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| data management in public health: An Introduction to Statistical Computing with SAS (First Edition) Brianna Magnusson, Caroline Stampfel, 2018-12-31 SAS Data Management for Public Health: An Introduction equips readers with the tools and knowledge they need to prepare public health data in SAS Data Management software for use in analysis. Highly accessible in nature, the book is specifically designed to help students who are new to SAS learn and master the system. The book is organized into 20 lessons. The opening lessons introduce SAS and provide tips and best practices for exploring data. Students are introduced to PROC MEANS, FREQ, UNIVARIATE, and PROC SGPLOT. They learn how to import data; merge, concatenate, and manage variables; perform data cleanup; and recode categorical and continuous variables. Specific lessons address comments, labels, and titles, formatting variables, conditional recoding, DO groups, arrays for recoding, and categorical data analysis. Closing lessons introduce stratified and subpopulation analysis, as well as logistic regression. The book includes an appendix to help students navigate and use SAS Studio. SAS Data Management for Public Health is an ideal resource for standalone courses in which SAS is taught or to complement any biostatistics or epidemiology course where students need to use SAS to analyze their data. Brianna Magnusson holds a Ph.D. in epidemiology and a M.P.H. from Virginia Commonwealth University. She is an associate professor in the Department of Public Health at Brigham Young University. Dr. Magnusson's research focuses on sexual and reproductive health with emphasis on factors influencing sexual decision-making. Caroline Stampfel holds an M.P.H. with a concentration in environmental epidemiology from the Yale School of Public Health. She serves as the director of programs for the Association of Maternal & Child Health Programs and leads a team of maternal and child health experts using data-driven, innovative approaches to improve the health and well-being of women, children, youth, families, and communities. |
| data management in public health: Encyclopedia of Public Health Wilhelm Kirch, 2008-06-13 The Encyclopedic Reference of Public Health presents the most important definitions, principles and general perspectives of public health, written by experts of the different fields. The work includes more than 2,500 alphabetical entries. Entries comprise review-style articles, detailed essays and short definitions. Numerous figures and tables enhance understanding of this little-understood topic. Solidly structured and inclusive, this two-volume reference is an invaluable tool for clinical scientists and practitioners in academia, health care and industry, as well as students, teachers and interested laypersons. |
| data management in public health: Medical Data Management Florian Leiner, Wilhelm Gaus, Reinhold Haux, Petra Knaup-Gregori, 2003-01-14 Medical Data Management is a systematic introduction to the basic methodology of professional clinical data management. It emphasizes generic methods of medical documentation applicable to such diverse tasks as the electronic patient record, maintaining a clinical trials database, and building a tumor registry. This book is for all students in medical informatics and health information management, and it is ideal for both the undergraduate and the graduate levels. The book also guides professionals in the design and use of clinical information systems in various health care settings. It is an invaluable resource for all health care professionals involved in designing, assessing, adapting, or using clinical data management systems in hospitals, outpatient clinics, study centers, health plans, etc. The book combines a consistent theoretical foundation of medical documentation methods outlining their practical applicability in real clinical data management systems. Two new chapters detail hospital information systems and clinical trials. There is a focus on the international classification of diseases (ICD-9 and -10) systems, as well as a discussion on the difference between the two codes. All chapters feature exercises, bullet points, and a summary to provide the reader with essential points to remember. New to the Third Edition is a comprehensive section comprised of a combined Thesaurus and Glossary which aims to clarify the unclear and sometimes inconsistent terminology surrounding the topic. |
| data management in public health: Health Information Management: Empowering Public Health J. Mantas, R. Šendelj, I. Ognjanović, 2020-10-14 The effective and efficient management of healthcare institutions is key to the successful development of national health systems. In an increasingly digital society, the skills involved in health information management become a primary factor in ensuring this development. Employment is projected to grow in all areas of healthcare, but especially in those related to information management, such as applied informatics, public health informatics and medical informatics. This book, Health Information Management: Empowering Public Health, aims to provide a clear and comprehensive introduction to the study and development of health information management. It is designed for use by university and vocational courses to train allied health