:
2022
Copyright by:
N/A 
Adult content:
No
Language:
English
Categories:
Mathematics and Statistics, Medicine, Nonfiction