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| clinical research data management training: A Guide to GCP for Clinical Data Management MARK. ELSLEY, 2017 |
| clinical research data management training: Clinical Data Management Richard K. Rondel, Sheila A. Varley, Colin F. Webb, 2000-02-03 Extensively revised and updated, with the addition of new chapters and authors, this long-awaited second edition covers all aspects of clinical data management. Giving details of the efficient clinical data management procedures required to satisfy both corporate objectives and quality audits by regulatory authorities, this text is timely and an important contribution to the literature. The volume: * is written by well-known and experienced authors in this area * provides new approaches to major topics in clinical data management * contains new chapters on systems software validation, database design and performance measures. It will be invaluable to anyone in the field within the pharmaceutical industry, and to all biomedical professionals working in clinical research. |
| clinical research data management training: Fundamentals of Clinical Data Science Pieter Kubben, Michel Dumontier, Andre Dekker, 2018-12-21 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. |
| clinical research data management training: Principles and Practice of Clinical Research John I. Gallin, Frederick P Ognibene, 2011-04-28 The second edition of this innovative work again provides a unique perspective on the clinical discovery process by providing input from experts within the NIH on the principles and practice of clinical research. Molecular medicine, genomics, and proteomics have opened vast opportunities for translation of basic science observations to the bedside through clinical research. As an introductory reference it gives clinical investigators in all fields an awareness of the tools required to ensure research protocols are well designed and comply with the rigorous regulatory requirements necessary to maximize the safety of research subjects. Complete with sections on the history of clinical research and ethics, copious figures and charts, and sample documents it serves as an excellent companion text for any course on clinical research and as a must-have reference for seasoned researchers.*Incorporates new chapters on Managing Conflicts of Interest in Human Subjects Research, Clinical Research from the Patient's Perspective, The Clinical Researcher and the Media, Data Management in Clinical Research, Evaluation of a Protocol Budget, Clinical Research from the Industry Perspective, and Genetics in Clinical Research *Addresses the vast opportunities for translation of basic science observations to the bedside through clinical research*Delves into data management and addresses how to collect data and use it for discovery*Contains valuable, up-to-date information on how to obtain funding from the federal government |
| clinical research data management training: A Practical Guide to Managing Clinical Trials JoAnn Pfeiffer, Cris Wells, 2017-05-18 A Practical Guide to Managing Clinical Trials is a basic, comprehensive guide to conducting clinical trials. Designed for individuals working in research site operations, this user-friendly reference guides the reader through each step of the clinical trial process from site selection, to site set-up, subject recruitment, study visits, and to study close-out. Topics include staff roles/responsibilities/training, budget and contract review and management, subject study visits, data and document management, event reporting, research ethics, audits and inspections, consent processes, IRB, FDA regulations, and good clinical practices. Each chapter concludes with a review of key points and knowledge application. Unique to this book is A View from India, a chapter-by-chapter comparison of clinical trial practices in India versus the U.S. Throughout the book and in Chapter 10, readers will glimpse some of the challenges and opportunities in the emerging and growing market of Indian clinical trials. |
| clinical research data management training: Managing and Sharing Research Data Louise Corti, Veerle Van den Eynden, Libby Bishop, Matthew Woollard, 2014-02-04 Research funders in the UK, USA and across Europe are implementing data management and sharing policies to maximize openness of data, transparency and accountability of the research they support. Written by experts from the UK Data Archive with over 20 years experience, this book gives post-graduate students, researchers and research support staff the data management skills required in today’s changing research environment. The book features guidance on: how to plan your research using a data management checklist how to format and organize data how to store and transfer data research ethics and privacy in data sharing and intellectual property rights data strategies for collaborative research how to publish and cite data how to make use of other people’s research data, illustrated with six real-life case studies of data use. |
| clinical research data management training: Sharing Clinical Trial Data Institute of Medicine, Board on Health Sciences Policy, Committee on Strategies for Responsible Sharing of Clinical Trial Data, 2015-04-20 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. |
