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| clinical data management metrics: 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 data management metrics: Practical Guide to Clinical Data Management Susanne Prokscha, 1999-01-31 Clinical data management (CDM) has changed from being an essentially clerical task in the late 1970s and early 1980s to a highly computerized, highly specialized field today. And clinical data manages have had to adapt their data management systems and processes accordingly. Practical Guide to Clinical Data Management steers you through a basic understanding of the role of data management in clinical trials and includes more advanced topics such as CDM systems, SOPs, and quality assurance. This book helps you ensure GCP, manage laboratory data, and deal with the kinds of clinical data that can cause difficulties in database applications. With the tools this book provides, you'll learn how to: Ensure that your DMB system is in compliance with federal regulations Build a strategic data management and databsing plan Track and record CRFs Deal with problem data, adverse event data, and legacy data Manage and store lab data Identify and manage discrepancies Ensure quality control over reports Choose a CDM system that is right for your company Create and implement a system validation plan and process Set up and enforce data collection standards Develop test plans and change control systems This book is your guide to finding the most successful and practical options for effective clinical data management. |
| clinical data management metrics: 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 data management metrics: 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 data management metrics: 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 data management metrics: 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 data management metrics: Advance Concepts of Clinical Research Guidance for Industry Dr. Gayatri Ganu, Book is useful for the industrial experts who engage in clinical trials, also for students and research scholar who come in contact with clinical terms. |
| clinical data management metrics: The Tyranny of Metrics Jerry Z. Muller, 2019-04-30 How the obsession with quantifying human performance threatens business, medicine, education, government—and the quality of our lives Today, organizations of all kinds are ruled by the belief that the path to success is quantifying human performance, publicizing the results, and dividing up the rewards based on the numbers. But in our zeal to instill the evaluation process with scientific rigor, we've gone from measuring performance to fixating on measuring itself—and this tyranny of metrics now threatens the quality of our organizations and lives. In this brief, accessible, and powerful book, Jerry Muller uncovers the damage metrics are causing and shows how we can begin to fix the problem. Filled with examples from business, medicine, education, government, and other fields, the book explains why paying for measured performance doesn't work, why surgical scorecards may increase deaths, and much more. But Muller also shows that, when used as a complement to judgment based on personal experience, metrics can be beneficial, and he includes an invaluable checklist of when and how to use them. The result is an essential corrective to a harmful trend that increasingly affects us all. |
| clinical data management metrics: Clinical Analytics and Data Management for the DNP Martha L. Sylvia, PhD, MBA, RN, Mary F. Terhaar, PhD, RN, ANEF, FAAN, 2023-01-18 Praise for the first edition: DNP students may struggle with data management, since their projects are not research but quality improvement, and this book covers the subject well. I recommend it for DNP students for use during their capstone projects. Score: 98, 5 Stars -- Doody's Medical Reviews This unique text and reference—the only book to address the full spectrum of clinical data management for the DNP student—instills a fundamental understanding of how clinical data is gathered, used, and analyzed, and how to incorporate this data into a quality DNP project. The new third edition is updated to reflect changes in national health policy such as quality measurements, bundled payments for specialty care, and Advances to the Affordable Care Act (ACA) and evolving programs through the Centers for Medicare and Medicaid Services (CMS). The third edition reflects the revision of 2021 AACN Essentials and provides data sets and other examples in Excel and SPSS format, along with several new chapters. This resource takes the DNP student step-by-step through the complete process of data management, from planning through presentation, clinical applications of data management that are discipline-specific, and customization of statistical techniques to address clinical data management goals. Chapters are brimming with descriptions, resources, and exemplars that are helpful to both faculty and students. Topics spotlight requisite competencies for DNP clinicians and leaders such as phases of clinical data management, statistics and analytics, assessment of clinical and economic outcomes, value-based care, quality improvement, benchmarking, and data visualization. A progressive case study highlights multiple techniques and methods throughout the text. New to the Third Edition: New Chapter: Using EMR Data for the DNP Project New chapter solidifies link between EBP and Analytics for the DNP project New chapter highlights use of workflow mapping to transition between current and future state, while simultaneously visualizing process measures needed to ensure success of the DNP project Includes more examples to provide practical application exercises for students Key Features: Disseminates robust strategies for using available data from everyday practice to support trustworthy evaluation of outcomes Uses multiple tools to meet data management objectives [SPSS, Excel®, Tableau] Presents case studies to illustrate multiple techniques and methods throughout chapters Includes specific examples of the application and utility of these techniques using software that is familiar to graduate nursing students Offers real world examples of completed DNP projects Provides Instructor’s Manual, PowerPoint slides, data sets in SPSS and Excel, and forms for completion of data management and evaluation plan |