professionals. It can also be used as an in-service training tool for new healthcare-facility personnel, for those working in government healthcare institutions, independent billing and health assurance services, or individually by health information specialists. The book describes health information management, and explains how it merges the fields of health care and information technology. Readers will learn logical thinking and communication, and will be introduced to the organizational processes in healthcare institutions, as well as finding out how to organize and analyze health care data; accurately record, store and assess health data; use an electronic patient record system; and provide statistical analysis and interpret the results. The book will be of interest to all those wishing to gain a better insight into what is involved health information management, and to all those studying the subject. |
| data management in public health: 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. |
| data management in public health: Statistics & Data Analytics for Health Data Management Nadinia A. Davis, Betsy J. Shiland, 2015-12-04 Introducing Statistics & Data Analytics for Health Data Management by Nadinia Davis and Betsy Shiland, an engaging new text that emphasizes the easy-to-learn, practical use of statistics and manipulation of data in the health care setting. With its unique hands-on approach and friendly writing style, this vivid text uses real-world examples to show you how to identify the problem, find the right data, generate the statistics, and present the information to other users. Brief Case scenarios ask you to apply information to situations Health Information Management professionals encounter every day, and review questions are tied to learning objectives and Bloom's taxonomy to reinforce core content. From planning budgets to explaining accounting methodologies, Statistics & Data Analytics addresses the key HIM Associate Degree-Entry Level competencies required by CAHIIM and covered in the RHIT exam. - Meets key HIM Associate Degree-Entry Level competencies, as required by CAHIIM and covered on the RHIT registry exam, so you get the most accurate and timely content, plus in-depth knowledge of statistics as used on the job. - Friendly, engaging writing style offers a student-centered approach to the often daunting subject of statistics. - Four-color design with ample visuals makes this the only textbook of its kind to approach bland statistical concepts and unfamiliar health care settings with vivid illustrations and photos. - Math review chapter brings you up-to-speed on the math skills you need to complete the text. - Brief Case scenarios strengthen the text's hands-on, practical approach by taking the information presented and asking you to apply it to situations HIM professionals encounter every day. - Takeaway boxes highlight key points and important concepts. - Math Review boxes remind you of basic arithmetic, often while providing additional practice. - Stat Tip boxes explain trickier calculations, often with Excel formulas, and warn of pitfalls in tabulation. - Review questions are tied to learning objectives and Bloom's taxonomy to reinforce core content and let you check your understanding of all aspects of a topic. - Integrated exercises give you time to pause, reflect, and retain what you have learned. - Answers to integrated exercises, Brief Case scenarios, and review questions in the back of the book offer an opportunity for self-study. - Appendix of commonly used formulas provides easy reference to every formula used in the textbook. - A comprehensive glossary gives you one central location to look up the meaning of new terminology. - Instructor resources include TEACH lesson plans, PowerPoint slides, classroom handouts, and a 500-question Test Bank in ExamView that help prepare instructors for classroom lectures. |
| data management in public health: Management of Emerging Public Health Issues and Risks Benoit Roig, Karine Weiss, Veronique Thireau, 2018-11-13 Management of Emerging Public Health Issues and Risks: Multidisciplinary Approaches to the Changing Environment addresses the threats facing the rapidly changing world and provides guidance on how to manage risks to population health. Unlike conventional and recognized risks (major, industrial, and natural), emerging risks are characterized by low or non-existent scientific knowledge, high levels of uncertainty, and different levels of acceptability by the relevant authorities and exposed populations. Emerging risk must be analyzed through multiple and crossed approaches identifying the phenomenon linked to the emergence of risk but also by combining scientific, policy and social data in order to provide more enlightened decision making. Management of Emerging Public Health Issues and Risks: Multidisciplinary Approaches to the Changing Environment provides examples of transdisciplinary approaches used to characterize, analyze, and manage emerging risks. This book will be useful for public health researchers, policy makers, and students as well as those working in emergency management, risk management, security, environmental health, nanomaterials, and food science. - Presents emerging risks from the technological, environmental, health, and energy sectors, as well as their social impacts - Contextualizes emerging risks as new threats, existing threats in new locations, and known issues, which are newly recognized as risks due to increased scientific knowledge - Includes case studies from around the world to reinforce concepts |