| clinical research data management training: Practical Guide to Clinical Data Management Susanne Prokscha, 2011-10-26 The management of clinical data, from its collection during a trial to its extraction for analysis, has become a critical element in the steps to prepare a regulatory submission and to obtain approval to market a treatment. Groundbreaking on its initial publication nearly fourteen years ago, and evolving with the field in each iteration since then, |
| clinical research data management training: Practical Guide to Clinical Data Management, Third Edition Susanne Prokscha, 2011-10-26 The management of clinical data, from its collection during a trial to its extraction for analysis, has become a critical element in the steps to prepare a regulatory submission and to obtain approval to market a treatment. Groundbreaking on its initial publication nearly fourteen years ago, and evolving with the field in each iteration since then, the third edition of Practical Guide to Clinical Data Management includes important updates to all chapters to reflect the current industry approach to using electronic data capture (EDC) for most studies. See what’s new in the Third Edition: A chapter on the clinical trial process that explains the high level flow of a clinical trial from creation of the protocol through the study lock and provides the context for the clinical data management activities that follow Reorganized content reflects an industry trend that divides training and standard operating procedures for clinical data management into the categories of study startup, study conduct, and study closeout Coverage of current industry and Food and Drug Administration (FDA) approaches and concerns The book provides a comprehensive overview of the tasks involved in clinical data management and the computer systems used to perform those tasks. It also details the context of regulations that guide how those systems are used and how those regulations are applied to their installation and maintenance. Keeping the coverage practical rather than academic, the author hones in on the most critical information that impacts clinical trial conduct, providing a full end-to-end overview or introduction for clinical data managers. |
| clinical research data management training: Understanding Clinical Research Renato D. Lopes, Robert A. Harrington, 2013-05-22 A complete guide to understanding and applying clinical research results Ideal for both researchers and healthcare providers Understanding Clinical Research addresses both the operational challenges of clinical trials and the needs of clinicians to comprehend the nuances of research methods to accurately analyze study results. This timely resource covers all aspects of clinical trials--from study design and statistics to regulatory oversight--and it delivers a detailed yet streamlined overview of must-know research topics. The text features an accessible three-part organization that traces the evolution of clinical research and explains the bedrock principles and unique challenges of clinical experimentation and observational research. Reinforcing this content are real-life case examples--drawn from the authors' broad experience--that put chapter concepts into action and contribute to a working knowledge of integral research techniques. FEATURES: The most definitive guide to promoting excellence in clinical research, designed to empower healthcare providers to assess a study's strengths and weaknesses with confidence and apply this knowledge to optimize patient outcomes In-depth coverage of fundamental research methods and protocols from preeminent authorities provides readers with an instructive primer and a springboard for ongoing clinical research education Clear, comprehensive three-part organization: Section One: Evolution of Clinical Research offers a succinct history of clinical trials, drug regulations, and the role of the FDA while covering the impact of information technology and academic research organizations Section Two: Principles of Clinical Experimentation takes you through the typical phases of clinical trials in the development of medical products, from initial human subject research to postapproval surveillance studies Section Three: Observational Research highlights the underlying principles, pitfalls, and methods for case-control studies, cohort studies, registries, and subgroup analyses within randomized trials |
| clinical research data management training: Principles of Good Clinical Practice Michael J. McGraw, 2010 Part of RPS Pharmacy Business Administration Series, this book offers good clinical practice guidelines. It includes standards on how clinical trials should be conducted, provide assurance of safety and efficacy of various drugs and protect human rights. |
| clinical research data management training: Clinical Research Informatics Rachel L. Richesson, James E. Andrews, Kate Fultz Hollis, 2023-06-14 This extensively revised new edition comprehensively reviews the rise of clinical research informatics (CRI). It enables the reader to develop a thorough understanding of how CRI has developed and the evolving challenges facing the biomedical informatics professional in the modern clinical research environment. Emphasis is placed on the changing role of the consumer and the need to merge clinical care delivery and research as part of a changing paradigm in global healthcare delivery. Clinical Research Informatics presents a detailed review of using informatics in the continually evolving clinical research environment. It represents a valuable textbook reference for all students and practising healthcare informatics professional looking to learn and expand their understanding of this fast-moving and increasingly important discipline. |
