Reinventing Clinical Decision Support


Book Description

This book takes an in-depth look at the emerging technologies that are transforming the way clinicians manage patients, while at the same time emphasizing that the best practitioners use both artificial and human intelligence to make decisions. AI and machine learning are explored at length, with plain clinical English explanations of convolutional neural networks, back propagation, and digital image analysis. Real-world examples of how these tools are being employed are also discussed, including their value in diagnosing diabetic retinopathy, melanoma, breast cancer, cancer metastasis, and colorectal cancer, as well as in managing severe sepsis. With all the enthusiasm about AI and machine learning, it was also necessary to outline some of criticisms, obstacles, and limitations of these new tools. Among the criticisms discussed: the relative lack of hard scientific evidence supporting some of the latest algorithms and the so-called black box problem. A chapter on data analytics takes a deep dive into new ways to conduct subgroup analysis and how it’s forcing healthcare executives to rethink the way they apply the results of large clinical trials to everyday medical practice. This re-evaluation is slowly affecting the way diabetes, heart disease, hypertension, and cancer are treated. The research discussed also suggests that data analytics will impact emergency medicine, medication management, and healthcare costs. An examination of the diagnostic reasoning process itself looks at how diagnostic errors are measured, what technological and cognitive errors are to blame, and what solutions are most likely to improve the process. It explores Type 1 and Type 2 reasoning methods; cognitive mistakes like availability bias, affective bias, and anchoring; and potential solutions such as the Human Diagnosis Project. Finally, the book explores the role of systems biology and precision medicine in clinical decision support and provides several case studies of how next generation AI is transforming patient care.




Fundamentals of Clinical Data Science


Book Description

This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.




The Digital Reconstruction of Healthcare


Book Description

The complex challenges facing healthcare are being met by the transitioning much patient care from hospitals, clinics, and offices to virtual settings. The digital reconstruction of medicine includes telemedicine, mobile apps, sensing devices, and other technologies. The book explores how these tools are meeting patient needs across the globe.




Healthcare Digital Transformation


Book Description

This book is a reference guide for healthcare executives and technology providers involved in the ongoing digital transformation of the healthcare sector. The book focuses specifically on the challenges and opportunities for health systems in their journey toward a digital future. It draws from proprietary research and public information, along with interviews with over one hundred and fifty executives in leading health systems such as Cleveland Clinic, Partners, Mayo, Kaiser, and Intermountain as well as numerous technology and retail providers. The authors explore the important role of technology and that of EHR systems, digital health innovators, and big tech firms in the ongoing digital transformation of healthcare. Importantly, the book draws on the accelerated learnings of the healthcare sector during the COVID-19 pandemic in their digital transformation efforts to adopt telehealth and virtual care models. Features of this book: Provides an understanding of the current state of digital transformation and the factors influencing the ongoing transformation of the healthcare sector. Includes interviews with executives from leading health systems. Describes the important role of emerging technologies; EHR systems, digital health innovators, and more. Includes case studies from innovative health organizations. Provides a set of templates and frameworks for developing and implementing a digital roadmap. Based on best practices from real-life examples, the book is a guidebook that provides a set of templates and frameworks for digital transformation practitioners in healthcare.




Healthcare Information Management Systems


Book Description

Aimed at health care professionals, this book looks beyond traditional information systems and shows how hospitals and other health care providers can attain a competitive edge. Speaking practitioner to practitioner, the authors explain how they use information technology to manage their health care institutions and to support the delivery of clinical care. This second edition incorporates the far-reaching advances of the last few years, which have moved the field of health informatics from the realm of theory into that of practice. Major new themes, such as a national information infrastructure and community networks, guidelines for case management, and community education and resource centres are added, while such topics as clinical and blood banking have been thoroughly updated.




Practical Data Analytics for Innovation in Medicine


Book Description

Practical Data Analytics for Innovation in Medicine: Building Real Predictive and Prescriptive Models in Personalized Healthcare and Medical Research Using AI, ML, and Related Technologies, Second Edition discusses the needs of healthcare and medicine in the 21st century, explaining how data analytics play an important and revolutionary role. With healthcare effectiveness and economics facing growing challenges, there is a rapidly emerging movement to fortify medical treatment and administration by tapping the predictive power of big data, such as predictive analytics, which can bolster patient care, reduce costs, and deliver greater efficiencies across a wide range of operational functions. Sections bring a historical perspective, highlight the importance of using predictive analytics to help solve health crisis such as the COVID-19 pandemic, provide access to practical step-by-step tutorials and case studies online, and use exercises based on real-world examples of successful predictive and prescriptive tools and systems. The final part of the book focuses on specific technical operations related to quality, cost-effective medical and nursing care delivery and administration brought by practical predictive analytics. Brings a historical perspective in medical care to discuss both the current status of health care delivery worldwide and the importance of using modern predictive analytics to help solve the health care crisis Provides online tutorials on several predictive analytics systems to help readers apply their knowledge on today’s medical issues and basic research Teaches how to develop effective predictive analytic research and to create decisioning/prescriptive analytic systems to make medical decisions quicker and more accurate




