How To Report Statistics In Medicine

This volume presents a comprehensive and comprehensible set of guidelines for reporting the statistical analyses and research designs and activities commonly used in biomedical research.

Experts estimate that as many as 98,000 people die in any given year from medical errors that occur in hospitals. That's more than die from motor vehicle accidents, breast cancer, or AIDSâ€"three causes that receive far more public attention. Indeed, more people die annually from medication errors than from workplace injuries. Add the financial cost to the human tragedy, and medical error easily rises to the top ranks of urgent, widespread public problems. To Err Is Human breaks the silence that has surrounded medical errors and their consequenceâ€"but not by pointing fingers at caring health care professionals who make honest mistakes. After all, to err is human. Instead, this book sets forth a national agendaâ€"with state and local implicationsâ€"for reducing medical errors and improving patient safety through the design of a safer health system. This volume reveals the often startling statistics of medical error and the disparity between the incidence of error and public perception of it, given many patients' expectations that the medical profession always performs perfectly. A careful examination is made of how the surrounding forces of legislation, regulation, and market activity influence the quality of care provided by health care organizations and then looks at their handling of medical mistakes. Using a detailed case study, the book reviews the current understanding of why these mistakes happen. A key theme is that legitimate liability concerns discourage reporting of errorsâ€"which begs the question, "How can we learn from our mistakes?" Balancing regulatory versus market-based initiatives and public versus private efforts, the Institute of Medicine presents wide-ranging recommendations for improving patient safety, in the areas of leadership, improved data collection and analysis, and development of effective systems at the level of direct patient care. To Err Is Human asserts that the problem is not bad people in health careâ€"it is that good people are working in bad systems that need to be made safer. Comprehensive and straightforward, this book offers a clear prescription for raising the level of patient safety in American health care. It also explains how patients themselves can influence the quality of care that they receive once they check into the hospital. This book will be vitally important to federal, state, and local health policy makers and regulators, health professional licensing officials, hospital administrators, medical educators and students, health caregivers, health journalists, patient advocatesâ€"as well as patients themselves. First in a series of publications from the Quality of Health Care in America, a project initiated by the Institute of Medicine

This book deals with statistics in medicine in a simple way. The text is supported by abundant examples from medical data. This book aims to explain and simplify the process of data presentation. Further aspects addressed include how to design and conduct clinical trials, and how to write journal articles.

Statistical Methods in Laboratory Medicine focuses on the application of statistics in laboratory medicine. The book first ponders on quantitative and random variables, exploratory data analysis (EDA), probability, and probability distributions. Discussions focus on negative binomial distribution, non-random distributions, binomial distribution, fitting the binomial model to sample data, conditional probability and statistical independence, rules of probability, and Bayes' theorem. The text then examines inference, regression, and measurement and control. Topics cover analytical goals for assay precision, estimating the error variance components, indirect structural assays, functional assays, bivariate regression model, and least-squares estimates of the functional relation parameters. The manuscript takes a look at assay method comparison studies, multivariate analysis, forecasting and control, and test interpretation. Concerns include time series structure and terminology, polynomial regression, assessing the performance of the classification rule, quantitative screening tests, sample correlation coefficient, and computer assisted diagnosis. The book is a dependable reference for medical experts and statisticians interested in the employment of statistics in laboratory medicine.

As many medical and healthcare researchers have a love-hate relationship with statistics, the second edition of this practical reference book may make all the difference. Using practical examples, mainly from the authors' own research, the book explains how to make sense of statistics, turn statistical computer output into coherent information, and help decide which pieces of information to report and how to present them. The book takes you through all the stages of the research process, from the initial research proposal, through ethical approval and data analysis, to reporting on and publishing the findings. Helpful tips and information boxes, offer clear guidance throughout, including easily followed instructions on how to: -develop a quantitative research proposal for ethical/institutional approval or research funding -write up the statistical aspects of a paper for publication -choose and perform simple and more advanced statistical analyses -describe the statistical methods and present the results of an analysis. This new edition covers a wider range of statistical programs - SAS, STATA, R, and SPSS, and shows the commands needed to obtain the analyses and how to present it, whichever program you are using. Each specific example is annotated to indicate other scenarios that can be analysed using the same methods, allowing you to easily transpose the knowledge gained from the book to your own research. The principles of good presentation are also covered in detail, from translating relevant results into suitable extracts, through to randomised controlled trials, and how to present a meta-analysis. An added ingredient is the inclusion of code and datasets for all analyses shown in the book on our website (http://medical-statistics.info). Written by three experienced biostatisticians based in the UK and US, this is a step-by-step guide that will be invaluable to researchers and postgraduate students in medicine, those working in the professions allied to medicine, and statisticians in consultancy roles.

Praise for the First Edition " . . . the book is a valuable addition to the literature in thefield, serving as a much-needed guide for both clinicians andadvanced students."—Zentralblatt MATH A new edition of the cutting-edge guide to diagnostic tests inmedical research In recent years, a considerable amount of research has focusedon evolving methods for designing and analyzing diagnostic accuracystudies. Statistical Methods in Diagnostic Medicine, Second Editioncontinues to provide a comprehensive approach to the topic, guidingreaders through the necessary practices for understanding thesestudies and generalizing the results to patient populations. Following a basic introduction to measuring test accuracy andstudy design, the authors successfully define various measures ofdiagnostic accuracy, describe strategies for designing diagnosticaccuracy studies, and present key statistical methods forestimating and comparing test accuracy. Topics new to the SecondEdition include: Methods for tests designed to detect and locate lesions Recommendations for covariate-adjustment Methods for estimating and comparing predictive values andsample size calculations Correcting techniques for verification and imperfect standardbiases Sample size calculation for multiple reader studies when pilotdata are available Updated meta-analysis methods, now incorporating randomeffects Three case studies thoroughly showcase some of the questions andstatistical issues that arise in diagnostic medicine, with allassociated data provided in detailed appendices. A related web sitefeatures Fortran, SAS®, and R software packages so thatreaders can conduct their own analyses. Statistical Methods in Diagnostic Medicine, Second Edition is anexcellent supplement for biostatistics courses at the graduatelevel. It also serves as a valuable reference for clinicians andresearchers working in the fields of medicine, epidemiology, andbiostatistics.

Medicine deals with treatments that work often but not always, so treatment success must be based on probability. Statistical methods lift medical research from the anecdotal to measured levels of probability. This book presents the common statistical methods used in 90% of medical research, along with the underlying basics, in two parts: a textbook section for use by students in health care training programs, e.g., medical schools or residency training, and a reference section for use by practicing clinicians in reading medical literature and performing their own research. The book does not require a significant level of mathematical knowledge and couches the methods in multiple examples drawn from clinical medicine, giving it applicable context. Easy-to-follow format incorporates medical examples, step-by-step methods, and check yourself exercises Two-part design features course material and a professional reference section Chapter summaries provide a review of formulas, method algorithms, and check lists Companion site links to statistical databases that can be downloaded and used to perform the exercises from the book and practice statistical methods New in this Edition: New chapters on: multifactor tests on means of continuous data, equivalence testing, and advanced methods New topics include: trial randomization, treatment ethics in medical research, imputation of missing data, and making evidence-based medical decisions Updated database coverage and additional exercises Expanded coverage of numbers needed to treat and to benefit, and regression analysis including stepwise regression and Cox regression Thorough discussion on required sample size