| clinical research data management training: Designing Clinical Research Stephen B. Hulley, Steven R. Cummings, Warren S. Browner, Deborah G. Grady, Thomas B. Newman, 2011-11-30 Designing Clinical Research sets the standard for providing a practical guide to planning, tabulating, formulating, and implementing clinical research, with an easy-to-read, uncomplicated presentation. This edition incorporates current research methodology—including molecular and genetic clinical research—and offers an updated syllabus for conducting a clinical research workshop. Emphasis is on common sense as the main ingredient of good science. The book explains how to choose well-focused research questions and details the steps through all the elements of study design, data collection, quality assurance, and basic grant-writing. All chapters have been thoroughly revised, updated, and made more user-friendly. |
| clinical research data management training: Assuring Data Quality and Validity in Clinical Trials for Regulatory Decision Making Institute of Medicine, Roundtable on Research and Development of Drugs, Biologics, and Medical Devices, 1999-07-27 In an effort to increase knowledge and understanding of the process of assuring data quality and validity in clinical trials, the IOM hosted a workshop to open a dialogue on the process to identify and discuss issues of mutual concern among industry, regulators, payers, and consumers. The presenters and panelists together developed strategies that could be used to address the issues that were identified. This IOM report of the workshop summarizes the present status and highlights possible strategies for making improvements to the education of interested and affected parties as well as facilitating future planning. |
| clinical research data management training: Practical Guide to Clinical Data Management Susanne Prokscha, 2024 A Practical Guide to Clinical Data Management, Fourth Edition provides a comprehensive overview of the tasks involved in clinical data management and the computer systems used to perform those tasks. |
| clinical research data management training: A Clinical Trials Manual From The Duke Clinical Research Institute Margaret Liu, Kate Davis, 2011-08-24 The publication of the second edition of this manual comes at an important juncture in the history of clinical research. As advances in information technology make it possible to link individuals and groups in diverse locations in jointly seeking the answers to pressing global health problems, it is critically important to remain vigilant about moral and ethical safeguards for every patient enrolled in a trial. Those who study this manual will be well aware of how to ensure patient safety along with fiscal responsibility, trial efficiency, and research integrity. —Robert Harrington, Professor of Medicine, Director, Duke Clinical Research Institute, Durham, North Carolina, USA The Duke Clinical Research Institute (DCRI) is one of the world's leading academic clinical research organizations; its mission is to develop and share knowledge that improves the care of patients around the world through innovative clinical research. This concise handbook provides a practical nuts and bolts approach to the process of conducting clinical trials, identifying methods and techniques that can be replicated at other institutions and medical practices. Designed for investigators, research coordinators, CRO personnel, students, and others who have a desire to learn about clinical trials, this manual begins with an overview of the historical framework of clinical research, and leads the reader through a discussion of safety concerns and resulting regulations. Topics include Good Clinical Practice, informed consent, management of subject safety and data, as well as monitoring and reporting adverse events. Updated to reflect recent regulatory and clinical developments, the manual reviews the conduct of clinical trials research in an increasingly global context. This new edition has been further expanded to include: In-depth information on conducting clinical trials of medical devices and biologics The role and responsibilities of Institutional Review Boards, and Recent developments regarding subject privacy concerns and regulations. Ethical documents such as the Belmont Report and the Declaration of Helsinki are reviewed in relation to all aspects of clinical research, with a discussion of how researchers should apply the principles outlined in these important documents. This graphically appealing and eminently readable manual also provides sample forms and worksheets to facilitate data management and regulatory record retention; these can be modified and adapted for use at investigative sites. |
| clinical research data management training: Validating Clinical Trial Data Reporting with SAS Carol I. Matthews, Brian C. Shilling, 2008 This indispensable guide focuses on validating programs written to support the clinical trial process from after the data collection stage to generating reports and submitting data and output to the Food and Drug Administration. |