| clinical data management metrics: Ordinarily Well Peter D. Kramer, 2016-06-07 Do antidepressants work, or are they glorified dummy pills? How can we tell? In Ordinarily Well, the celebrated psychiatrist and author Peter D. Kramer examines the growing controversy about the popular medications. A practicing doctor who trained as a psychotherapist and worked with pioneers in psychopharmacology, Kramer combines moving accounts of his patients’ dilemmas with an eye-opening history of drug research to cast antidepressants in a new light. Kramer homes in on the moment of clinical decision making: Prescribe or not? What evidence should doctors bring to bear? Using the wide range of reference that readers have come to expect in his books, he traces and critiques the growth of skepticism toward antidepressants. He examines industry-sponsored research, highlighting its shortcomings. He unpacks the “inside baseball” of psychiatry—statistics—and shows how findings can be skewed toward desired conclusions. Kramer never loses sight of patients. He writes with empathy about his clinical encounters over decades as he weighed treatments, analyzed trial results, and observed medications’ influence on his patients’ symptoms, behavior, careers, families, and quality of life. He updates his prior writing about the nature of depression as a destructive illness and the effect of antidepressants on traits like low self-worth. Crucially, he shows how antidepressants act in practice: less often as miracle cures than as useful, and welcome, tools for helping troubled people achieve an underrated goal—becoming ordinarily well. |
| clinical data management metrics: Improving Healthcare Quality in Europe Characteristics, Effectiveness and Implementation of Different Strategies OECD, World Health Organization, 2019-10-17 This volume, developed by the Observatory together with OECD, provides an overall conceptual framework for understanding and applying strategies aimed at improving quality of care. Crucially, it summarizes available evidence on different quality strategies and provides recommendations for their implementation. This book is intended to help policy-makers to understand concepts of quality and to support them to evaluate single strategies and combinations of strategies. |
| clinical data management metrics: 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 data management metrics: Virtual Bio-Instrumentation Jon B. Olansen, Eric Rosow, 2001-12-18 This is the eBook version of the print title. The eBook edition does not provide access to the content of the CD ROMs that accompanies the print book. Bringing the power of virtual instrumentation to the biomedical community. Applications across diverse medical specialties Detailed design guides for LabVIEW and BioBench applications Hands-on problem-solving throughout the book Laboratory, clinical, and healthcare applications Numerous VI's with source code, plus several demos, are available on the book's web site Virtual instrumentation allows medical researchers and practitioners to combine the traditional diagnostic tools with advanced technologies such as databases, Active X, and the Internet. In both laboratory and clinical environments, users can interact with a wealth of disparate systems, facilitating better, faster, and more informed decision making. Virtual Bio-Instrumentation: Biomedical, Clinical, and Healthcare Applications in LabVIEW is the first book of its kind to apply VI technology to the biomedical field. Hands-on problems throughout the book demonstrate immediate practical uses Examples cover a variety of medical specialties Detailed design instructions give the inside view of LabVIEW and BioBench applications Both students and practicing professionals will appreciate the practical applications offered for modeling fundamental physiology, advanced systems analysis, medical device development and testing, and even hospital management and clinical engineering scenarios. |
| clinical data management metrics: Re-Engineering Clinical Trials Peter Schueler, Brendan Buckley, 2014-12-16 The pharmaceutical industry is currently operating under a business model that is not sustainable for the future. Given the high costs associated with drug development, there is a vital need to reform this process in order to provide safe and effective drugs while still securing a profit. Re-Engineering Clinical Trials evaluates the trends and challenges associated with the current drug development process and presents solutions that integrate the use of modern communication technologies, innovations and novel enrichment designs. This book focuses on the need to simplify drug development and offers you well-established methodologies and best practices based on real-world experiences from expert authors across industry and academia. Written for all those involved in clinical research, development and clinical trial design, this book provides a unique and valuable resource for streamlining the process, containing costs and increasing drug safety and effectiveness. - Highlights the latest paradigm-shifts and innovation advances in clinical research - Offers easy-to-find best practice sections, lists of current literature and resources for further reading and useful solutions to day-to-day problems in current drug development - Discusses important topics such as safety profiling, data mining, site monitoring, change management, increasing development costs, key performance indicators and much more |
| clinical data management metrics: Healthcare Analytics Ross M. Mullner, Edward M. Rafalski, 2019-08-26 This is a comprehensive, practical guide which looks at the advantages and limitations of new data analysis techniques being introduced across public health and administration services. The Affordable Care Act (ACT) and free market reforms in healthcare are generating a rapid change of pace. The electronification of medical records from paper to digital, which is required to meet the meaningful use standards set forth by the Act, is advancing what and how information can be analyzed. Coupled with the advent of more computing power and big data analytics and techniques, practitioners now more than ever need to stay on top of these trends. This book presents a comprehensive look at healthcare analytics from population data to geospatial analysis using current case studies and data analysis examples in health. This resource will appeal to undergraduate and graduate students in health administration and public health. It will benefit healthcare professionals and administrators in nursing and public health, as well as medical students who are interested in the future of data within healthcare. |
| clinical data management metrics: Advances in Information Technology Research and Application: 2012 Edition , 2012-12-26 Advances in Information Technology Research and Application / 2012 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Information Technology. The editors have built Advances in Information Technology Research and Application / 2012 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Information Technology in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Advances in Information Technology Research and Application / 2012 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/. |
