Subject heading search terms: Medical care AND Information services, Medical care--evaluation, medical care AND data mining, Medical informatics--Data processing, Medicine--Research, medical statistics, Outcome assessment (Medical care); Keyword search terms: data collection AND health care.
Achieving Person-Centred Health Systems: Evidence, Strategies and Challenges by
The idea of person-centred health systems is widely advocated in political and policy declarations to better address health system challenges. A person-centred approach is advocated on political, ethical and instrumental grounds and believed to benefit service users, health professionals and the health system more broadly. However, there is continuing debate about the strategies that are available and effective to promote and implement 'person-centred' approaches. This book brings together the world's leading experts in the field to present the evidence base and analyse current challenges and issues. It examines 'person-centredness' from the different roles people take in health systems, as individual service users, care managers, taxpayers or active citizens. The evidence presented will not only provide invaluable policy advice to practitioners and policymakers working on the design and implementation of person-centred health systems but will also be an excellent resource for academics and graduate students researching health systems in Europe. This title is available as Open Access on Cambridge Core.
Advances in Telemedicine for Health Monitoring: Technologies, Design and Applications by
Advances in telemedicine technologies have offered clinicians greater levels of real-time guidance and technical assistance for diagnoses, monitoring, operations or interventions from colleagues based in remote locations. The topic includes the use of videoconferencing, mentorship during surgical procedures, or machine-to-machine communication to process data from one location by programmes running in another.
Big Data Analytics for Healthcare: Datasets, Techniques, Life Cycles, Management, and Applications by
Big Data Analytics and Medical Information Systems presents the valuable use of artificial intelligence and big data analytics in healthcare and medical sciences. It focuses on theories, methods and approaches in which data analytic techniques can be used to examine medical data to provide a meaningful pattern for classification, diagnosis, treatment, and prediction of diseases. The book discusses topics such as theories and concepts of the field, and how big medical data mining techniques and applications can be applied to classification, diagnosis, treatment, and prediction of diseases. In addition, it covers social, behavioral, and medical fake news analytics to prevent medical misinformation and myths. It is a valuable resource for graduate students, researchers and members of biomedical field who are interested in learning more about analytic tools to support their work.
Building Data Capacity for Patient-Centered Outcomes Research: Priorities for the Next Decade by
The Office of the Assistant Secretary for Planning and Evaluation (ASPE), in partnership with other agencies and divisions of the United States Department of Health and Human Services, coordinates a portfolio of projects that build data capacity for conducting patient-centered outcomes research (PCOR). PCOR focuses on producing scientific evidence on the effectiveness of prevention and treatment options to inform the health care decisions of patients, families, and health care providers, taking into consideration the preferences, values, and questions patients face when making health care choices. ASPE asked the National Academies to appoint a consensus study committee to identify issues critical to the continued development of the data infrastructure for PCOR. Building Data Capacity for Patient-Centered Outcomes Research contains findings and conclusions in the areas that could benefit from being prioritized as part of ASPE's work, and offers input on strengthening the overall framework for building the data infrastructure over the coming years. The committee authoring this report also issued three interim reports, which summarized discussions from three workshops, and are included as appendices in the final report.
Challenges of Trustable AI and Added-Value on Health: : Proceedings of MIE 2022 by
Artificial Intelligence (AI) in healthcare promises to improve the accuracy of diagnosis and screening, support clinical care, and assist in various public health interventions such as disease surveillance, outbreak response, and health system management. But the increasing importance of AI in healthcare means that trustworthy AI is vital to achieve the beneficial impacts on health anticipated by both health professionals and patients.This book presents the proceedings of the 32nd Medical Informatics Europe Conference (MIE2022), organized by the European Federation for Medical Informatics (EFMI) and held from 27 - 30 May 2022 in Nice, France. The theme of the conference was Challenges of Trustable AI and Added-Value on Health. Over 400 submissions were received from 43 countries, and were reviewed in a thorough process by at least three reviewers before being assessed by an SPC co-chair, with papers requiring major revision undergoing further review. Included here are 147 full papers (acceptance rate 54%), 23 short papers and 79 posters from the conference. Topics covered include the usual sub-domains of biomedical informatics: decision support and clinical information systems; clinical research informatics; knowledge management and representation; consumer health informatics; natural language processing; public health informatics; and privacy, ethical and societal aspects, but also innovative approaches to the collection, such as organization and analysis of data and knowledge related to health and wellbeing, as well as theoretical and applied contributions to AI methods and algorithms. Providing an overview of the latest developments in medical informatics, the book will be of interest to all those involved in the development and provision of healthcare today.
