Table Of Content

i Real- World Evidence in a Patient- Centric Digital Era Real- world evidence is defined as evidence generated from real-w orld data out- side 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-w orld 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 custom- arily 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-c ase studies to demon- strate 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 refer- ence for medical researchers, health technology innovators, data scientists, epidemiologists, population health analysts, health economists, outcomes researchers, policymakers, and analysts in the healthcare industry. ii Chapman & Hall/ CRC Biostatistics Series Series Editors Shein- Chung Chow, Duke University School of Medicine, USA Byron Jones, Novartis Pharma AG, Switzerland Jen- pei Liu, National Taiwan University, Taiwan Karl E. Peace, Georgia Southern University, USA Bruce W. Turnbull, Cornell University, USA Recently Published Titles Simultaneous Global New Drug Development Multi- Regional Clinical Trials after ICH E17 Edited by Gang Li, Bruce Binkowitz, William Wang, Hui Quan, and Josh Chen Quantitative Methodologies and Process for Safety Monitoring and Ongoing Benefit Risk Evaluation Edited by William Wang, Melvin Munsaka, James Buchanan, and Judy Li Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS Qingzhao Yu and Bin Li Hybrid Frequentist/ Bayesian Power and Bayesian Power in Planning Clinical Trials Andrew P. Grieve Advanced Statistics in Regulatory Critical Clinical Initiatives Edited By Wei Zhang, Fangrong Yan, Feng Chen, and Shein- Chung Chow Medical Statistics for Cancer Studies Trevor F. Cox Real- World Evidence in a Patient- Centric Digital Era Edited by Kelly H. Zou, Lobna A. Salem, and Amrit Ray For more information about this series, please visit: www.routle dge.com/ Chap man- - Hall- CRC- Biosta tist ics- Ser ies/ book- ser ies/ CHBI OSTA TIS iii Real- World Evidence in a Patient- Centric Digital Era Edited by Kelly H. Zou Lobna A. Salem Amrit Ray iv First edition published 2023 by CRC Press 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487- 2742 and by CRC Press 2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN © 2023 CRC Press CRC Press is an imprint of Taylor & Francis Group, LLC Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, access www.copyri ght.com or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-7 50- 8400. For works that are not available on CCC please contact [email protected] Trademark notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification and explanation without intent to infringe. ISBN: 9780367861810 (hbk) ISBN: 9781032303628 (pbk) ISBN: 9781003017523 (ebk) DOI: 10.1201/ 9781003017523 Publisher’s note: This book has been prepared from camera- ready copy provided by the authors. v Contents Preface: Real World Evidence and Digital Innovation to Combat Noncommunicable Diseases................................................................................vii List of Contributors ..............................................................................................xiii About the Editors ..................................................................................................xv Disclaimer ............................................................................................................xvii 1. Real-World Evidence Generation .................................................................1 Joseph S. Imperato, Joseph P. Cook, Diana Morgenstern, Kim Gilchrist, Tarek A. Hassan, Jorge Saenz, and Danute Ducinskiene 2. Applications of RWE for Regulatory Uses ................................................27 Eleanor E. Panico, Corinne S. Pillai, Ewa Filipowska, and Kelly H. Zou 3. Patient Data Privacy, Protected Health Information, and Ethics of Real- World Evidence .....................................................................................51 Corinne S. Pillai, Eleanor E. Panico, Kelly H. Zou, and Ewa Filipowska 4. Real- World Data, Big Data, and Artificial Intelligence: Recent Development and Emerging Trends in the European Union ................73 Kelly H. Zou 5. Patient Centricity and Precision Medicine ...............................................83 Diana Morgenstern, Mina B. Riad, Claudia Zavala, and Amrit Ray 6. Health Information Technology ..................................................................95 Joseph P. Cook, Gabriel Jipa, Claudia Zavata, and Lobna A. Salem 7. Digital Health Technologies and Innovations .......................................137 Kelly H. Zou, Mina B. Riad, Shaantanu Donde, Joan van der Horn, and Tarek A. Hassan 8. Economic Analysis and Outcome Assessment .......................................153 Jean- Pascal Roussy and Kelly H. Zou 9. Partnerships and Collaborations ..............................................................165 Salman Rizvi and Urooj A. Siddiqui v vi vi Contents 10. Global Perspective: China Big Data Collaboration to Improve Patient Care .................................................................................173 Zhi Xia Xie, Jim Z. Li, Yvonne Huang, Olive Jin, Wei Yu, and Kelly H. Zou 11. The Future of Patient- Centric Data- Driven Healthcare ......................181 Kelly H. Zou, Lobna A. Salem, and Amrit Ray Index .....................................................................................................................187 vii Preface Real World Evidence and Digital Innovation to Combat Noncommunicable Diseases Kelly H. Zou,1 Lobna A. Salem,1 Joseph P. Cook,1 Anurita Majumdar,2 and Amrit Ray3 1Viatris, 2GlaxoSmithKline, 3Principled Impact, LLC Why do Real- World Evidence and Digital Technologies Matter? The Food & Drug Administration (FDA) defines Real-World Data (RWD) as “the data relating to patient health status and/o r the delivery of healthcare routinely collected from a variety of sources” (FDA, 2022a). Healthcare facilities routinely collect medical and patient data and electronically record them when patients use their facilities. Such recording continues even after patients leave the healthcare facility. The gathering of these data provides the healthcare com- munity with a significant amount of useful medical and patient information. Real- world evidence (RWE) “is the clinical evidence regarding the usage and potential benefits or risks of a medical product derived from analysis of RWD” (FDA, 2022a). As the name suggests, RWE provides scientific and clin- ically relevant real- world information to improve medical care for patients globally (FDA, 2018). Digital