| data management in public health: 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. |
| data management in public health: Public Health Informatics and Information Systems J.A. Magnuson, Paul C. Fu, Jr., 2013-11-29 This revised edition covers all aspects of public health informatics and discusses the creation and management of an information technology infrastructure that is essential in linking state and local organizations in their efforts to gather data for the surveillance and prevention. Public health officials will have to understand basic principles of information resource management in order to make the appropriate technology choices that will guide the future of their organizations. Public health continues to be at the forefront of modern medicine, given the importance of implementing a population-based health approach and to addressing chronic health conditions. This book provides informatics principles and examples of practice in a public health context. In doing so, it clarifies the ways in which newer information technologies will improve individual and community health status. This book's primary purpose is to consolidate key information and promote a strategic approach to information systems and development, making it a resource for use by faculty and students of public health, as well as the practicing public health professional. Chapter highlights include: The Governmental and Legislative Context of Informatics; Assessing the Value of Information Systems; Ethics, Information Technology, and Public Health; and Privacy, Confidentiality, and Security. Review questions are featured at the end of every chapter. Aside from its use for public health professionals, the book will be used by schools of public health, clinical and public health nurses and students, schools of social work, allied health, and environmental sciences. |
| data management in public health: Applied Spatial Statistics for Public Health Data Lance A. Waller, Carol A. Gotway, 2004-07-29 While mapped data provide a common ground for discussions between the public, the media, regulatory agencies, and public health researchers, the analysis of spatially referenced data has experienced a phenomenal growth over the last two decades, thanks in part to the development of geographical information systems (GISs). This is the first thorough overview to integrate spatial statistics with data management and the display capabilities of GIS. It describes methods for assessing the likelihood of observed patterns and quantifying the link between exposures and outcomes in spatially correlated data. This introductory text is designed to serve as both an introduction for the novice and a reference for practitioners in the field Requires only minimal background in public health and only some knowledge of statistics through multiple regression Touches upon some advanced topics, such as random effects, hierarchical models and spatial point processes, but does not require prior exposure Includes lavish use of figures/illustrations throughout the volume as well as analyses of several data sets (in the form of data breaks) Exercises based on data analyses reinforce concepts |
| data management in public health: Integrating Social Care into the Delivery of Health Care National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Health Care Services, Committee on Integrating Social Needs Care into the Delivery of Health Care to Improve the Nation's Health, 2020-01-30 Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation's Health was released in September 2019, before the World Health Organization declared COVID-19 a global pandemic in March 2020. Improving social conditions remains critical to improving health outcomes, and integrating social care into health care delivery is more relevant than ever in the context of the pandemic and increased strains placed on the U.S. health care system. The report and its related products ultimately aim to help improve health and health equity, during COVID-19 and beyond. The consistent and compelling evidence on how social determinants shape health has led to a growing recognition throughout the health care sector that improving health and health equity is likely to depend †at least in part †on mitigating adverse social determinants. This recognition has been bolstered by a shift in the health care sector towards value-based payment, which incentivizes improved health outcomes for persons and populations rather than service delivery alone. The combined result of these changes has been a growing emphasis on health care systems addressing patients' social risk factors and social needs with the aim of improving health outcomes. This may involve health care systems linking individual patients with government and community social services, but important questions need to be answered about when and how health care systems should integrate social care into their practices and what kinds of infrastructure are required to facilitate such activities. Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation's Health examines the potential for integrating services addressing social needs and the social determinants of health into the delivery of health care to achieve better health outcomes. This report assesses approaches to social care integration currently being taken by health care providers and systems, and new or emerging approaches and opportunities; current roles in such integration by different disciplines and organizations, and new or emerging roles and types of providers; and current and emerging efforts to design health care systems to improve the nation's health and reduce health inequities. |