| clinical data management metrics: Henry's Clinical Diagnosis and Management by Laboratory Methods E-Book Richard A. McPherson, Matthew R. Pincus, 2011-09-06 Recognized as the definitive book in laboratory medicine since 1908, Henry’s Clinical Diagnosis and Management by Laboratory Methods, edited by Richard A. McPherson, MD and Matthew R. Pincus, MD, PhD, is a comprehensive, multidisciplinary pathology reference that gives you state-of-the-art guidance on lab test selection and interpretation of results. Revisions throughout keep you current on the latest topics in the field, such as biochemical markers of bone metabolism, clinical enzymology, pharmacogenomics, and more! A user-friendly full-color layout puts all the latest, most essential knowledge at your fingertips. Update your understanding of the scientific foundation and clinical application of today's complete range of laboratory tests. Get optimal test results with guidance on error detection, correction, and prevention as well as cost-effective test selection. Reference the information you need quickly and easily thanks to a full-color layout, many new color illustrations and visual aids, and an organization by organ system. Master all the latest approaches in clinical laboratory medicine with new and updated coverage of: the chemical basis for analyte assays and common interferences; lipids and dyslipoproteinemia; markers in the blood for cardiac injury evaluation and related stroke disorders; coagulation testing for antiplatelet drugs such as aspirin and clopidogrel; biochemical markers of bone metabolism; clinical enzymology; hematology and transfusion medicine; medical microbiology; body fluid analysis; and many other rapidly evolving frontiers in the field. Effectively monitor the pace of drug clearing in patients undergoing pharmacogenomic treatments with a new chapter on this groundbreaking new area. Apply the latest best practices in clinical laboratory management with special chapters on organization, work flow, quality control, interpretation of results, informatics, financial management, and establishing a molecular diagnostics laboratory. Confidently prepare for the upcoming recertification exams for clinical pathologists set to begin in 2016. |
| clinical data management metrics: The Data and Analytics Playbook Lowell Fryman, Gregory Lampshire, Dan Meers, 2016-08-12 The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality explores the way in which data continues to dominate budgets, along with the varying efforts made across a variety of business enablement projects, including applications, web and mobile computing, big data analytics, and traditional data integration. The book teaches readers how to use proven methods and accelerators to break through data obstacles to provide faster, higher quality delivery of mission critical programs. Drawing upon years of practical experience, and using numerous examples and an easy to understand playbook, Lowell Fryman, Gregory Lampshire, and Dan Meers discuss a simple, proven approach to the execution of multiple data oriented activities. In addition, they present a clear set of methods to provide reliable governance, controls, risk, and exposure management for enterprise data and the programs that rely upon it. In addition, they discuss a cost-effective approach to providing sustainable governance and quality outcomes that enhance project delivery, while also ensuring ongoing controls. Example activities, templates, outputs, resources, and roles are explored, along with different organizational models in common use today and the ways they can be mapped to leverage playbook data governance throughout the organization. - Provides a mature and proven playbook approach (methodology) to enabling data governance that supports agile implementation - Features specific examples of current industry challenges in enterprise risk management, including anti-money laundering and fraud prevention - Describes business benefit measures and funding approaches using exposure based cost models that augment risk models for cost avoidance analysis and accelerated delivery approaches using data integration sprints for application, integration, and information delivery success |
| clinical data management metrics: Utilization Management in the Clinical Laboratory and Other Ancillary Services Kent Lewandrowski, Patrick M. Sluss, 2016-11-29 This book is the first comprehensive text on utilization management in the clinical laboratory and other ancillary services. It provides a detailed overview on how to establish a successful utilization management program, focusing on such issues as leadership, governance, informatics, and application of utilization management tools. The volume also describes ways to establish utilization management programs for multiple specialties, including anatomic pathology and cytology, hematology, radiology, clinical chemistry, and genetic testing among other specialties. Numerous examples of specific utilization management initiatives are also described that can be imported to other heath care organizations. A chapter on utilization management in Canada is also included. Edited by an established national leader in utilization management, Utilization Management in the Clinical Laboratory and Other Ancillary Services is a valuable resource for physicians, pathologists, laboratory directors, hospital administrators, and medical insurance professionals looking to implement a utilization management program. |
| clinical data management metrics: Introduction to Health Care Quality Yosef D. Dlugacz, 2017-01-04 Introduction to Health Care Quality explores the issues of quality management in today's health care environment, and provides clear guidance on new and perennial challenges in the field. The idea of 'quality' is examined in the context of a variety of health care situations, with practical emphasis on assessment, monitoring, analysis, and improvement. Students will learn how to utilize statistical tools, patient data, and more to understand new models of reimbursement, including pay for performance and value-based purchasing. They will also learn how to learn how to incorporate technology into everyday practice. Each chapter centers on an essential concept, but builds upon previous chapters to reinforce the material and equip students with a deeper understanding of the modern health care industry. Real-world situations are highlighted to show the intersection of theory and application, while cutting-edge methodologies and models prepare students for today's data-driven health care environment. Health care quality is defined and assessed according to setting, with factors such as standards, laws, regulations, accreditation, and consumerism impacting measurement and analysis in tremendous ways. This book provides an overview of this complex field, with insightful discussion and expert practical guidance. Health care today is worlds away from any other point in history. As the field grows ever more complex, quality management becomes increasingly critical for ensuring optimal patient care. Introduction to Health Care Quality helps students and professionals make sense of the issues, and provide top-notch service in today's rapidly changing health care environment. |