The Clinician's Handbook on Measurement-Based Care: The How, the What, and the Why Bother by
Measurement-based care, for many busy clinicians, may sound like just another time-intensive, potentially costly venture. Or worse, they may even see it as an affront to their own clinical judgment. But as this new, supremely practical volume reveals, the systematic collection of data is a critical component for delivering high-quality, high-value care, treatment, and services. Written in a style accessible to professionals across the spectrum of behavioral health care and human services, this guide leverages the authors' advanced training and extensive experience in clinical psychology and program leadership to describe: * The basic definition of measurement-based care* How to choose appropriate measures and design a methodology* How to choose psychometrically sound scales (the volume includes an easily referenced compendium of MBC scales organized by mental health concern)* How to aggregate patient data and analyze the information By breaking measurement-based care down into steps that are easy to both understand and implement, The Clinician's Handbook on Measurement-Based Care underscores not only the benefit to patients--strengthening the therapeutic alliance, reinforcing patient progress, and improving clinical outcomes--but also its potential advantages at the practice level, including improving program fidelity, demonstrating value to third parties, and improving the overall quality and safety of services provided to all individuals serviced by the clinician or the organization.
Enhancing Scientific Reproducibility in Biomedical Research Through Transparent Reporting: Proceedings of a Workshop by
Sharing knowledge is what drives scientific progress - each new advance or innovation in biomedical research builds on previous observations. However, for experimental findings to be broadly accepted as credible by the scientific community, they must be verified by other researchers. An essential step is for researchers to report their findings in a manner that is understandable to others in the scientific community and provide sufficient information for others to validate the original results and build on them. In recent years, concern has been growing over a number of studies that have failed to replicate previous results and evidence from larger meta-analyses, which have pointed to the lack of reproducibility in biomedical research. On September 25 and 26, 2019, the National Academies of Science, Engineering, and Medicine hosted a public workshop in Washington, DC, to discuss the current state of transparency in the reporting of preclinical biomedical research and to explore opportunities for harmonizing reporting guidelines across journals and funding agencies. Convened jointly by the Forum on Drug Discovery, Development, and Translation; the Forum on Neuroscience and Nervous System Disorders; the National Cancer Policy Forum; and the Roundtable on Genomics and Precision Health, the workshop primarily focused on transparent reporting in preclinical research, but also considered lessons learned and best practices from clinical research reporting. This publication summarizes the presentation and discussion of the workshop.
High Performance Computing for Intelligent Medical Systems by
The interface of high-performance computing, computational intelligence and medical science creates intelligent medical systems which offer significant improvements in the quality of life and efficacy of clinical treatment. This book reviews advances and applications of high-performance computing for medical applications.
Improving Health Care Quality: Case Studies with JMP by
Learn how to improve the quality of health care offered by your institution using data you already have Improving Health Care Quality: Case Studies with JMP® teaches readers how to systematically identify problems, collect and interpret data, and solve issues in the real world. Relying on JMP® software, the authors walk readers through the process of applying quality improvement techniques to real-life health care problems. The case studies provided in the book vary significantly and provide a wide-ranging view of the application of quality improvement techniques in the health care field. Studies regarding length of stay of diabetes patients to benchmarking the costs of hip replacement all serve to illuminate and explain the underlying concepts of statistical analysis. The authors break each case study down into several sections, including: Background and Task Data and Data Management Analysis Summary Concepts and Tools Exercises and Discussion Questions Each section reinforces the lessons learned in each case study and helps the reader learn to apply statistical data to their own health care quality problems.