| data management in public health: Big Data and Health Analytics Katherine Marconi, Harold Lehmann, 2014-12-20 This book provides frameworks, use cases, and examples that illustrate the role of big data and analytics in modern health care, including how public health information can inform health delivery. Written for health care professionals and executives, this book presents the current thinking of academic and industry researchers and leaders from around the world. Using non-technical language, it includes case studies that illustrate the business processes that underlie the use of big data and health analytics to improve health care delivery. |
| data management in public health: Big Data, Big Challenges: A Healthcare Perspective Mowafa Househ, Andre W. Kushniruk, Elizabeth M. Borycki, 2019-02-26 This is the first book to offer a comprehensive yet concise overview of the challenges and opportunities presented by the use of big data in healthcare. The respective chapters address a range of aspects: from health management to patient safety; from the human factor perspective to ethical and economic considerations, and many more. By providing a historical background on the use of big data, and critically analyzing current approaches together with issues and challenges related to their applications, the book not only sheds light on the problems entailed by big data, but also paves the way for possible solutions and future research directions. Accordingly, it offers an insightful reference guide for health information technology professionals, healthcare managers, healthcare practitioners, and patients alike, aiding them in their decision-making processes; and for students and researchers whose work involves data science-related research issues in healthcare. |
| data management in public health: Race, Ethnicity, and Language Data Institute of Medicine, Board on Health Care Services, Subcommittee on Standardized Collection of Race/Ethnicity Data for Healthcare Quality Improvement, 2009-12-30 The goal of eliminating disparities in health care in the United States remains elusive. Even as quality improves on specific measures, disparities often persist. Addressing these disparities must begin with the fundamental step of bringing the nature of the disparities and the groups at risk for those disparities to light by collecting health care quality information stratified by race, ethnicity and language data. Then attention can be focused on where interventions might be best applied, and on planning and evaluating those efforts to inform the development of policy and the application of resources. A lack of standardization of categories for race, ethnicity, and language data has been suggested as one obstacle to achieving more widespread collection and utilization of these data. Race, Ethnicity, and Language Data identifies current models for collecting and coding race, ethnicity, and language data; reviews challenges involved in obtaining these data, and makes recommendations for a nationally standardized approach for use in health care quality improvement. |
| data management in public health: New Horizons for a Data-Driven Economy José María Cavanillas, Edward Curry, Wolfgang Wahlster, 2016-04-04 In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment. |
| data management in public health: Handbook of Research on Information Management and One Health Jorge Lima de Magalhães, Zulmira Maria de Araújo Hartz, George Leal Jamil, Henrique Silveira, Liliane Jamil, 2021-10-22 This book studies the management of Big Data in Health information specifically for the new concept One Health and Digital Health, concerning ailments that plague neglected populations and provides practical approaches by scientists and practitioners in the field that will assist in managing the knowledge of Big Data in information Health, to strengthen the skills and training of decision-making managers with tactical and strategic analysis, planning and decision making. This book project aims to-- |
| data management in public health: R for Health Data Science Ewen Harrison, Riinu Pius, 2020-12-31 In this age of information, the manipulation, analysis, and interpretation of data have become a fundamental part of professional life; nowhere more so than in the delivery of healthcare. From the understanding of disease and the development of new treatments, to the diagnosis and management of individual patients, the use of data and technology is now an integral part of the business of healthcare. Those working in healthcare interact daily with data, often without realising it. The conversion of this avalanche of information to useful knowledge is essential for high-quality patient care. R for Health Data Science includes everything a healthcare professional needs to go from R novice to R guru. By the end of this book, you will be taking a sophisticated approach to