AI Driven Innovations in Healthcare

Best Practices and Case Studies
1. Auflage 2025
ISBN: 978-1-041-02888-8
Verlag: Taylor & Francis

Buch, Englisch, 200 Seiten, Format (B × H): 178 mm x 254 mm, Gewicht: 449 g

The integration of artificial intelligence (AI) in healthcare organizations is no longer a futuristic concept—it’s here, reshaping patient care, optimizing operational efficiency, and enhancing diagnostic accuracy. However, while AI offers immense potential, finding its practical applications, and scaling its implementation is fraught with both technical and practical challenges, ranging from data security, ethical concerns, regulatory practices, and workforce adaptation. For digital health leaders, adopting AI successfully requires a deep understanding of not only the technology itself but also the organizational and human factors that can make or break its success. Artificial Intelligence Driven Innovations in Healthcare is a practical guide designed to help digital health and IT professionals, chief medical information officers, administrators, and policymakers navigate these complexities and leverage AI to achieve sustainable improvements in care delivery.
This book is not a technical manual on AI algorithms, but rather, a guide to show how technology leaders are adopting AI within their own healthcare organization or healthcare practice. It presents best practices from the Healthcare Information Management and Systems Society (HIMSS)/INFORMA annual conferences in recent years. The includes contributions from approximately 20 presenters from HIMSS Global Health Conference. The focus of these chapters will be around AI technology’s place in helping to create innovations in operations, design, and delivery. This book will draw on real-world case studies, spotlighting successful attempts to implement AI in a range of healthcare environments, from small clinics to major hospital systems.

The book will begin with an overview of AI’s role in healthcare and its key applications, such as predictive analytics, personalized treatment planning, robotic surgery, and administrative automation. Each chapter will also feature case studies and expert insights from leading healthcare organizations that have successfully navigated the AI adoption process. These examples will provide practical lessons and real-life scenarios to help readers anticipate challenges and proactively design solutions. Each chapter will be organized into similar sections for each organization’s case study: Strategy and Vision for AI, Implementation Best Practices, Initial Results, Challenges and Future Opportunities.

Zielgruppe

Professional Practice & Development

Autoren/Hrsg.

Langabeer, James R

Langabeer PhD, James R.

Lalani, Karima

Lalani PhD, Karima

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie Medizinische Biotechnologie
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Gesundheitswirtschaft
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Informationstheorie, Kodierungstheorie
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein
• Wirtschaftswissenschaften Betriebswirtschaft Management Wissensmanagement

Inhaltsverzeichnis

Part 1: Transforming the Continuum of Care Chapter 1. Towards AI and Human Collaboration Chapter 2. AI in Healthcare and Medicine: Shaping the Future Chapter 3. Unlocking the Power of AI in Transforming Patient Access and Staff Engagement Chapter 4. Delivering AI responsibly in clinical settings across the health continuum Chapter 5. Reimagining Primary and Specialty Care with AI Part 2: AI Across the Healthcare Ecosystem Chapter 6. Impact of AI on Dentistry Chapter 7. Leveraging Artificial Intelligence in Substance Use Outreach and Treatment Chapter 8. AI and Radiology: Shaping the Present, Defining the Future Chapter 9. The Expanding Role of AI in Life Sciences Innovation Part 3. AI for Smarter Healthcare Operations Chapter 10. AI-Driven Innovations in Healthcare Finance Chapter 11. The Role of AI in Mitigating Healthcare Fraud Chapter 12. AI and the Health Information Workforce Chapter 13. Building AI Readiness Across the Health Workforce Appendix A: Key Terminology

Über Autor(innen)

Dr. James Langabeer is an experienced healthcare professor and leader, passionate about creating and innovating strategic and efficient healthcare systems. Trained as a behavioral decision scientist, he is a prominent researcher in strategic and operational decision-making. He is also the Managing Partner of Yellowstone Research, an independent consultancy providing healthcare strategy consulting, and a clinical leader and tenured Professor at the University of Texas Health Science Center at Houston. His thoughts have been featured in Oprah, Forbes, MoneyGeek, Texas Monthly, NBC, Fox, CBS News, and NPR among others, and he has published well over 100 peer-reviewed journal articles and 7 books. He is a former national Chair of the American Heart Association Ambulatory Quality Committee and sits on multiple healthcare advisory boards. He holds a PhD in Management Science from the University of Lancaster in England, a Doctor of Education in leadership and organizational psychology from the University of Houston, an MBA from Baylor University, and he has achieved Fellow status in HIMSS, ACHE, and the American Heart Association.

Dr. Karima Lalani is the Program Director of the Health Informatics and Health Information Management program, and an Assistant Teaching Professor of Health Systems and Population Health, at the University of Washington School of Public Health.

Dr. Lalani holds a Ph.D. in Health Policy and Management, and is a seasoned healthcare management researcher and professional, with over 15 years of experience in healthcare workforce education and training, strategic planning, and digital health. She is a Registered Health Information Administrator (RHIA), and a Fellow of the American College of Healthcare Executives (FACHE).

Dr. Lalani’s research interests include health informatics, digital health, workforce development, interprofessional education, COVID-19’s impact on mental health of first responders and healthcare workers, and teaching hospitals. As a doctoral student, she studied the financial performance of all major teaching hospitals in the U.S. and continues to research and publish in this area.

Prior to joining the UW, Dr. Lalani was an Assistant Professor at The University of Texas Health Science Center at Houston (UTHealth Houston) School of Biomedical Informatics and the Assistant Director of Center for Health Systems Analytics at UTHealth Houston, where she was responsible for overseeing and managing the Center’s multidisciplinary research projects on substance use and mental health, as well as for creating opportunities and developing partnerships for expanding the Center’s thought leadership on public health challenges, healthcare quality and inter-organizational collaborations.

As an Assistant Professor at UTHealth, Dr. Lalani taught courses on Healthcare Leadership, Public Health Informatics, Scholarly Research Foundations, and Telehealth. Prior to UTHealth, Dr. Lalani was faculty at Texas State University in Health Information Management, where she taught courses on Organizational Management of Health Information Technology, as well as Technical and Legal Aspects of Health Information Management, and was recognized with multiple Excellence in Teaching awards.