| clinical data management metrics: Data Management, Analytics and Innovation Neha Sharma, Amol Goje, Amlan Chakrabarti, Alfred M. Bruckstein, 2023-05-28 This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. The volume is a collection of peer reviewed research papers presented at Seventh International Conference on Data Management, Analytics and Innovation (ICDMAI 2023), held during 20 – 22 January, 2023 in Pune, India. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry. |
| clinical data management metrics: Performance Dashboards Wayne W. Eckerson, 2005-10-27 Tips, techniques, and trends on how to use dashboard technology to optimize business performance Business performance management is a hot new management discipline that delivers tremendous value when supported by information technology. Through case studies and industry research, this book shows how leading companies are using performance dashboards to execute strategy, optimize business processes, and improve performance. Wayne W. Eckerson (Hingham, MA) is the Director of Research for The Data Warehousing Institute (TDWI), the leading association of business intelligence and data warehousing professionals worldwide that provide high-quality, in-depth education, training, and research. He is a columnist for SearchCIO.com, DM Review, Application Development Trends, the Business Intelligence Journal, and TDWI Case Studies & Solution. |
| clinical data management metrics: The Strategic Application of Information Technology in Health Care Organizations John P. Glaser, 2004-03-01 This thoroughly revised and updated second edition of The Strategic Application of Information Technology in Health Care Organizations offers health care executives and managers a balanced analysis of health care information systems. Written by John Glaser-a renowned expert in the field of health care information technology-this important resource shows health care professionals how to use IT to reduce costs, respond to the demands of managed care, develop a continuum of care, and manage and improve the quality of service to patients, payers, and physicians. |
| clinical data management metrics: Clinical Research Informatics Rachel L. Richesson, James E. Andrews, 2019-02-07 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 informatician 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 informaticians looking to learn and expand their understanding of this fast-moving and increasingly important discipline. |
| clinical data management metrics: Encyclopedia of Biopharmaceutical Statistics - Four Volume Set Shein-Chung Chow, 2018-09-03 Since the publication of the first edition in 2000, there has been an explosive growth of literature in biopharmaceutical research and development of new medicines. This encyclopedia (1) provides a comprehensive and unified presentation of designs and analyses used at different stages of the drug development process, (2) gives a well-balanced summary of current regulatory requirements, and (3) describes recently developed statistical methods in the pharmaceutical sciences. Features of the Fourth Edition: 1. 78 new and revised entries have been added for a total of 308 chapters and a fourth volume has been added to encompass the increased number of chapters. 2. Revised and updated entries reflect changes and recent developments in regulatory requirements for the drug review/approval process and statistical designs and methodologies. 3. Additional topics include multiple-stage adaptive trial design in clinical research, translational medicine, design and analysis of biosimilar drug development, big data analytics, and real world evidence for clinical research and development. 4. A table of contents organized by stages of biopharmaceutical development provides easy access to relevant topics. About the Editor: Shein-Chung Chow, Ph.D. is currently an Associate Director, Office of Biostatistics, U.S. Food and Drug Administration (FDA). Dr. Chow is an Adjunct Professor at Duke University School of Medicine, as well as Adjunct Professor at Duke-NUS, Singapore and North Carolina State University. Dr. Chow is the Editor-in-Chief of the Journal of Biopharmaceutical Statistics and the Chapman & Hall/CRC Biostatistics Book Series and the author of 28 books and over 300 methodology papers. He was elected Fellow of the American Statistical Association in 1995. |
| clinical data management metrics: Data Governance Neera Bhansali, 2013-06-17 As organizations deploy business intelligence and analytic systems to harness business value from their data assets, data governance programs are quickly gaining prominence. And, although data management issues have traditionally been addressed by IT departments, organizational issues critical to successful data management require the implementation of enterprise-wide accountabilities and responsibilities. Data Governance: Creating Value from Information Assets examines the processes of using data governance to manage data effectively. Addressing the complete life cycle of effective data governance—from metadata management to privacy and compliance—it provides business managers, IT professionals, and students with an integrated approach to designing, developing, and sustaining an effective data governance strategy. Explains how to align data governance with business goals Describes how to build successful data stewardship with a governance framework Outlines strategies for integrating IT and data governance frameworks Supplies business-driven and technical perspectives on data quality management, metadata management, data access and security, and data lifecycle The book summarizes the experiences of global experts in the field and addresses critical areas of interest to the information systems and management community. Case studies from healthcare and financial sectors, two industries that have successfully leveraged the potential of data-driven strategies, provide further insights into real-time practice. Facilitating a comprehensive understanding of data governance, the book addresses the burning issue of aligning data assets to both IT assets and organizational strategic goals. With a focus on the organizational, operational, and strategic aspects of data governance, the text provides you with the understanding required to leverage, derive, and sustain maximum value from the informational assets housed in your IT infrastructure. |
