The critical care unit manages patients with a vast range of disease and injuries affecting every organ system. The unit can initially be a daunting environment, with complex monitoring equipment producing large volumes of clinical data. Core Topics in Critical Care Medicine is a practical, comprehensive, introductory-level text for any clinician in their first few months in the critical care unit. It guides clinicians in both the initial assessment and the clinical management of all CCU patients, demystifying the critical care unit and providing key knowledge in a concise and accessible manner. The full spectrum of disorders likely to be encountered in critical care are discussed, with additional chapters on transfer and admission, imaging in the CCU, structure and organisation of the unit, and ethical and legal issues. Written by Critical Care experts, Core Topics in Critical Care Medicine provides comprehensive, concise and easily accessible information for all trainees.

This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.

Recent technological innovations - influenced primarily by the development of more sophisticated, faster and cheaper computer systems - permitted also the evolution of more affordable systems for Patient Data Management, so called PDM-Systems. The experience of the authors, on one of the first PDMS installation sites in Europe, shows that the purchase of such a system is not an easy task, since accurate data are not available in a comparable format. Therefore the first part of the book is devoted to a comparison of already installed, commercially distributed bedside based PDMS with regard to their specifications, functions and performance. The methods included a questionnaire with detailed questions for the vendors to answer and a "table of functions” comparing the most important functions which should be included in a PDMS. With that list the different systems (which were all in clinical use) were checked for the availability and the way of use of these functions. To evaluate variations in the systems performance an "information retrieval test” was designed and executed. In the second part the different vendors, whose systems were included in the study, were to describe the systems from their viewpoints. The third part contains papers describing the users’ experiences. The fourth and last part shows how to use PDMS-data for scientific and therapeutic purposes including two papers on clinical expert systems. Thus, this book provides valuable information for clinicians and hospital managers who have to decide on the purchase of a Patient Data Management System.

This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.

A database is in principle just a large collection of related or separate data, systematically stored in a computer. It should be possible for the data to be easily entered into the database-structure and afterwards also easily read, corrected and processed. The later analysis of data from such a database is greatly enhanced by the availability of special query languages and statistical analysis programs, not only for serial items but also for large combinations of data. Query languages, such as SQL (Structured Query Language) developed especially for these purposes, make databases easily accessible, also to researchers who may not be very well versed in computer programming. The cardiological/medical clinician and researcher of today is of necessity confronted more and more with computer-based data storage. Interest is of course focused primarily on the clinical use of such databases more than on the technical design itself, except for some very specific, personalized applications. For the latter approach, there are at present many software packages commercially available, especially designed for use in the personal computer environment. This book is comprised out of a number of contributions by various authors with differing backgrounds and from many different countries. The editors, being a cardiologist and an information scientist, have strived to achieve an equilibrium between these two fields. The chapters in this book form a cross-section of the many approaches to database design and implementation in the area of cardiology.

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 papers presented are refereed and from all over the world. They reflect the breadth and depth of the field of biomedical and health informatics, covering topics such as; health information systems, knowledge and data management, education, standards, consumer health and human factors, emerging technologies, sustainability, organizational and economic issues, genomics, and image and signal processing. As this volume carries such a wide collection, it will be of great interest to anyone engaged in biomedical and health informatics research and application.