| clinical research data management training: Clinical Trials Handbook Shayne Cox Gad, 2009-06-17 Best practices for conducting effective and safe clinical trials Clinical trials are arguably the most important steps in proving drug effectiveness and safety for public use. They require intensive planning and organization and involve a wide range of disciplines: data management, biostatistics, pharmacology, toxicology, modeling and simulation, regulatory monitoring, ethics, and particular issues for given disease areas. Clinical Trials Handbook provides a comprehensive and thorough reference on the basics and practices of clinical trials. With contributions from a range of international authors, the book takes the reader through each trial phase, technique, and issue. Chapters cover every key aspect of preparing and conducting clinical trials, including: Interdisciplinary topics that have to be coordinated for a successful clinical trialData management (and adverse event reporting systems) Biostatistics, pharmacology, and toxicology Modeling and simulation Regulatory monitoring and ethics Particular issues for given disease areas-cardiology, oncology, cognitive, dementia, dermatology, neuroscience, and more With unique information on such current issues as adverse event reporting (AER) systems, adaptive trial designs, and crossover trial designs, Clinical Trials Handbook will be a ready reference for pharmaceutical scientists, statisticians, researchers, and the many other professionals involved in drug development. |
| clinical research data management training: Cochrane Handbook for Systematic Reviews of Interventions Julian P. T. Higgins, Sally Green, 2008-11-24 Healthcare providers, consumers, researchers and policy makers are inundated with unmanageable amounts of information, including evidence from healthcare research. It has become impossible for all to have the time and resources to find, appraise and interpret this evidence and incorporate it into healthcare decisions. Cochrane Reviews respond to this challenge by identifying, appraising and synthesizing research-based evidence and presenting it in a standardized format, published in The Cochrane Library (www.thecochranelibrary.com). The Cochrane Handbook for Systematic Reviews of Interventions contains methodological guidance for the preparation and maintenance of Cochrane intervention reviews. Written in a clear and accessible format, it is the essential manual for all those preparing, maintaining and reading Cochrane reviews. Many of the principles and methods described here are appropriate for systematic reviews applied to other types of research and to systematic reviews of interventions undertaken by others. It is hoped therefore that this book will be invaluable to all those who want to understand the role of systematic reviews, critically appraise published reviews or perform reviews themselves. |
| clinical research data management training: The Design and Management of Medical Device Clinical Trials Salah M. Abdel-aleem, 2011-09-09 Clinical trials tasks and activities are widely diverse and require certain skill sets to both plan and execute. This book provides professionals in the field of clinical research with valuable information on the challenging issues of the design, execution, and management of clinical trials, and how to resolve these issues effectively. It discusses key obstacles such as challenges to patient recruitment, investigator and study site selection, and dealing with compliance issues. Through practical examples, professionals working with medical device clinical trials will discover the appropriate steps to take. |
| clinical research data management training: Fundamentals of Clinical Trials Lawrence M. Friedman, Curt Furberg, David L. DeMets, 1998 This classic reference, now updated with the newest applications and results, addresses the fundamentals of such trials based on sound scientific methodology, statistical principles, and years of accumulated experience by the three authors. |
| clinical research data management training: The Prevention and Treatment of Missing Data in Clinical Trials National Research Council, Division of Behavioral and Social Sciences and Education, Committee on National Statistics, Panel on Handling Missing Data in Clinical Trials, 2010-12-21 Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data. |
| clinical research data management training: Statistical Thinking for Non-Statisticians in Drug Regulation Richard Kay, 2013-05-20 Written by a well-known lecturer and consultant to the pharmaceutical industry, this book focuses on the pharmaceutical non-statistician working within a very strict regulatory environment. Statistical Thinking for Clinical Trials in Drug Regulation presents the concepts and statistical thinking behind medical studies with a direct connection to the regulatory environment so that readers can be clear where the statistical methodology fits in with industry requirements. Pharmaceutical-related examples are used throughout to set the information in context. As a result, this book provides a detailed overview of the statistical aspects of the design, conduct, analysis and presentation of data from clinical trials within drug regulation. Statistical Thinking for Clinical Trials in Drug Regulation: Assists pharmaceutical personnel in communicating effectively with statisticians using statistical language Improves the ability to read and understand statistical methodology in papers and reports and to critically appraise that methodology Helps to understand the statistical aspects of the regulatory framework better quoting extensively from regulatory guidelines issued by the EMEA (European Medicines Evaluation Agency), ICH (International Committee on Harmonization and the FDA (Food and Drug Administration) |
