PATIENT CENTRIC BLOOD SAMPLING AND QUANTITATIVE ANALYSIS Authoritative resource providing a complete overview of patient centric blood sampling, as well as its benefits and challenges Patient Centric Blood Sampling and Quantitative Analysis focuses on the growing interest in alternative means to standard phlebotomy and analytical workflows for the collection and analysis of high-quality human biological samples for the quantitative determination of circulating drugs, their metabolites, and endogenous substances for clinical trials, routine healthcare and neonatal screening. The book clearly explains the benefits and constraints of having patients collect small volumes of blood in locations outside of a clinic (e.g at home), including: patient convenience; less invasive procedures; increased frequency of sampling; applicability to collecting samples from the young, elderly, and those in remote locations; greater frequency; and lower cost per sample. Readers will learn about approaches for successfully implementing patient centric sampling workflows in a number of scenarios, including the clinical setting and in the analytical laboratory. Edited by four recognized experts in this field, with additional specialists in the discipline enlisted to write the component chapters, enabling greater depth and detail to be added and further raising the scientific standing of the publication, Patient Centric Blood Sampling and Quantitative Analysis includes information on: Basics of patient centric blood sampling and techniques and approaches that are available and in development for the collection and analysis of the samples Science behind patient centric blood sampling and its implications regarding human healthcare and wellbeing Application areas of patient centric sampling, including drug development, clinical chemistry/pathology, therapeutic drug monitoring, and more Practical approaches to successful implementation for existing and developing purposes and workflows, and case studies to support implementation within an organization Giving the reader a broad understanding of what patient centric sampling is and where it might be applied for existing and potential future areas, Patient Centric Blood Sampling and Quantitative Analysis is an essential resource on the subject for many different types of laboratories, areas of clinical research and healthcare, including those in pharmaceutical, clinical, and research functions.

PATIENT CENTRIC BLOOD SAMPLING AND QUANTITATIVE ANALYSIS Authoritative resource providing a complete overview of patient centric blood sampling, as well as its benefits and challenges Patient Centric Blood Sampling and Quantitative Analysis focuses on the growing interest in alternative means to standard phlebotomy and analytical workflows for the collection and analysis of high-quality human biological samples for the quantitative determination of circulating drugs, their metabolites, and endogenous substances for clinical trials, routine healthcare and neonatal screening. The book clearly explains the benefits and constraints of having patients collect small volumes of blood in locations outside of a clinic (e.g at home), including: patient convenience; less invasive procedures; increased frequency of sampling; applicability to collecting samples from the young, elderly, and those in remote locations; greater frequency; and lower cost per sample. Readers will learn about approaches for successfully implementing patient centric sampling workflows in a number of scenarios, including the clinical setting and in the analytical laboratory. Edited by four recognized experts in this field, with additional specialists in the discipline enlisted to write the component chapters, enabling greater depth and detail to be added and further raising the scientific standing of the publication, Patient Centric Blood Sampling and Quantitative Analysis includes information on: Basics of patient centric blood sampling and techniques and approaches that are available and in development for the collection and analysis of the samples Science behind patient centric blood sampling and its implications regarding human healthcare and wellbeing Application areas of patient centric sampling, including drug development, clinical chemistry/pathology, therapeutic drug monitoring, and more Practical approaches to successful implementation for existing and developing purposes and workflows, and case studies to support implementation within an organization Giving the reader a broad understanding of what patient centric sampling is and where it might be applied for existing and potential future areas, Patient Centric Blood Sampling and Quantitative Analysis is an essential resource on the subject for many different types of laboratories, areas of clinical research and healthcare, including those in pharmaceutical, clinical, and research functions.

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.

Getting the right diagnosis is a key aspect of health care - it provides an explanation of a patient's health problem and informs subsequent health care decisions. The diagnostic process is a complex, collaborative activity that involves clinical reasoning and information gathering to determine a patient's health problem. According to Improving Diagnosis in Health Care, diagnostic errors-inaccurate or delayed diagnoses-persist throughout all settings of care and continue to harm an unacceptable number of patients. It is likely that most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences. Diagnostic errors may cause harm to patients by preventing or delaying appropriate treatment, providing unnecessary or harmful treatment, or resulting in psychological or financial repercussions. The committee concluded that improving the diagnostic process is not only possible, but also represents a moral, professional, and public health imperative. Improving Diagnosis in Health Care, a continuation of the landmark Institute of Medicine reports To Err Is Human (2000) and Crossing the Quality Chasm (2001), finds that diagnosis-and, in particular, the occurrence of diagnostic errorsâ€"has been largely unappreciated in efforts to improve the quality and safety of health care. Without a dedicated focus on improving diagnosis, diagnostic errors will likely worsen as the delivery of health care and the diagnostic process continue to increase in complexity. Just as the diagnostic process is a collaborative activity, improving diagnosis will require collaboration and a widespread commitment to change among health care professionals, health care organizations, patients and their families, researchers, and policy makers. The recommendations of Improving Diagnosis in Health Care contribute to the growing momentum for change in this crucial area of health care quality and safety.