Life Cycle Decisions for Biomedical Data: The Challenge of Forecasting Costs by
Biomedical research results in the collection and storage of increasingly large and complex data sets. Preserving those data so that they are discoverable, accessible, and interpretable accelerates scientific discovery and improves health outcomes, but requires that researchers, data curators, and data archivists consider the long-term disposition of data and the costs of preserving, archiving, and promoting access to them. Life Cycle Decisions for Biomedical Data examines and assesses approaches and considerations for forecasting costs for preserving, archiving, and promoting access to biomedical research data. This report provides a comprehensive conceptual framework for cost-effective decision making that encourages data accessibility and reuse for researchers, data managers, data archivists, data scientists, and institutions that support platforms that enable biomedical research data preservation, discoverability, and use.
Machine Learning, Big Data, and IoT for Medical Informatics by
Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics. In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data. This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT.
Medical Knowledge Extraction from Big Data by
Data mining refers to the activity of going through big data sets to look for relevant information. As human health care data are the most difficult of all data to collect and their primary direction is the treatment of patients, and secondarily dealing with research, almost the only vindication for collecting medical data is to benefit the disease. All data miners should take into account that Medical Knowledge Extraction is internally connected with the Evidence-Based Medical approach because it uses data for already treated or not patients and there are times that opposites to Guideline Based medical practice. Additonally all researchers should be aware when are dealing with medical databases they may face the possibility that their work will never be accepted or even used from health care professionals if all these obligations will not be correctly addressed from the early beginning. In the present book, one can find after the three introductory chapters, a number of successfully evaluated applications that have been developed after mining approaches in Big or smaller amount (according to the application) of medical Data in different fields of every day clinical practice from teams of experts. The challenging adventure of Medical Knowledge Extraction can be followed by ambitious researchers finally resulting in a successful decision support system, that some times is so novel that it will provide new directions for basic or clinical research further that the existed. At least this procedure will save the experience of the best doctors on duty and will help young residents to be better and better.
Medical Statistics from Scratch: An Introduction for Health Professionals by
Correctly understanding and using medical statistics is a key skill for all medical students and health professionals. In an informal and friendly style, Medical Statistics from Scratch provides a practical foundation for everyone whose first interest is probably not medical statistics. Keeping the level of mathematics to a minimum, it clearly illustrates statistical concepts and practice with numerous real-world examples and cases drawn from current medical literature. Medical Statistics from Scratch is an ideal learning partner for all medical students and health professionals needing an accessible introduction, or a friendly refresher, to the fundamentals of medical statistics.
Primary Care Medicine: Office Evaluation and Management of the Adult Patient by
Presented in companion electronic format updated quarterly, its problem-based orientation spans the full spectrum of problems encountered in adult primary care practice. Chapters address screening, diagnosis, prevention and management, including indications for referral and approaches to patient education and shared decision making. Clear, practical, bulleted recommendations and an extensive annotated bibliography of best references follow detailed discussions of pathophysiology, clinical presentation, differential diagnosis, and strategies for workup and treatment. Now with its 40th-anniversary edition, this exceptional text is a must-have resource for physicians, nurse practitioners, physician assistants, students, and residents- offering the most complete and up-to-date resource available for primary care education and practice. Included interactive eBook incorporates quarterly updates featuring critically reviewed important new evidence as well as a study guide for students and tables for shared decision making. Fully updated chapter content based on nearly 4,000 new references and real-world advice in bulleted form at the end of each chapter ensure current, easily accessible, evidence-based point-of-care decision support. Unique problem-based chapter organization covers the spectrum of adult primary care, highlighted by more than 400 tables, figures, and photographs, many in color. Chapters present actionable, scientifically validated guidance that allows physicians to go beyond standard consensus guidelines and provide highly personalized care. Best evidence is integrated with considerations of affordability, cost-effectiveness, convenience, and patient preference. Special consideration is given to team-based approaches of primary care delivery, recognizing its increasing importance to achieving high levels of practice performance. Enrich Your eBook Reading Experience Read directly on your preferred device(s), such as computer, tablet, or smartphone. Easily convert to audiobook, powering your content with natural language text-to-speech.