| clinical research data management training: Management of Data in Clinical Trials Eleanor McFadden, 1997-11-07 Timely, authoritative, complete-a comprehensive guide to managing data in clinical trials At some point during their training, virtually all health professionals are exposed to the theory of clinical trials, but few are taught about the practical details of organizing and conducting a clinical trial. This book fills that gap in training. Management of Data in Clinical Trials is a valuable working resource for anyone involved in any type of clinical trial-from large multicenter trials to small single-investigator studies. The information is relevant to trials in all disease areas, done in any clinical setting, and is general enough to be applicable both within and outside the United States. This authoritative handbook offers in-depth coverage of accrual and follow-up phases of a clinical trial and provides valuable expert advice and step-by-step guidance on: * Trial planning and resource assessment * Developing a trial protocol and case report forms * Selection and use of computers and software for clinical trials * Eligibility checking and patient registration * Data collection and data entry * Quality control systems at the local and central levels * Training and education of data management staff * The role of data management in implementing good clinical practice (GCP) * Development of software tools for trial management |
| clinical research data management training: Global Clinical Trials Playbook Menghis Bairu, Richard Chin, 2012-04-20 Pharmaceuticals companies, biotech companies, and CROs, regardless of size, all face the same challenge of managing costs and operational execution associated with bringing a valuable drugs and devices to market. Because of timeline pressures and cost as well as the growing interest in neglected diseases and diseases affecting the emerging nations, clinical trials are increasingly conducted in emerging markets and developing countries where infrastructure, leadership, skilled personnel and a governance are at a premium. Working with academics, regulatory professionals, safety officers, experts from the pharma industry and CROs, the editors have put together this up-to-date, step-by-step guide book to building and enhancing global clinical trial capacity in emerging markets and developing countries. This book covers the design, conduct, and tools to build and/or enhance human capacity to execute such trials, appealing to individuals in health ministries, pharmaceutical companies, world health organizations, academia, industry, and non-governmental organizations (NGOs) who are managing global clinical trials. Gives medical professionals the business tools needed to effectively execute clinical trials throughout the world Provides real world international examples which illustrate the practical translation of principles Includes forms, templates, and additional references for standardization in a number of global scenarios |
| clinical research data management training: Pharmaceutical Medicine Adrian Kilcoyne, 2013-05-23 Pharmaceutical Medicine provides an accessible, user-friendly and up-to-date guide for those involved in clinical trials or marketing of new medicines in the pharmaceutical industry. |
| clinical research data management training: Thesis Writing for Master's and Ph.D. Program Subhash Chandra Parija, Vikram Kate, 2018-11-03 This book on Thesis Writing for Master’s and Ph.D. program focuses on the difficulties students encounter with regard to choosing a guide; selecting an appropriate research title considering the available resources; conducting research; and ways to overcome the hardships they face while researching, writing and preparing their dissertation for submission. Thesis writing is an essential skill that medical and other postgraduates are expected to learn during their academic career as a mandatory partial requirement in order to receive the Master’s degree. However, at the majority of medical schools, writing a thesis is largely based on self-learning, which adds to the burden on students due to the tremendous amount of time spent learning the writing skills in addition to their exhausting clinical and academic work. Due to the difficulties faced during the early grooming years and lack of adequate guidance, acquiring writing skills continues to be a daunting task for most students. This book addresses these difficulties and deficiencies and provides comprehensive guidance, from selecting the research title to publishing in a scientific journal. |
| clinical research data management training: Clinical Trials Stuart J. Pocock, 2013-07-17 This comprehensive, unified text on the principles and practice of clinical trials presents a detailed account of how to conduct the trials. It describes the design, analysis, and interpretation of clinical trials in a non-technical manner and provides a general perspective on their historical development, current status, and future strategy. Features examples derived from the author's personal experience. |