| clinical data management metrics: Textbook of Organ Transplantation Set Allan D. Kirk, Stuart J. Knechtle, Christian P. Larsen, Joren C. Madsen, Thomas C. Pearson, Steven A. Webber, 2014-07-21 Brought to you by the world’s leading transplant clinicians, Textbook of Organ Transplantation provides a complete and comprehensive overview of modern transplantation in all its complexity, from basic science to gold-standard surgical techniques to post-operative care, and from likely outcomes to considerations for transplant program administration, bioethics and health policy. Beautifully produced in full color throughout, and with over 600 high-quality illustrations, it successfully: Provides a solid overview of what transplant clinicians/surgeons do, and with topics presented in an order that a clinician will encounter them. Presents a holistic look at transplantation, foregrounding the interrelationships between transplant team members and non-surgical clinicians in the subspecialties relevant to pre- and post-operative patient care, such as gastroenterology, nephrology, and cardiology. Offers a focused look at pediatric transplantation, and identifies the ways in which it significantly differs from transplantation in adults. Includes coverage of essential non-clinical topics such as transplant program management and administration; research design and data collection; transplant policy and bioethical issues. Textbook of Organ Transplantation is the market-leading and definitive transplantation reference work, and essential reading for all transplant surgeons, transplant clinicians, program administrators, basic and clinical investigators and any other members of the transplantation team responsible for the clinical management or scientific study of transplant patients. |
| clinical data management metrics: Pharmaceutical Medicine Adrian Kilcoyne, Phil Ambery, Daniel O'Connor, 2013-05-23 The breadth of the pharmaceutical medicine can be daunting, but this book is designed to navigate a path through the speciality. Providing a broad overview of all topics relevant to the discipline of pharmaceutical medicine, it gives you the facts fast, in a user-friendly format, without having to dive through page upon page of dense text. With 136 chapters spread across 8 sections, the text offers a thorough grounding in issues ranging from medicines regulation to clinical trial design and data management. This makes it a useful revision aid for exams as well as giving you a taster of areas of pharmaceutical medicine adjacent to your current role. For healthcare professionals already working in the field, this book offers a guiding hand in difficult situations as well as supplying rapid access to the latest recommendations and guidelines. Written by authors with experience in the industry and drug regulation, this comprehensive and authoritative guide provides a shoulder to lean on throughout your pharmaceutical career. |
| clinical data management metrics: Laboratory Management Information Systems: Current Requirements and Future Perspectives Moumtzoglou, Anastasius, 2014-07-31 Technological advances have revolutionized the way we manage information in our daily workflow. The medical field has especially benefitted from these advancements, improving patient treatment, health data storage, and the management of laboratory samples and results. Laboratory Management Information Systems: Current Requirements and Future Perspectives responds to the issue of administering appropriate regulations in a medical laboratory environment in the era of telemedicine, electronic health records, and other e-health services. Exploring concepts such as the implementation of ISO 15189:2012 policies and the effects of e-health application, this book is an integral reference source for researchers, academicians, students of health care programs, health professionals, and laboratory personnel. |
| clinical data management metrics: Handbook of Research on Information Technology Management and Clinical Data Administration in Healthcare Dwivedi, Ashish N., 2009-05-31 This book presents theoretical and empirical research on the value of information technology in healthcare--Provided by publisher. |
| clinical data management metrics: Heart Teams for Treatment of Cardiovascular Disease Thierry Mesana, 2019-07-11 This book provides a comprehensive framework for developing heart teams to manage a variety of cardiovascular diseases. Management of cardiovascular diseases has changed dramatically in recent years due to developments in evidence-based practices and treatments as well as the introduction of new devices. The sequential method of referring patients from doctor to doctor is becoming an antiquated model. The future of cardiac care lies in developing multidisciplinary Heart Teams to provide patient-focused treatment for complex cardiovascular problems. This volume examines the history and evolution of cardiovascular care and technology and explains why the implementation of heart teams is absolutely necessary to the future of cardiac care. It analyzes the role of heart teams for heart failure, complex coronary revascularization, mitral valve disease, cardiac imaging, aortic valve disease, cardiac arrhythmias, and women's heart health. Finally, the book explores how heart teams work with hospital administration and the broader healthcare industry. Heart Teams for Treatment of Cardiovascular Disease: A Guide for Advancing Patient-Centered Cardiac Care is an essential resource for physicians and related professionals, residents, fellows, and graduate students in cardiology, cardiac surgery, critical care medicine, and radiology. |
| clinical data management metrics: Intelligent Systems and IoT Applications in Clinical Health Joshi, Herat, Kumar Reddy, C. Kishor, Ouaissa, Mariya, Hanafiah, Marlia Mohd, Doss, Srinath, 2024-11-01 Integrating intelligent systems and internet of things (IoT) into clinical health is crucial for enhancing patient care and operational efficiency. These technologies enable real-time data collection and analysis, facilitating personalized treatment plans and improving diagnostic accuracy. Together innovations can streamline workflows, reduce costs, and ultimately lead to better health outcomes for patients. It is essential to explore how these technologies can be implemented into healthcare. Intelligent Systems and IoT Applications in Clinical Health explores and elucidates the integration of AI, IoT, and blockchain technologies in healthcare. It advances current research by providing comprehensive insights into how these technologies can be leveraged to enhance patient care, improve operational efficiency, and ensure data security. Covering topics such as clinical healthcare, digital health experience, and monitoring systems, this book is an excellent resource for researchers, academicians, medical professionals, medical administrators, educators, graduate and postgraduate students, and more. |