health data science with beautiful visualisations, elegant tables, and nuanced analyses. Features Provides an introduction to the fundamentals of R for healthcare professionals Highlights the most popular statistical approaches to health data science Written to be as accessible as possible with minimal mathematics Emphasises the importance of truly understanding the underlying data through the use of plots Includes numerous examples that can be adapted for your own data Helps you create publishable documents and collaborate across teams With this book, you are in safe hands – Prof. Harrison is a clinician and Dr. Pius is a data scientist, bringing 25 years’ combined experience of using R at the coal face. This content has been taught to hundreds of individuals from a variety of backgrounds, from rank beginners to experts moving to R from other platforms. |
| data management in public health: The Palgrave Handbook of Global Health Data Methods for Policy and Practice Sarah B. Macfarlane, Carla AbouZahr, 2019-03-05 This handbook compiles methods for gathering, organizing and disseminating data to inform policy and manage health systems worldwide. Contributing authors describe national and international structures for generating data and explain the relevance of ethics, policy, epidemiology, health economics, demography, statistics, geography and qualitative methods to describing population health. The reader, whether a student of global health, public health practitioner, programme manager, data analyst or policymaker, will appreciate the methods, context and importance of collecting and using global health data. |
| data management in public health: Population Health Management Anne Hewitt, PhD, MA, Julie Mascari, MHA, Stephen Wagner, PhD, FACHE, LFACMPE, 2021-10-06 “This is an outstanding book and I would highly recommend it for any professional or faculty in a current public health role, and absolutely for a student in the fields of public health, nursing, health administration, health education, medicine, and information technology (artificial intelligence)... This book provides the resources for professionals to learn and apply theory, analytics, quality, and services to understand populations with the ultimate goal of transforming U.S. health care. ---Doody's Review Service, 5 stars Population Health Management: Strategies, Tools, Applications, and Outcomes uniquely combines perspectives and concepts from community, public, and global health and aligns them with the essentials of health management. Written by leading experts in academia and industry, this text emphasizes the integration of management skills necessary to deliver quality care while producing successful outcomes sensitive to the needs of diverse populations. Designed to be both student-friendly and comprehensive, this text utilizes various models, frameworks, case examples, chapter podcasts, and more to illustrate foundational knowledge and impart the skills necessary for health care managers to succeed throughout the health care sector. The book spans core topics such as community needs assessments, social determinants of health, the role of data analytics, managerial epidemiology, value-based care payment models, and new population health delivery models. COVID-19 examples throughout chapters illustrate population health management strategies solving real-world challenges. Practical and outcomes-driven, Population Health Management prepares students in health administration and management, public health, social work, allied health, and other health professions for the challenges of an evolving health care ecosystem and the changing roles in the health management workforce. Key Features: Highlights up-to-date topics focusing on social marketing, design thinking for innovation, adopting virtual care and telehealth strategies, and social marketing ideas Introduces new population health management skills and tools such as the Social Vulnerability Index, Policy Map, PRAPARE, the PHM Framework, Design Thinking and Digital Messaging Incorporates Did You Know? callouts, chapter-based podcasts, and discussion questions to help explain real-world situations and examples that students and health professionals may encounter as administrators and managers Includes four full-length case studies focusing on the co-production of health, implementing a population health data analytics platform, health equity, and collaborative leadership Connects chapter objectives with the National Center for Healthcare Leadership (NCHL) and the Public Health Foundation (PHF) competencies Purchase includes digital access for use on most mobile devices or computers, as well as full suite of instructor resources with Instructor's Manual, PowerPoint slides, test bank, and sample syllabus |
| data management in public health: Geospatial Technology and Smart Cities Poonam Sharma, 2021-07-06 This book presents fundamental and applied research in developing geospatial modeling solutions to manage the challenges that urban areas are facing today. It aims to connect the academics, researchers, experts, town planners, investors and government officials to exchange ideas. The areas addressed include urban heat island analysis, urban flood vulnerability and risk mapping, green spaces, solar energy, infrastructure management, among others. The book suggests directions for smart city research and outlines practical propositions. As an emerging and critical area of research and development, much research is now being done with regard to cities. At the international level and in India alike, the “smart cities” concept is a vital topic for universities and research centers, and well as for civic bodies, town planners and policymakers. As such, the book offers a valuable resource for a broad readership. |
