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Most industries have plunged into data automation, but health care organizations have lagged in moving patients' medical records from paper to computers. In its first edition, this book presented a blueprint for introducing the computer-based patient record (CPR). The revised edition adds new information to the original book. One section describes recent developments, including the creation of a computer-based patient record institute. An international chapter highlights what is new in this still-emerging technology. An expert committee explores the potential of machine-readable CPRs to improve diagnostic and care decisions, provide a database for policymaking, and much more, addressing these key questions: Who uses patient records? What technology is available and what further research is necessary to meet users' needs? What should government, medical organizations, and others do to make the transition to CPRs? The volume also explores such issues as privacy and confidentiality, costs, the need for training, legal barriers to CPRs, and other key topics.
The workplace is where 156 million working adults in the United States spend many waking hours, and it has a profound influence on health and well-being. Although some occupations and work-related activities are more hazardous than others and face higher rates of injuries, illness, disease, and fatalities, workers in all occupations face some form of work-related safety and health concerns. Understanding those risks to prevent injury, illness, or even fatal incidents is an important function of society. Occupational safety and health (OSH) surveillance provides the data and analyses needed to understand the relationships between work and injuries and illnesses in order to improve worker safety and health and prevent work-related injuries and illnesses. Information about the circumstances in which workers are injured or made ill on the job and how these patterns change over time is essential to develop effective prevention programs and target future research. The nation needs a robust OSH surveillance system to provide this critical information for informing policy development, guiding educational and regulatory activities, developing safer technologies, and enabling research and prevention strategies that serves and protects all workers. A Smarter National Surveillance System for Occupational Safety and Health in the 21st Century provides a comprehensive assessment of the state of OSH surveillance. This report is intended to be useful to federal and state agencies that have an interest in occupational safety and health, but may also be of interest broadly to employers, labor unions and other worker advocacy organizations, the workers' compensation insurance industry, as well as state epidemiologists, academic researchers, and the broader public health community. The recommendations address the strengths and weaknesses of the envisioned system relative to the status quo and both short- and long-term actions and strategies needed to bring about a progressive evolution of the current system.
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Prolonged life expectancy along with the increasing complexity of medicine and health services raises health costs worldwide dramatically. Whilst the smart health concept has much potential to support the concept of the emerging P4-medicine (preventive, participatory, predictive, and personalized), such high-tech medicine produces large amounts of high-dimensional, weakly-structured data sets and massive amounts of unstructured information. All these technological approaches along with “big data” are turning the medical sciences into a data-intensive science. To keep pace with the growing amounts of complex data, smart hospital approaches are a commandment of the future, necessitating context aware computing along with advanced interaction paradigms in new physical-digital ecosystems. The very successful synergistic combination of methodologies and approaches from Human-Computer Interaction (HCI) and Knowledge Discovery and Data Mining (KDD) offers ideal conditions for the vision to support human intelligence with machine learning. The papers selected for this volume focus on hot topics in smart health; they discuss open problems and future challenges in order to provide a research agenda to stimulate further research and progress.