| clinical research data management training: Responsible Conduct of Research Adil E. Shamoo, David B. Resnik, 2009-02-12 Recent scandals and controversies, such as data fabrication in federally funded science, data manipulation and distortion in private industry, and human embryonic stem cell research, illustrate the importance of ethics in science. Responsible Conduct of Research, now in a completely updated second edition, provides an introduction to the social, ethical, and legal issues facing scientists today. |
| clinical research data management training: Registries for Evaluating Patient Outcomes Agency for Healthcare Research and Quality/AHRQ, 2014-04-01 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. |
| clinical research data management training: Beyond the HIPAA Privacy Rule Institute of Medicine, Board on Health Care Services, Board on Health Sciences Policy, Committee on Health Research and the Privacy of Health Information: The HIPAA Privacy Rule, 2009-03-24 In the realm of health care, privacy protections are needed to preserve patients' dignity and prevent possible harms. Ten years ago, to address these concerns as well as set guidelines for ethical health research, Congress called for a set of federal standards now known as the HIPAA Privacy Rule. In its 2009 report, Beyond the HIPAA Privacy Rule: Enhancing Privacy, Improving Health Through Research, the Institute of Medicine's Committee on Health Research and the Privacy of Health Information concludes that the HIPAA Privacy Rule does not protect privacy as well as it should, and that it impedes important health research. |
| clinical research data management training: Career Opportunities in Clinical Drug Research Rebecca Jane Anderson, 2010 It is simply amazing to me that so many of my industry coworkers stumbled upon their careers in clinical research, like I did, merely by chance. In most cases, once those opportunities were presented to us, we found fulfilling and successful careers. Undoubtedly, other eager job seekers would also find this career path attractive. If only someone would tell them about it. |
| clinical research data management training: Sharing and reuse of health-related data for research purposes World Health Organization, 2022-04-06 This document sets out WHO policy on the sharing and reuse of health-related data for research purposes, and guidance on how to implement the policy. It clarifies for WHO staff the policy and practice on the reuse and onward sharing of health data collected under the auspices of WHO technical programmes for research purposes. Its scope includes research data generated by research undertaken directly by WHO, or funded by WHO, as well as the use of other health data for research purposes. This document also provides further references and resources to assist in the development of a data management and sharing plan that is in alignment with the vision of this policy. This covers both emergency and non-emergency situations and complements the following from the reuse perspective: Policy on use and sharing of data collected in Member States by the World Health Organization (WHO) outside the context of public health emergencies; the Policy Statement on Data Sharing by the World Health Organization in the Context of Public Health Emergencies and; the Joint statement on public disclosure of results from clinical trials. |
| clinical research data management training: Transforming Clinical Research in the United States Institute of Medicine, Board on Health Sciences Policy, Forum on Drug Discovery, Development, and Translation, 2010-10-22 An ideal health care system relies on efficiently generating timely, accurate evidence to deliver on its promise of diminishing the divide between clinical practice and research. There are growing indications, however, that the current health care system and the clinical research that guides medical decisions in the United States falls far short of this vision. The process of generating medical evidence through clinical trials in the United States is expensive and lengthy, includes a number of regulatory hurdles, and is based on a limited infrastructure. The link between clinical research and medical progress is also frequently misunderstood or unsupported by both patients and providers. The focus of clinical research changes as diseases emerge and new treatments create cures for old conditions. As diseases evolve, the ultimate goal remains to speed new and improved medical treatments to patients throughout the world. To keep pace with rapidly changing health care demands, clinical research resources need to be organized and on hand to address the numerous health care questions that continually emerge. Improving the overall capacity of the clinical research enterprise will depend on ensuring that there is an adequate infrastructure in place to support the investigators who conduct research, the patients with real diseases who volunteer to participate in experimental research, and the institutions that organize and carry out the trials. To address these issues and better understand the current state of clinical research in the United States, the Institute of Medicine's (IOM) Forum on Drug Discovery, Development, and Translation held a 2-day workshop entitled Transforming Clinical Research in the United States. The workshop, summarized in this volume, laid the foundation for a broader initiative of the Forum addressing different aspects of clinical research. Future Forum plans include further examining regulatory, administrative, and structural barriers to the effective conduct of clinical research; developing a vision for a stable, continuously funded clinical research infrastructure in the United States; and considering strategies and collaborative activities to facilitate more robust public engagement in the clinical research enterprise. |