Public Health and Informatics: Proceedings of MIE 2021 by
For several years now, both eHealth applications and digitalization have been seen as fundamental to the new era of health informatics and public health. The current pandemic situation has also highlighted the importance of medical informatics for the scientific process of evidence-based reasoning and decision making at all levels of healthcare.This book presents the accepted full papers, short papers, and poster papers delivered as part of the 31st Medical Informatics in Europe Conference (MIE 2021), held virtually from 29-31 May 2021. MIE 2021 was originally due to be held in Athens, Greece, but due to the continuing pandemic situation, the conference was held as a virtual event. The 261 papers included here are grouped into 7 chapters: biomedical data, tools and methods; supporting care delivery; health and prevention; precision medicine and public health; human factors and citizen centered digital health; ethics, legal and societal aspects; and posters.Providing a state-of-the-art overview of medical informatics from around the world, the book will be of interest to all those working with eHealth applications and digitalization to improve the delivery of healthcare today.
Qualitative Research in Health Care by
Provides the essential information that health care researchers and health professionals need to understand the basics of qualitative research Now in its fourth edition, this concise, accessible, and authoritative introduction to conducting and interpreting qualitative research in the health care field has been fully revised and updated. Continuing to introduce the core qualitative methods for data collection and analysis, this new edition also features chapters covering newer methods which are becoming more widely used in the health research field; examining the role of theory, the analysis of virtual and digital data, and advances in participatory approaches to research. Qualitative Research in Health Care, 4th Edition looks at the interface between qualitative and quantitative research in primary mixed method studies, case study research, and secondary analysis and evidence synthesis. The book further offers chapters covering: different research designs, ethical issues in qualitative research; interview, focus group and observational methods; and documentary and conversation analysis. A succinct, and practical guide quickly conveying the essentials of qualitative research Updated with chapters on new and increasingly used methods of data collection including digital and web research Features new examples and up-to-date references and further reading The fourth edition of Qualitative Research in Health Care is relevant to health care professionals, researchers and students in health and related disciplines.
Recent Advances in Medical Statistics by
This book illustrates the use of complex statistical models in medical and health sciences. The use of these models by researchers contributes to the understanding of more complex processes and thus advances knowledge. The various chapters describe how an ordinal logistic model is applied to disabilities, a model in structural equations to an emergency code, multi-state models for the analysis of time-to-event data and Copula models to agitation-sedation scores, spatial models to epidemiology, and statistical methods to clinical trials and to N-of-1 trial design.
Reorienting Health Care and Business Sector Investment Priorities Toward Health and Well-Being: Proceedings of a Workshop by
On December 3, 2018, the National Academies of Sciences, Engineering, and Medicine convened a workshop, hosted by New York University (NYU) Langone Health in New York City, to explore how evolving concepts of value in health care and business investments are leading to a shift in resources toward investments in health and well-being for all. Workshop participants explored what industry leaders are doing to make progress and avoid pitfalls, tools and platforms that are useful to these efforts, and lessons and insights that stakeholders can use to help reinforce the shift toward healthier investments. This publication summarizes the presentations and discussions from the workshop.
Statistics in Medicine by
Statistics in Medicine, Fourth Edition, helps medical and biomedical investigators design and answer questions about analyzing and interpreting data and predicting the sample size required to achieve useful results. It makes medical statistics easy for the non-biostatistician by outlining common methods used in 90% of medical research. The text covers how to plan studies from conception to publication, what to do with data, and follows with step-by-step instructions for biostatistical methods from the simplest levels, to more sophisticated methods now used in medical articles. Examples from almost every medical specialty, and from dentistry, nursing, pharmacy and health care management are provided. This book does not require background knowledge of statistics or mathematics beyond high school algebra and provides abundant clinical examples and exercises to reinforce concepts. It is a valuable source for biomedical researchers, healthcare providers and anyone who conducts research or quality improvement projects.