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Author: Richard D. Riley
Publisher: Oxford University Press
ISBN: 0192516655
Category : Medical
Languages : en
Pages : 373
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Book Description
"What is going to happen to me?" Most patients ask this question during a clinical encounter with a health professional. As well as learning what problem they have (diagnosis) and what needs to be done about it (treatment), patients want to know about their future health and wellbeing (prognosis). Prognosis research can provide answers to this question and satisfy the need for individuals to understand the possible outcomes of their condition, with and without treatment. Central to modern medical practise, the topic of prognosis is the basis of decision making in healthcare and policy development. It translates basic and clinical science into practical care for patients and populations. Prognosis Research in Healthcare: Concepts, Methods and Impact provides a comprehensive overview of the field of prognosis and prognosis research and gives a global perspective on how prognosis research and prognostic information can improve the outcomes of healthcare. It details how to design, carry out, analyse and report prognosis studies, and how prognostic information can be the basis for tailored, personalised healthcare. In particular, the book discusses how information about the characteristics of people, their health, and environment can be used to predict an individual's future health. Prognosis Research in Healthcare: Concepts, Methods and Impact, addresses all types of prognosis research and provides a practical step-by-step guide to undertaking and interpreting prognosis research studies, ideal for medical students, health researchers, healthcare professionals and methodologists, as well as for guideline and policy makers in healthcare wishing to learn more about the field of prognosis.
Author: Richard D. Riley
Publisher: Oxford University Press
ISBN: 0192516655
Category : Medical
Languages : en
Pages : 373
Get Book Here
Book Description
"What is going to happen to me?" Most patients ask this question during a clinical encounter with a health professional. As well as learning what problem they have (diagnosis) and what needs to be done about it (treatment), patients want to know about their future health and wellbeing (prognosis). Prognosis research can provide answers to this question and satisfy the need for individuals to understand the possible outcomes of their condition, with and without treatment. Central to modern medical practise, the topic of prognosis is the basis of decision making in healthcare and policy development. It translates basic and clinical science into practical care for patients and populations. Prognosis Research in Healthcare: Concepts, Methods and Impact provides a comprehensive overview of the field of prognosis and prognosis research and gives a global perspective on how prognosis research and prognostic information can improve the outcomes of healthcare. It details how to design, carry out, analyse and report prognosis studies, and how prognostic information can be the basis for tailored, personalised healthcare. In particular, the book discusses how information about the characteristics of people, their health, and environment can be used to predict an individual's future health. Prognosis Research in Healthcare: Concepts, Methods and Impact, addresses all types of prognosis research and provides a practical step-by-step guide to undertaking and interpreting prognosis research studies, ideal for medical students, health researchers, healthcare professionals and methodologists, as well as for guideline and policy makers in healthcare wishing to learn more about the field of prognosis.
Author: Richard D. Riley
Publisher:
ISBN: 9780191837890
Category : Prognosis
Languages : en
Pages :
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Book Description
Author: Nicholas A. Christakis
Publisher: University of Chicago Press
ISBN: 9780226104713
Category : Medical
Languages : en
Pages : 354
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Book Description
This groundbreaking book explains prognosis from the perspective of doctors, examining why physicians are reluctant to predict the future, how doctors use prognosis, the symbolism it contains, and the emotional difficulties it involves. Drawing on his experiences as a doctor and sociologist, Nicholas Christakis interviewed scores of physicians and searched dozens of medical textbooks and medical school curricula for discussions of prognosis in an attempt to get to the core of this nebulous medical issue that, despite its importance, is only partially understood and rarely discussed. "Highly recommended for everyone from patients wrestling with their personal prognosis to any medical practitioner touched by this bioethical dilemma."—Library Journal, starred review "[T]he first full general discussion of prognosis ever written. . . . [A] manifesto for a form of prognosis that's equal parts prediction-an assessment of likely outcomes based on statistical averages-and prophecy, an intuition of what lies ahead."—Jeff Sharlet, Chicago Reader "[S]ophisticated, extraordinarily well supported, and compelling. . . . [Christakis] argues forcefully that the profession must take responsibility for the current widespread avoidance of prognosis and change the present culture. This prophet is one whose advice we would do well to heed."—James Tulsky, M.D., New England Journal of Medicine
Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 030921646X
Category : Medical
Languages : en
Pages : 217
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Book Description
Advances in medical, biomedical and health services research have reduced the level of uncertainty in clinical practice. Clinical practice guidelines (CPGs) complement this progress by establishing standards of care backed by strong scientific evidence. CPGs are statements that include recommendations intended to optimize patient care. These statements are informed by a systematic review of evidence and an assessment of the benefits and costs of alternative care options. Clinical Practice Guidelines We Can Trust examines the current state of clinical practice guidelines and how they can be improved to enhance healthcare quality and patient outcomes. Clinical practice guidelines now are ubiquitous in our healthcare system. The Guidelines International Network (GIN) database currently lists more than 3,700 guidelines from 39 countries. Developing guidelines presents a number of challenges including lack of transparent methodological practices, difficulty reconciling conflicting guidelines, and conflicts of interest. Clinical Practice Guidelines We Can Trust explores questions surrounding the quality of CPG development processes and the establishment of standards. It proposes eight standards for developing trustworthy clinical practice guidelines emphasizing transparency; management of conflict of interest ; systematic review-guideline development intersection; establishing evidence foundations for and rating strength of guideline recommendations; articulation of recommendations; external review; and updating. Clinical Practice Guidelines We Can Trust shows how clinical practice guidelines can enhance clinician and patient decision-making by translating complex scientific research findings into recommendations for clinical practice that are relevant to the individual patient encounter, instead of implementing a one size fits all approach to patient care. This book contains information directly related to the work of the Agency for Healthcare Research and Quality (AHRQ), as well as various Congressional staff and policymakers. It is a vital resource for medical specialty societies, disease advocacy groups, health professionals, private and international organizations that develop or use clinical practice guidelines, consumers, clinicians, and payers.
Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309164257
Category : Medical
Languages : en
Pages : 267
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Book Description
Healthcare decision makers in search of reliable information that compares health interventions increasingly turn to systematic reviews for the best summary of the evidence. Systematic reviews identify, select, assess, and synthesize the findings of similar but separate studies, and can help clarify what is known and not known about the potential benefits and harms of drugs, devices, and other healthcare services. Systematic reviews can be helpful for clinicians who want to integrate research findings into their daily practices, for patients to make well-informed choices about their own care, for professional medical societies and other organizations that develop clinical practice guidelines. Too often systematic reviews are of uncertain or poor quality. There are no universally accepted standards for developing systematic reviews leading to variability in how conflicts of interest and biases are handled, how evidence is appraised, and the overall scientific rigor of the process. In Finding What Works in Health Care the Institute of Medicine (IOM) recommends 21 standards for developing high-quality systematic reviews of comparative effectiveness research. The standards address the entire systematic review process from the initial steps of formulating the topic and building the review team to producing a detailed final report that synthesizes what the evidence shows and where knowledge gaps remain. Finding What Works in Health Care also proposes a framework for improving the quality of the science underpinning systematic reviews. This book will serve as a vital resource for both sponsors and producers of systematic reviews of comparative effectiveness research.
Author: Ewout W. Steyerberg
Publisher: Springer
ISBN: 3030163997
Category : Medical
Languages : en
Pages : 574
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Book Description
The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice. There is an increasing need for personalized evidence-based medicine that uses an individualized approach to medical decision-making. In this Big Data era, there is expanded access to large volumes of routinely collected data and an increased number of applications for prediction models, such as targeted early detection of disease and individualized approaches to diagnostic testing and treatment. Clinical Prediction Models presents a practical checklist that needs to be considered for development of a valid prediction model. Steps include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formatting. The text also addresses common issues that make prediction models suboptimal, such as small sample sizes, exaggerated claims, and poor generalizability. The text is primarily intended for clinical epidemiologists and biostatisticians. Including many case studies and publicly available R code and data sets, the book is also appropriate as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. While practical in nature, the book also provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling. Updates to this new and expanded edition include: • A discussion of Big Data and its implications for the design of prediction models • Machine learning issues • More simulations with missing ‘y’ values • Extended discussion on between-cohort heterogeneity • Description of ShinyApp • Updated LASSO illustration • New case studies
Author: Agency for Healthcare Research and Quality/AHRQ
Publisher: Government Printing Office
ISBN: 1587634333
Category : Medical
Languages : en
Pages : 385
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Book Description
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.
Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309113695
Category : Medical
Languages : en
Pages : 202
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Book Description
Drawing on the work of the Roundtable on Evidence-Based Medicine, the 2007 IOM Annual Meeting assessed some of the rapidly occurring changes in health care related to new diagnostic and treatment tools, emerging genetic insights, the developments in information technology, and healthcare costs, and discussed the need for a stronger focus on evidence to ensure that the promise of scientific discovery and technological innovation is efficiently captured to provide the right care for the right patient at the right time. As new discoveries continue to expand the universe of medical interventions, treatments, and methods of care, the need for a more systematic approach to evidence development and application becomes increasingly critical. Without better information about the effectiveness of different treatment options, the resulting uncertainty can lead to the delivery of services that may be unnecessary, unproven, or even harmful. Improving the evidence-base for medicine holds great potential to increase the quality and efficiency of medical care. The Annual Meeting, held on October 8, 2007, brought together many of the nation's leading authorities on various aspects of the issues - both challenges and opportunities - to present their perspectives and engage in discussion with the IOM membership.
Author: Kerm Henriksen
Publisher:
ISBN:
Category : Medical
Languages : en
Pages : 526
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Book Description
v. 1. Research findings -- v. 2. Concepts and methodology -- v. 3. Implementation issues -- v. 4. Programs, tools and products.
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
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Book Description
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