| clinical data management metrics: Fourth Congress on Intelligent Systems Sandeep Kumar, |
| clinical data management metrics: Medical Quality Management Angelo P. Giardino, Lee Ann Riesenberg, Prathibha Varkey, 2020-08-31 This comprehensive medical textbook is a compendium of the latest information on healthcare quality. The text provides knowledge about the theory and practical applications for each of the core areas that comprise the field of medical quality management as well as insight and essential briefings on the impact of new healthcare technologies and innovations on medical quality and improvement. The third edition provides significant new content related to medical quality management and quality improvement, a user-friendly format, case studies, and updated learning objectives. This textbook also serves as source material for the American Board of Medical Quality in the development of its core curriculum and certification examinations. Each chapter is designed for a review of the essential background, precepts, and exemplary practices within the topical area: Basics of Quality Improvement Data Analytics for the Improvement of Healthcare Quality Utilization Management, Case Management, and Care Coordination Economics and Finance in Medical Quality Management External Quality Improvement — Accreditation, Certification, and Education The Interface Between Quality Improvement and Law Ethics and Quality Improvement With the new edition of Medical Quality Management: Theory and Practice, the American College of Medical Quality presents the experience and expertise of its contributors to provide the background necessary for healthcare professionals to assume the responsibilities of medical quality management in healthcare institutions, provide physicians in all medical specialties with a core body of knowledge related to medical quality management, and serve as a necessary guide for healthcare administrators and executives, academics, directors, medical and nursing students and residents, and physicians and other health practitioners. |
| clinical data management metrics: Continuing Medical Education Dennis K. Wentz, 2011 The only full-scale history of continuing medical education and its future |
| clinical data management metrics: Patient-Reported Outcomes in Performance Measurement David Cella, Elizabeth A. Hahn, Sally E. Jensen, Zeeshan Butt, Cindy J. Nowinski, Nan Rothrock, Kathleen N. Lohr, 2015-09-17 Patient-reported outcomes (PROs) are measures of how patients feel or what they are able to do in the context of their health status; PROs are reports, usually on questionnaires, about a patient's health conditions, health behaviors, or experiences with health care that individuals report directly, without modification of responses by clinicians or others; thus, they directly reflect the voice of the patient. PROs cover domains such as physical health, mental and emotional health, functioning, symptoms and symptom burden, and health behaviors. They are relevant for many activities: helping patients and their clinicians make informed decisions about health care, monitoring the progress of care, setting policies for coverage and reimbursement of health services, improving the quality of health care services, and tracking or reporting on the performance of health care delivery organizations. We address the major methodological issues related to choosing, administering, and using PROs for these purposes, particularly in clinical practice settings. We include a framework for best practices in selecting PROs, focusing on choosing appropriate methods and modes for administering PRO measures to accommodate patients with diverse linguistic, cultural, educational, and functional skills, understanding measures developed through both classic and modern test theory, and addressing complex issues relating to scoring and analyzing PRO data. |
| clinical data management metrics: The Transformation of Academic Health Centers Steven Wartman, 2015-03-30 The Transformation of Academic Health Centers: The Institutional Challenge to Improve Health and Well-Being in Healthcare's Changing Landscape presents the direct knowledge and vision of accomplished academic leaders whose unique positions as managers of some of the most complex academic and business enterprises make them expert contributors. Users will find invaluable insights and leadership perspectives on healthcare, health professions education, and bio-medical and clinical research that systematically explores the evolving role of global academic health centers with an eye focused on the transformation necessary to be successful in challenging environments. The book is divided into five sections moving from the broad perspective of the role of academic health centers to the role of education, training, and disruptive technologies. It then addresses the discovery processes, improving funding models, and research efficiency. Subsequent sections address the coming changes in healthcare delivery and future perspectives, providing a complete picture of the needs of the growing and influential healthcare sector. - Outlines strategies for academic health centers to successfully adapt to the global changes in healthcare and delivery - Offers forward-thinking and compelling professional and personal assessments of the evolving role of academic health centers by recognized outstanding academic healthcare leaders - Includes case studies and personal reflections, providing lessons learned and new recommendations to challenge leaders - Provides discussions on the discovery process, improving funding models, and research efficiency |
| clinical data management metrics: Clinical Trials Design in Operative and Non Operative Invasive Procedures Kamal M.F. Itani, Domenic J. Reda, 2017-05-16 The aim of this text is to provide the framework for building a clinical trial as it pertains to operative and non operative invasive procedures, how to get it funded and how to conduct such a trial up to publication of results The text provides all details of building a scientifically and ethically valid proposal, including how to build the infrastructure for a clinical trial and how to move it forward through various funding agencies. The text also presents various types of clinical trials, the use of implantable devices and FDA requirements, and adjuncts to clinical trials and interaction with industry Clinical Trials Design in Invasive Operative and Non Operative Procedures will be of interest to all specialists of surgery, anesthesiologists, interventional radiologists, gastroenterologists, cardiologists, and pulmonologists |