| clinical research data management training: Individual Participant Data Meta-Analysis Richard D. Riley, Jayne F. Tierney, Lesley A. Stewart, 2021-06-08 Individual Participant Data Meta-Analysis: A Handbook for Healthcare Research provides a comprehensive introduction to the fundamental principles and methods that healthcare researchers need when considering, conducting or using individual participant data (IPD) meta-analysis projects. Written and edited by researchers with substantial experience in the field, the book details key concepts and practical guidance for each stage of an IPD meta-analysis project, alongside illustrated examples and summary learning points. Split into five parts, the book chapters take the reader through the journey from initiating and planning IPD projects to obtaining, checking, and meta-analysing IPD, and appraising and reporting findings. The book initially focuses on the synthesis of IPD from randomised trials to evaluate treatment effects, including the evaluation of participant-level effect modifiers (treatment-covariate interactions). Detailed extension is then made to specialist topics such as diagnostic test accuracy, prognostic factors, risk prediction models, and advanced statistical topics such as multivariate and network meta-analysis, power calculations, and missing data. Intended for a broad audience, the book will enable the reader to: Understand the advantages of the IPD approach and decide when it is needed over a conventional systematic review Recognise the scope, resources and challenges of IPD meta-analysis projects Appreciate the importance of a multi-disciplinary project team and close collaboration with the original study investigators Understand how to obtain, check, manage and harmonise IPD from multiple studies Examine risk of bias (quality) of IPD and minimise potential biases throughout the project Understand fundamental statistical methods for IPD meta-analysis, including two-stage and one-stage approaches (and their differences), and statistical software to implement them Clearly report and disseminate IPD meta-analyses to inform policy, practice and future research Critically appraise existing IPD meta-analysis projects Address specialist topics such as effect modification, multiple correlated outcomes, multiple treatment comparisons, non-linear relationships, test accuracy at multiple thresholds, multiple imputation, and developing and validating clinical prediction models Detailed examples and case studies are provided throughout. |
| clinical research data management training: Field Trials of Health Interventions Peter G. Smith, Richard H. Morrow, David A. Ross, 2015 This is an open access title available under the terms of a CC BY-NC 4.0 International licence. It is free to read at Oxford Scholarship Online and offered as a free PDF download from OUP and selected open access locations. Before new interventions are released into disease control programmes, it is essential that they are carefully evaluated in field trials'. These may be complex and expensive undertakings, requiring the follow-up of hundreds, or thousands, of individuals, often for long periods. Descriptions of the detailed procedures and methods used in the trials that have been conducted have rarely been published. A consequence of this, individuals planning such trials have few guidelines available and little access to knowledge accumulated previously, other than their own. In this manual, practical issues in trial design and conduct are discussed fully and in sufficient detail, that Field Trials of Health Interventions may be used as a toolbox' by field investigators. It has been compiled by an international group of over 30 authors with direct experience in the design, conduct, and analysis of field trials in low and middle income countries and is based on their accumulated knowledge and experience. Available as an open access book via Oxford Medicine Online, this new edition is a comprehensive revision, incorporating the new developments that have taken place in recent years with respect to trials, including seven new chapters on subjects ranging from trial governance, and preliminary studies to pilot testing. |
| clinical research data management training: Biomedical Index to PHS-supported Research: pt. A. Subject access A-H , 1992 |
| clinical research data management training: NIH Guide for Grants and Contracts , 1993 |
| clinical research data management training: Research Awards Index , 1989 |
| clinical research data management training: Research Grants Index National Institutes of Health (U.S.). Division of Research Grants, 1975 |
ClinicalTrials.gov
Study record managers: refer to the Data Element Definitions if submitting registration or results information.