| data management in public health: Public Health in India Diatha Krishna Sundar, Shashank Garg, Isha Garg, 2015-06-05 Despite rapid advances in modern medicine and state-of-the-art health care services in the private sector, primary health care in India remains inaccessible to a majority of the population. Besides, even policymakers often do not have access to real-time data to fine-tune their policies or design appropriate research and intervention programmes. Drawing on field experiences, this volume brings together scholars and practitioners to examine public health from different perspectives. It discusses practical and applied issues related to the health sector, especially the role of Information and Communications Technology (ICT); participation of civil society; service delivery; quality evaluation; consumer empowerment; data management; and research and intervention. This book will be useful to scholars, students and practitioners of public health in developing countries such as India. It will also interest policymakers, health care professionals, and departments of public health management and those concerned with community medicine. |
| data management in public health: The Health Care Data Guide Lloyd P. Provost, Sandra K. Murray, 2011-12-06 The Health Care Data Guide is designed to help students and professionals build a skill set specific to using data for improvement of health care processes and systems. Even experienced data users will find valuable resources among the tools and cases that enrich The Health Care Data Guide. Practical and step-by-step, this book spotlights statistical process control (SPC) and develops a philosophy, a strategy, and a set of methods for ongoing improvement to yield better outcomes. Provost and Murray reveal how to put SPC into practice for a wide range of applications including evaluating current process performance, searching for ideas for and determining evidence of improvement, and tracking and documenting sustainability of improvement. A comprehensive overview of graphical methods in SPC includes Shewhart charts, run charts, frequency plots, Pareto analysis, and scatter diagrams. Other topics include stratification and rational sub-grouping of data and methods to help predict performance of processes. Illustrative examples and case studies encourage users to evaluate their knowledge and skills interactively and provide opportunity to develop additional skills and confidence in displaying and interpreting data. Companion Web site: www.josseybass.com/go/provost |
| data management in public health: Secondary Data Sources for Public Health Sarah Boslaugh, 2007-04-09 Secondary data play an increasingly important role in epidemiology and public health research and practice; examples of secondary data sources include national surveys such as the BRFSS and NHIS, claims data for the Medicare and Medicaid systems, and public vital statistics records. Although a wealth of secondary data is available, it is not always easy to locate and access appropriate data to address a research or policy question. This practical guide circumvents these difficulties by providing an introduction to secondary data and issues specific to its management and analysis, followed by an enumeration of major sources of secondary data in the United States. Entries for each data source include the principal focus of the data, years for which it is available, history and methodology of the data collection process, and information about how to access the data and supporting materials, including relevant details about file structure and format. |
| data management in public health: Sharing Research Data to Improve Public Health in Africa National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Committee on Population, 2015-09-18 Sharing research data on public health issues can promote expanded scientific inquiry and has the potential to advance improvements in public health. Although sharing data is the norm in some research fields, sharing of data in public health is not as firmly established. In March 2015, the National Research Council organized an international conference in Stellenbosch, South Africa, to explore the benefits of and barriers to sharing research data within the African context. The workshop brought together public health researchers and epidemiologists primarily from the African continent, along with selected international experts, to talk about the benefits and challenges of sharing data to improve public health, and to discuss potential actions to guide future work related to public health research data sharing. Sharing Research Data to Improve Public Health in Africa summarizes the presentations and discussions from this workshop. |
| data management in public health: 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. |