| clinical data management metrics: Nursing Informatics for the Advanced Practice Nurse, Second Edition Susan McBride, PhD, RN-BC, CPHIMS, FAAN, Mari Tietze, PhD, RN, FHIMSS, FAAN, 2018-09-28 A “must have” text for all healthcare professionals practicing in the digital age of healthcare. Nursing Informatics for the Advanced Practice Nurse, Second Edition, delivers a practical array of tools and information to show how advanced practice nurses can maximize patient safety, quality of care, and cost savings through the use of technology. Since the first edition of this text, health information technology has only expanded. With increased capability and complexity, the current technology landscape presents new challenges and opportunities for interprofessional teams. Nurses, who are already trained to use the analytic process to assess, analyze, and intervene, are in a unique position to use this same process to lead teams in addressing healthcare delivery challenges with data. The only informatics text written specifically for advanced practice nurses, Nursing Informatics for the Advanced Practice Nurse, Second Edition, takes an expansive, open, and innovative approach to thinking about technology. Every chapter is highly practical, filled with case studies and exercises that demonstrate how the content presented relates to the contemporary healthcare environment. Where applicable, concepts are aligned with the six domains within the Quality and Safety Education in Nursing (QSEN) approach and are tied to national goals and initiatives. Featuring chapters written by physicians, epidemiologists, engineers, dieticians, and health services researchers, the format of this text reflects its core principle that it takes a team to fully realize the benefit of technology for patients and healthcare consumers. What’s New Several chapters present new material to support teams’ optimization of electronic health records Updated national standards and initiatives Increased focus and new information on usability, interoperability and workflow redesign throughout, based on latest evidence Explores challenges and solutions of electronic clinical quality measures (eCQMs), a major initiative in healthcare informatics; Medicare and Medicaid Services use eCQMs to judge quality of care, and how dynamics change rapidly in today’s environment Key Features Presents national standards and healthcare initiatives Provides in-depth case studies for better understanding of informatics in practice Addresses the DNP Essentials, including II: Organization and system leadership for quality improvement and systems thinking, IV: Core Competency for Informatics, and Interprofessional Collaboration for Improving Patient and Population health outcomes Includes end-of-chapter exercises and questions for students Instructor’s Guide and PowerPoint slides for instructors Aligned with QSEN graduate-level competencies |
| clinical data management metrics: A Practical Guide for Informationists Antonio P DeRosa, 2018-02-23 A Practical Guide for Informationists: Supporting Research and Clinical Practice guides new informationists to a successful career, giving them a pathway to this savvier, more technically advanced, domain-focused role in modern day information centers and libraries. The book's broad scope serves as an invaluable toolkit for healthcare professionals, researchers and graduate students in information management, library and information science, data management, informatics, etc. Furthermore, it is also ideal as a textbook for courses in medical reference services/medical informatics in MLIS programs. - Offer examples (e.g. case studies) of ways of delivering information services to end users - Includes recommendations, evidence and worksheets/take-aways/templates to be repurposed and adapted by the reader - Aimed at the broad area of healthcare and research libraries |
Using Study Metrics to Monitor Several Aspects of Clinical …
With this framework in mind, this paper presents and briefly discusses a non-exhaustive list of metrics that can be implemented early on in the study to monitor progress and performance …
METRICS AND BEST PRACTICES IN CLINICAL DATA …
Clinical data management processing metrics have been used to monitor and evaluate clini- cal data management processing of National Institutes of Health- and pharmaceutical in- dustry …
A GUIDE TO CLINICAL DATA MANAGEMENT FOR …
Clinical data managers should have adequate process knowledge in order to maintain the quality standards of the CDM processes. These are the reasons why the CDM team consists of …
Actionable Metrics to Improve Study Efficiency & Collaboration
The term “companion metrics” refers to the concept that many MCC metrics should be examined in combination with other MCC metrics … together they give you a more complete picture of …
Quality by Design Metrics Framework - CTTI
This Quality by Design Metrics Framework was developed by the Clinical Trials Transformation Initiative (CTTI) in collaboration with CluePoints . It may also be feasible to use this tool as a …
Best Practices in Implementing and Utilizing Clinic-Level Metrics
metrics from outcome metrics • Analyze appropriate data sources to track process and outcome metrics • Distinguish between appropriate and inappropriate uses of clinic metrics Summary
Data Quality Management In Clinical Research - National …
Data quality management (DQM) is a formal process for managing the quality, validity and integrity of the research data captured throughout the study from the time it is collected, stored …
How are we doing? The importance metrics and standard …
Assessing how well you are doing on a given process can be described as a 3-step process. First you must determine which attributes of your process are most important. Second you must …
Data Management Considerations for Clinical Trials - UC …
• Data management is easily one of the most overlooked, underappreciated aspects of clinical and translational research
Project Management for the Clinical Data Manager - Society …
Clinical data managers often assume some degree of project management responsibilities. This chapter discusses the discipline of project management and how to efectively apply project …
Clinical trial data management technology Guide - CDISC
specific technical guidance for practical clinical trial data management. In summary, the international community and the developed countries have established a number of clinical …
How to Optimize Clinical Inventory Management with Proven …
