Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital for hospitals and health systems to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. This book addresses several topics important to the understanding and use of data in healthcare. First, it provides a formal explanation based on epistemology (theory of knowledge) of what data actually is, what we can know about it, and how we can reason with it. The culture of data is also covered and where it fits into healthcare. Then, data quality is addressed, with a historical appreciation, as well as new concepts and insights derived from the author’s 35 years of experience in technology. The author provides a description of what healthcare data analysis is and how it is changing in the era of abundant data. Just as important is the topic of infrastructure and how it provides capability for data use. The book also describes how healthcare information infrastructure needs to change in order to meet current and future needs. The topics of artificial intelligence (AI) and machine learning in healthcare are also addressed. The author concludes with thoughts on the evolution of the role and use of data and information going into the future.

This book gives an in-depth philosophical analysis of moral problems to which information technology gives rise, for example, problems related to privacy, intellectual property, responsibility, friendship, and trust, with contributions from many of the best-known philosophers writing in the area.

The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.

This book provides a comprehensive and straightforward coverage of data processing and information technology. It is widely used as a course text on many professional and non-professional business and accountancy courses, and assumes no previous knowledge of the subject. This book provides a comprehensive and straightforward coverage of data processing and information technology. It is widely used as a course text on many professional and non-professional business and accountancy courses, and assumes no previous knowledge of the subject.

Computers, communications, digital information, softwareâ€"the constituents of the information ageâ€"are everywhere. Being computer literate, that is technically competent in two or three of today's software applications, is not enough anymore. Individuals who want to realize the potential value of information technology (IT) in their everyday lives need to be computer fluentâ€"able to use IT effectively today and to adapt to changes tomorrow. Being Fluent with Information Technology sets the standard for what everyone should know about IT in order to use it effectively now and in the future. It explores three kinds of knowledgeâ€"intellectual capabilities, foundational concepts, and skillsâ€"that are essential for fluency with IT. The book presents detailed descriptions and examples of current skills and timeless concepts and capabilities, which will be useful to individuals who use IT and to the instructors who teach them.

"This book presents theoretical and empirical research on the value of information technology in healthcare"--Provided by publisher.