CLINICAL Definition & Meaning - Merriam-Webster
The meaning of CLINICAL is of, relating to, or conducted in or as if in a clinic. How to use clinical in a sentence.
CLINICAL | English meaning - Cambridge Dictionary
CLINICAL definition: 1. used to refer to medical work or teaching that relates to the examination and treatment of ill…. Learn more.
CLINICAL definition and meaning | Collins English Dictionary
Clinical means involving or relating to the direct medical treatment or testing of patients.
Clinical Definition & Meaning | Britannica Dictionary
CLINICAL meaning: 1 : relating to or based on work done with real patients of or relating to the medical treatment that is given to patients in hospitals, clinics, etc.; 2 : requiring treatment as a …
CLINICAL | meaning - Cambridge Learner's Dictionary
CLINICAL definition: 1. relating to medical treatment and tests: 2. only considering facts and not influenced by…. Learn more.
Clinical - definition of clinical by The Free Dictionary
1. pertaining to a clinic. 2. concerned with or based on actual observation and treatment of disease in patients rather than experimentation or theory. 3. dispassionately analytic; unemotionally …
Clinical - Definition, Meaning & Synonyms | Vocabulary.com
Something that's clinical is based on or connected to the study of patients. Clinical medications have actually been used by real people, not just studied theoretically.
Clinical Definition & Meaning - YourDictionary
Clinical definition: Of, relating to, or connected with a clinic.
Equity Medical | Clinical Research In New York And Kentucky
We pioneer dermatological advancements, collaborating on innovative treatments through research and clinical trials in urban New York City and rural Southern Kentucky.
ClinicalTrials.gov
Study record managers: refer to the Data Element Definitions if submitting registration or results information.
CLINICAL Definition & Meaning - Merriam-Webster
The meaning of CLINICAL is of, relating to, or conducted in or as if in a clinic. How to use clinical in a sentence.
CLINICAL | English meaning - Cambridge Dictionary
CLINICAL definition: 1. used to refer to medical work or teaching that relates to the examination and treatment of ill…. Learn more.
CLINICAL definition and meaning | Collins English Dictionary
Clinical means involving or relating to the direct medical treatment or testing of patients.
Clinical Definition & Meaning | Britannica Dictionary
CLINICAL meaning: 1 : relating to or based on work done with real patients of or relating to the medical treatment that is given to patients in hospitals, clinics, etc.; 2 : requiring treatment as a …
CLINICAL | meaning - Cambridge Learner's Dictionary
CLINICAL definition: 1. relating to medical treatment and tests: 2. only considering facts and not influenced by…. Learn more.
Clinical - definition of clinical by The Free Dictionary
1. pertaining to a clinic. 2. concerned with or based on actual observation and treatment of disease in patients rather than experimentation or theory. 3. dispassionately analytic; …
Clinical - Definition, Meaning & Synonyms | Vocabulary.com
Something that's clinical is based on or connected to the study of patients. Clinical medications have actually been used by real people, not just studied theoretically.
Clinical Definition & Meaning - YourDictionary
Clinical definition: Of, relating to, or connected with a clinic.
Equity Medical | Clinical Research In New York And Kentucky
We pioneer dermatological advancements, collaborating on innovative treatments through research and clinical trials in urban New York City and rural Southern Kentucky.