An informative and comprehensive book on the applications and techniques of dried blood spot sampling Dried blood spot (DBS) sampling involves the collection of a small volume of blood, via a simple prick or other means, from a study subject onto a cellulose or polymer paper card, which is followed by drying and transfer to the laboratory for analysis. For many years, this method of blood sample collection has been extensively utilized in some important areas of human healthcare (for example, newborn screening for inherited metabolic disorders and HIV-related epidemiological studies). Because of its advantages over conventional blood, plasma, or serum sample collection, DBS sampling has been valued by the pharmaceutical industry in drug research and development. Dried Blood Spots: Applications and Techniques features contributions from an international team of leading scientists in the field. Their contributions present a unique resource on the history, principles, procedures, methodologies, applications, and emerging technologies related to DBS. Presented in three parts, the book thoroughly examines: Applications of DBS sampling and associated procedures and methodologies in various human healthcare studies Applications and perspectives of DBS sampling in drug research and development, and therapeutic drug monitoring New technologies and emerging applications related to DBS sampling and analysis Dried Blood Spots: Applications and Techniques is a valuable working guide for researchers, professionals, and students in healthcare, medical science, diagnostics, clinical chemistry, and pharmaceuticals, etc.

Data sharing can accelerate new discoveries by avoiding duplicative trials, stimulating new ideas for research, and enabling the maximal scientific knowledge and benefits to be gained from the efforts of clinical trial participants and investigators. At the same time, sharing clinical trial data presents risks, burdens, and challenges. These include the need to protect the privacy and honor the consent of clinical trial participants; safeguard the legitimate economic interests of sponsors; and guard against invalid secondary analyses, which could undermine trust in clinical trials or otherwise harm public health. Sharing Clinical Trial Data presents activities and strategies for the responsible sharing of clinical trial data. With the goal of increasing scientific knowledge to lead to better therapies for patients, this book identifies guiding principles and makes recommendations to maximize the benefits and minimize risks. This report offers guidance on the types of clinical trial data available at different points in the process, the points in the process at which each type of data should be shared, methods for sharing data, what groups should have access to data, and future knowledge and infrastructure needs. Responsible sharing of clinical trial data will allow other investigators to replicate published findings and carry out additional analyses, strengthen the evidence base for regulatory and clinical decisions, and increase the scientific knowledge gained from investments by the funders of clinical trials. The recommendations of Sharing Clinical Trial Data will be useful both now and well into the future as improved sharing of data leads to a stronger evidence base for treatment. This book will be of interest to stakeholders across the spectrum of research-from funders, to researchers, to journals, to physicians, and ultimately, to patients.

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

This is a comprehensive major reference work for our SpringerReference program covering clinical trials. Although the core of the Work will focus on the design, analysis, and interpretation of scientific data from clinical trials, a broad spectrum of clinical trial application areas will be covered in detail. This is an important time to develop such a Work, as drug safety and efficacy emphasizes the Clinical Trials process. Because of an immense and growing international disease burden, pharmaceutical and biotechnology companies continue to develop new drugs. Clinical trials have also become extremely globalized in the past 15 years, with over 225,000 international trials ongoing at this point in time. Principles in Practice of Clinical Trials is truly an interdisciplinary that will be divided into the following areas: 1) Clinical Trials Basic Perspectives 2) Regulation and Oversight 3) Basic Trial Designs 4) Advanced Trial Designs 5) Analysis 6) Trial Publication 7) Topics Related Specific Populations and Legal Aspects of Clinical Trials The Work is designed to be comprised of 175 chapters and approximately 2500 pages. The Work will be oriented like many of our SpringerReference Handbooks, presenting detailed and comprehensive expository chapters on broad subjects. The Editors are major figures in the field of clinical trials, and both have written textbooks on the topic. There will also be a slate of 7-8 renowned associate editors that will edit individual sections of the Reference.