This White Paper illustrates how a set of meaningful and actionable metrics, together with effective inventory management solutions and data collection tools, can guide specialty …
A SURVEY OF INDUSTRY BEST PRACTICE METRICS IN …
Fourteen pharmaceutical companies participated in a telephone survey of best prac- tices and metrics in clinical data management and statistics. Eleven companies were global and three …
Flow of Data in Clinical Trials - Chalmers
We describe the flow of clinical trial data throughout its journey from visit/collection to CSR to NDA/BLA, provide useful metrics to show how much time is saved by using data standards …
Finding the Right Balance - Data Management Surveillance …
Based on a Partnership Manual, which describes the interface processes between the Sponsor and the CRO, different tools were developed to continuously check the data of the clinical trial …
Sponsor Oversight of CROs Data Management and
Small biotechnology company sponsors of clinical trials may have none, or just one or two staff members familiar with these rules that serve as a biostatistician and data manager to review …
Metrics for Data Repositories and Knowledgebases: Working …
Metrics provide systematic parameters for evaluating the cost and benefits of a repository to the various repository stakeholders, including research institutions, funding agencies, and the …
INDEPENDENT RESEARCH SITES: THREE KEY …
Many sites don’t know which metrics to track or how to use those metrics to their advantage. In the absence of quality performance data and industry benchmarks, sites often struggle to …
Visualizing clinical operational metrics to enable decision …
There are many ways to track, report, and visualize metrics, ranging from raw percentages to traffic lights. We developed a visualization scheme for fifteen key metrics, some of which are …
Data and Analytics Fast-track your health system …
Clinical decision-making is too often disconnected from financial diagnostics. Thus clinicians sometimes make care decisions without considering the financial impact — for the …
Using Study Metrics to Monitor Several Aspects of Clinical …
With this framework in mind, this paper presents and briefly discusses a non-exhaustive list of metrics that can be implemented early on in the study to monitor progress and performance …
METRICS AND BEST PRACTICES IN CLINICAL DATA …
Clinical data management processing metrics have been used to monitor and evaluate clini- cal data management processing of National Institutes of Health- and pharmaceutical in- dustry …
A GUIDE TO CLINICAL DATA MANAGEMENT FOR BIOTECH …
Clinical data managers should have adequate process knowledge in order to maintain the quality standards of the CDM processes. These are the reasons why the CDM team consists of …
Actionable Metrics to Improve Study Efficiency & …
The term “companion metrics” refers to the concept that many MCC metrics should be examined in combination with other MCC metrics … together they give you a more complete picture of …
Quality by Design Metrics Framework - CTTI
This Quality by Design Metrics Framework was developed by the Clinical Trials Transformation Initiative (CTTI) in collaboration with CluePoints . It may also be feasible to use this tool as a …
Best Practices in Implementing and Utilizing Clinic-Level Metrics
metrics from outcome metrics • Analyze appropriate data sources to track process and outcome metrics • Distinguish between appropriate and inappropriate uses of clinic metrics Summary
Data Quality Management In Clinical Research - National …
Data quality management (DQM) is a formal process for managing the quality, validity and integrity of the research data captured throughout the study from the time it is collected, stored …
How are we doing? The importance metrics and standard …
Assessing how well you are doing on a given process can be described as a 3-step process. First you must determine which attributes of your process are most important. Second you must …
Data Management Considerations for Clinical Trials - UC …
• Data management is easily one of the most overlooked, underappreciated aspects of clinical and translational research
Project Management for the Clinical Data Manager - Society …
Clinical data managers often assume some degree of project management responsibilities. This chapter discusses the discipline of project management and how to efectively apply project …
Clinical trial data management technology Guide - CDISC
specific technical guidance for practical clinical trial data management. In summary, the international community and the developed countries have established a number of clinical …
How to Optimize Clinical Inventory Management with …
This White Paper illustrates how a set of meaningful and actionable metrics, together with effective inventory management solutions and data collection tools, can guide specialty …
A SURVEY OF INDUSTRY BEST PRACTICE METRICS IN …
Fourteen pharmaceutical companies participated in a telephone survey of best prac- tices and metrics in clinical data management and statistics. Eleven companies were global and three …
Flow of Data in Clinical Trials - Chalmers
We describe the flow of clinical trial data throughout its journey from visit/collection to CSR to NDA/BLA, provide useful metrics to show how much time is saved by using data standards …
Finding the Right Balance - Data Management Surveillance …
Based on a Partnership Manual, which describes the interface processes between the Sponsor and the CRO, different tools were developed to continuously check the data of the clinical trial …
Sponsor Oversight of CROs Data Management and
Small biotechnology company sponsors of clinical trials may have none, or just one or two staff members familiar with these rules that serve as a biostatistician and data manager to review …
Metrics for Data Repositories and Knowledgebases: …
Metrics provide systematic parameters for evaluating the cost and benefits of a repository to the various repository stakeholders, including research institutions, funding agencies, and the …
INDEPENDENT RESEARCH SITES: THREE KEY PERFORMANCE …
Many sites don’t know which metrics to track or how to use those metrics to their advantage. In the absence of quality performance data and industry benchmarks, sites often struggle to …
Visualizing clinical operational metrics to enable decision …
There are many ways to track, report, and visualize metrics, ranging from raw percentages to traffic lights. We developed a visualization scheme for fifteen key metrics, some of which are …
Data and Analytics Fast-track your health system performance …
Clinical decision-making is too often disconnected from financial diagnostics. Thus clinicians sometimes make care decisions without considering the financial impact — for the …