The Digital Reconstruction of Healthcare


Book Description

The complex challenges facing healthcare require innovative solutions that can make patient care more effective, easily available, and affordable. One such solution is the digital reconstruction of medicine that transitions much of patient care from hospitals, clinics, and offices to a variety of virtual settings. This reconstruction involves telemedicine, hospital-at-home services, mobile apps, remote sensing devices, clinical data analytics, and other cutting-edge technologies. The Digital Reconstruction of Healthcare: Transitioning from Brick and Mortar to Virtual Care takes a deep dive into these tools and how they can transform medicine to meet the unique needs of patients across the globe. This book enables readers to peer into the very near future and prepare them for the opportunities afforded by the digital shift in healthcare. It is also a wake-up call to readers who are less than enthusiastic about these digital tools and helps them to realize the cost of ignoring these tools. It is written for a wide range of medical professionals including: Physicians, nurses, and entrepreneurs who want to understand how to use or develop digital products and services IT managers who need to fold these tools into existing computer networks at hospitals, clinics, and medical offices Healthcare executives who decide how to invest in these platforms and products Insurers who need to stay current on the latest trends and the evidence to support their cost effectiveness Filled with insights from international experts, this book also features Dr. John Halamka’s lessons learned from years of international consulting with government officials on digital health. It also taps into senior research analyst Paul Cerrato’s expertise in AI, data analytics, and machine learning. Combining these lessons learned with an in-depth analysis of clinical informatics research, this book aims to separate hyped AI "solutions" from evidence-based digital tools. Together, these two pillars support the contention that these technologies can, in fact, help solve many of the seemingly intractable problems facing healthcare providers and patients.




The Transformative Power of Mobile Medicine


Book Description

The Transformative Power of Mobile Medicine: Leveraging Innovation, Seizing Opportunities, and Overcoming Obstacles of mHealth addresses the rapid advances taking place in mHealth and their impact on clinicians and patients. It provides guidance on reliable mobile health apps that are based on sound scientific evidence, while also offering advice on how to stay clear of junk science. The book explores the latest developments, including the value of blockchain, the emerging growth of remote sensors in chronic patient care, the potential use of Amazon Alexa and Google Assistant as patient bedside assistants, the use of Amazon's IoT button, and much more. This book enables physicians and nurses to gain a deep understanding of the strengths and weaknesses of mobile health and helps them choose evidence-based mobile medicine tools to improve patient care. - Provides clinicians and technologists with an update on the latest mobile health initiatives and tools, including the work done at Beth Israel Deaconess Medical Center/Harvard Medical School - Encompasses case studies with real-world examples to turn abstract concepts into flesh and blood examples of how mHealth benefits the public - Presents drawings, graphics and flow charts to help readers visualize the functionality and value of mobile medicine




Care After Covid: What the Pandemic Revealed Is Broken in Healthcare and How to Reinvent It


Book Description

A practical action plan for reinventing healthcare in a post-pandemic world—from a physician-entrepreneur who works with Fortune 500 companies. If the healthcare system were an emperor, Covid-19 tragically revealed that it had no clothes. Healthcare had to adapt, and quickly―sparking a dramatic acceleration of virtual care, drive-through testing, and home-based services. In the process, old rules were rewritten and, perhaps surprisingly, largely in a good way for patients. To succeed in the post-pandemic world, all of us―patients, caregivers, providers, employers, investors, technologists, and policymakers―need to understand the new healthcare landscape and change our strategies and behaviors accordingly. In Care After Covid, practicing physician and business leader Dr. Shantanu Nundy—Chief Medical Officer of Accolade, which provides technology-enabled health services to Fortune 500 companies as well as small businesses―lays out a comprehensive plan to transform healthcare along three dimensions: Distributed: healthcare will happen where health happens. It will shift from where doctors are to where patients are—at home, in the community, and increasingly on their phones. Digitally enabled: healthcare and the relationships that are central to care will be strengthened by data and technology. It will shift from being siloed to connected, from being episodic to continuous, from one-size-fits-all to more personalized. Decentralized: healthcare decisions and resources will be in the hands of those closest to care. The power to determine who gets care and how they get it will shift away from governments and insurance companies to communities, employers, doctors, and patients. Filled with firsthand insights and stories from the frontlines of healthcare—as well as innovative solutions that were proven effective before and during the pandemic—Care After Covid shows all stakeholders in the healthcare ecosystem exactly what needs to change and, more importantly, how to do it. The time to act is now. We can’t afford not to.




Clinical Decision Support and Beyond


Book Description

Clinical Decision Support and Beyond: Progress and Opportunities in Knowledge-Enhanced Health and Healthcare, now in its third edition, discusses the underpinnings of effective, reliable, and easy-to-use clinical decision support systems at the point of care as a productive way of managing the flood of data, knowledge, and misinformation when providing patient care. Incorporating CDS into electronic health record systems has been underway for decades; however its complexities, costs, and user resistance have lagged its potential. Thus it is of utmost importance to understand the process in detail, to take full advantage of its capabilities. The book expands and updates the content of the previous edition, and discusses topics such as integration of CDS into workflow, context-driven anticipation of needs for CDS, new forms of CDS derived from data analytics, precision medicine, population health, integration of personal monitoring, and patient-facing CDS. In addition, it discusses population health management, public health CDS and CDS to help reduce health disparities. It is a valuable resource for clinicians, practitioners, students and members of medical and biomedical fields who are interested to learn more about the potential of clinical decision support to improve health and wellness and the quality of health care. Presents an overview and details of the current state of the art and usefulness of clinical decision support, and how to utilize these capabilities Explores the technological underpinnings for developing, managing, and sharing knowledge resources and deploying them as CDS or for other uses Discusses the current drivers and opportunities that are expanding the prospects for use of knowledge to enhance health and healthcare