| data management in public health: Safe Management of Wastes from Health-care Activities Yves Chartier, 2014 This is the second edition of the WHO handbook on the safe, sustainable and affordable management of health-care waste--commonly known as the Blue Book. The original Blue Book was a comprehensive publication used widely in health-care centers and government agencies to assist in the adoption of national guidance. It also provided support to committed medical directors and managers to make improvements and presented practical information on waste-management techniques for medical staff and waste workers. It has been more than ten years since the first edition of the Blue Book. During the intervening period, the requirements on generators of health-care wastes have evolved and new methods have become available. Consequently, WHO recognized that it was an appropriate time to update the original text. The purpose of the second edition is to expand and update the practical information in the original Blue Book. The new Blue Book is designed to continue to be a source of impartial health-care information and guidance on safe waste-management practices. The editors' intention has been to keep the best of the original publication and supplement it with the latest relevant information. The audience for the Blue Book has expanded. Initially, the publication was intended for those directly involved in the creation and handling of health-care wastes: medical staff, health-care facility directors, ancillary health workers, infection-control officers and waste workers. This is no longer the situation. A wider range of people and organizations now have an active interest in the safe management of health-care wastes: regulators, policy-makers, development organizations, voluntary groups, environmental bodies, environmental health practitioners, advisers, researchers and students. They should also find the new Blue Book of benefit to their activities. Chapters 2 and 3 explain the various types of waste produced from health-care facilities, their typical characteristics and the hazards these wastes pose to patients, staff and the general environment. Chapters 4 and 5 introduce the guiding regulatory principles for developing local or national approaches to tackling health-care waste management and transposing these into practical plans for regions and individual health-care facilities. Specific methods and technologies are described for waste minimization, segregation and treatment of health-care wastes in Chapters 6, 7 and 8. These chapters introduce the basic features of each technology and the operational and environmental characteristics required to be achieved, followed by information on the potential advantages and disadvantages of each system. To reflect concerns about the difficulties of handling health-care wastewaters, Chapter 9 is an expanded chapter with new guidance on the various sources of wastewater and wastewater treatment options for places not connected to central sewerage systems. Further chapters address issues on economics (Chapter 10), occupational safety (Chapter 11), hygiene and infection control (Chapter 12), and staff training and public awareness (Chapter 13). A wider range of information has been incorporated into this edition of the Blue Book, with the addition of two new chapters on health-care waste management in emergencies (Chapter 14) and an overview of the emerging issues of pandemics, drug-resistant pathogens, climate change and technology advances in medical techniques that will have to be accommodated by health-care waste systems in the future (Chapter 15). |
| data management in public health: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| data management in public health: Biostatistics and Computer-based Analysis of Health Data Using SAS Christophe Lalanne, Mounir Mesbah, 2017-06-22 This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research.The use of SAS for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics. This practical book is primarily intended for health researchers with a basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epidemiological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential SAS commands. - Presents the use of SAS software in the statistical approach for the management of data modeling - Includes elements of the language and descriptive statistics - Supplies measures of association, comparison of means, and proportions for two or more samples - Explores linear and logistic regression - Provides survival data analysis |
| data management in public health: The Future of Public Health Committee for the Study of the Future of Public Health, Division of Health Care Services, Institute of Medicine, 1988-01-15 The Nation has lost sight of its public health goals and has allowed the system of public health to fall into 'disarray', from The Future of Public Health. This startling book contains proposals for ensuring that public health service programs are efficient and effective enough to deal not only with the topics of today, but also with those of tomorrow. In addition, the authors make recommendations for core functions in public health assessment, policy development, and service assurances, and identify the level of government--federal, state, and local--at which these functions would best be handled. |