technologies support access to quality healthcare in a number of ways and for separable purposes. They include electronic healthcare (“eHealth”), which covers a range of electronic technologies applied to healthcare and relates principally to the application of computers. Mobile health (“mHealth”) relates to the subset of eHealth that uses mobile technologies to share information over the radio waves. Artificial intelligence combines systems that mimic human intelligence and robust datasets to propel healthcare with new insights across early diagnosis, prevention, and treatment. Randomized controlled trials (RCTs) often do not address the complex intersection of many diseases and comorbid conditions, which are patient centric and require us to find alternate ways of getting evidence to support such need gaps. vii viii viii Preface NonCommunicable Diseases around the World Noncommunicable diseases (NCDs) are the leading cause of death around the world. The devastation of a “silent killer” has increasingly become a critical global health burden. Despite the overwhelming burden of NCDs, RCTs address disease entities and not NCDs holistically (KFF, 2019). The problem of NCDs cannot be overstated, according to the World Health Organization (WHO). NCDs account for 71% (41 million) of global deaths each year, nearly 44% of which are attributable to cardiovascular disease (CVD), including stroke and ischemic heart disease; 22% to cancer; 9% to chronic respiratory disease; and 4% to diabetes (Noncommunicable Diseases, WHO). Around 30% of these deaths are premature, occurring before the age of 70 years, and it is documented that every two seconds one person between the ages of 35– 75 would die prematurely from NCDs. CVD is often categorized as a disease of wealthy, industrialized societies. Yet with increased urbanization and changing lifestyles over the years, over 75% of CVD- related global deaths occur in low- and middle- income countries (LMIC), while in high- income countries (HICs), cancer is particularly preva- lent. Europe, for example, with one-e ighth of the world population, has one- quarter of all cancer cases. Three-hundred million people have chronic respiratory diseases worldwide, and this number is increasing. Likewise, the number of people with diabetes has increased nearly fourfold since 1980. With the coronavirus disease of 2019 (COVID) pandemic disproportionately impacting people living with NCDs, many patients suffered NCD- related comorbidities blurring the lines between what are known widely as communicable versus noncommunicable diseases. The pandemic has added to the complexity of the public health challenge and the difficulty in providing an effective solution to the growing NCDs burden. Hence, understanding NCDs with the objective of effective control should be a key consideration in the healthcare agendas of governments, multilateral organizations, and the private sector (WHO, 2022; KFF, 2019; Pan American Health Organization [PAHO], 2022). A sobering reality of NCDs is not only their mortality burden but also their major contribution to morbidity and disability. To make things more complicated, NCDs associated with the greatest morbidity and disability burden differ from those responsible for the greatest risk of mortality. For example, mental illness and chronic pain are recognized as key drivers of NCD- related morbidity and disability with a heavy economic burden but are not considered major contributors to mortality. The overall economic burden of NCDs continues to increase and it has been estimated that a cumulative US $47 trillion in economic output will be lost to NCDs between 2010 and 2030 (The US Government and Global Non- Communicable Disease Efforts). In the United States (US) alone, the ix Preface ix costs of managing chronic diseases are projected to total US $4.2 trillion yearly by 2023. To understand how to combat the burden of NCDs, there needs to be a thorough understanding of the underlying causes of NCDs. Two major factors contribute to the burden of NCDs, namely disease-related and healthcare system-related factors. Disease-r elated factors include envir- onmental and behavioral risk factors, some of which are modifiable, such as tobacco use and unhealthy diet, while others are non-m odifiable, such as CVD that is more common in men than women. For healthcare system- related factors, the lack of patient awareness and empowerment, along with limited access to well-trained primary care physicians to manage NCDs, leads to an overall gap in the integration/ coordination of care across the patient journey. Despite the technology revo- lution seen in many other sectors, technology in healthcare has not been leveraged to provide adequate solutions to the challenges posed by NCDs. Gaps in leveraging big data are revealing signs of the struggles to take advan- tage of what technology and diverse data sources (drug registries, healthcare data) can offer. Analyses of these data sources with the patient with chronic diseases at their center has the ability to generate meaningful learnings that could contribute significantly to address the data gap in NCDs’ burden. Real- World Evidence in NonCommunicable Diseases Given the negative impact of NCDs on patients’ and their families’ lives, we recommend the use of data-d riven methods (e.g., RWE) for understanding global healthcare policymaking with a view to address the burden and impact of NCDs broadly. We believe that RCTs tend to focus on less diverse patient populations to compare therapies, which leaves gaps in the evidence (FDA, 2022b). Hence, we recommend the use of RWE to complement the evidence, which would help in obtaining timely data for actionable insights and enabling informed decision making for NCD policies. There are also ways to consider external control arms and synthetic control arms (FDA, 2019). There are multiple ways that RWE can help address the NCD crisis, including in relation to prevention, epidemiology, diagnosis, risk- assessment, patient journey analysis, treatment choices, and prognosis. Using evidence generated from multiple sources in the real world and from multiple markets, we can map patient journeys to better understand adherence to therapies and to measure outcomes. In NCDs, in particular, it is common for patients to have multiple comorbid conditions and diseases that overlap. Therefore, quantitative and qualitative information can help evaluate patients’ diagnoses, therapies, and prognoses holistically and comprehensively. Furthermore, a beyond NCD-only approach can also be