| data management in public health: Essentials of Public Health Management L. Fleming Fallon (Jr.), Eric Zgodzinski, 2009 In the wake of 9/11, effective management of public health departments has become vitally important, as these organizations and agencies will be in the front line of any bioterror or chemical attack. Written by practitioners for other practitioners and students who want to pursue public health careers, this book provides a practical, non-theoretical approach useful for the hands-on management of these complex organizations and their daily operations. With accessible writing and many real life applications, this concise new volume serves departments at all levels--federal, state, city and county. |
| data management in public health: 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. |
| data management in public health: Public Health Management of Disasters Linda Young Landesman, 2005 This book can serve as a quick reference for either public health practitioners or public safety personnel who need quick information about disaster response for natural, man-made, and weapons of mass destruction. In addition, it identifies the public health role in each aspect of disaster activity, something that no other book has done. It also organizes morbidity and mortality concerns by disaster so that these negative outcomes can be referred to quickly. |
| data management in public health: Engaging Researchers with Data Management Connie Clare, Maria J. Cruz, Elli Papadopoulou, James Savage (Research associate), Marta Teperek, Yan Wang, Iza Witkowska, Joanne Yeomans, 2019 Engaging Researchers with Data Management is an invaluable collection of 24 case studies, drawn from institutions across the globe, that demonstrate clearly and practically how to engage the research community with RDM. These case studies together illustrate the variety of innovative strategies research institutions have developed to engage with their researchers about managing research data. Each study is presented concisely and clearly, highlighting the essential ingredients that led to its success and challenges encountered along the way. By interviewing key staff about their experiences. |
| data management in public health: The Importance of Health Informatics in Public Health during a Pandemic J. Mantas, A. Hasman, M.S. Househ, 2020-07-24 The COVID-19 pandemic has increased the focus on health informatics and healthcare technology for policy makers and healthcare professionals worldwide. This book contains the 110 papers (from 160 submissions) accepted for the 18th annual International Conference on Informatics, Management, and Technology in Healthcare (ICIMTH 2020), held virtually in Athens, Greece, from 3 – 5 July 2020. The conference attracts scientists working in the field of Biomedical and Health Informatics from all continents, and this year it was held as a Virtual Conference, by means of teleconferencing, due to the COVID-19 pandemic and the consequent lockdown in many countries around the world. The call for papers for the conference started in December 2019, when signs of the new virus infection were not yet evident, so early submissions were on the usual topics as announced. But papers submitted after mid-March were mostly focused on the first results of the pandemic analysis with respect to informatics in different countries and with different perspectives of the spread of the virus and its influence on public health across the world. This book therefore includes papers on the topic of the COVID-19 pandemic in relation to informatics reporting from hospitals and institutions from around the world, including South Korea, Europe, and the USA. The book encompasses the field of biomedical and health informatics in a very broad framework, and the timely inclusion of papers on the current pandemic will make it of particular interest to all those involved in the provision of healthcare everywhere. |
| data management in public health: Research Data Management Joyce M. Ray, 2014 It has become increasingly accepted that important digital data must be retained and shared in order to preserve and promote knowledge, advance research in and across all disciplines of scholarly endeavor, and maximize the return on investment of public funds. To meet this challenge, colleges and universities are adding data services to existing infrastructures by drawing on the expertise of information professionals who are already involved in the acquisition, management and preservation of data in their daily jobs. Data services include planning and implementing good data management practices, thereby increasing researchers' ability to compete for grant funding and ensuring that data collections with continuing value are preserved for reuse. This volume provides a framework to guide information professionals in academic libraries, presses, and data centers through the process of managing research data from the planning stages through the life of a grant project and beyond. It illustrates principles of good practice with use-case examples and illuminates promising data service models through case studies of innovative, successful projects and collaborations. |
| data management in public health: Introduction to Public Health Mary-Jane Schneider, 2011 New to the Third Edition: New or expanded sections covering: Pandemic Flu Response to Hurricane Katrina FDA Regulation of Tobacco Promoting Physical Activity Poisoning (now the #2 cause of injury death) Nonfatal Traumatic Brain Injuries National Children's Study Coal Ash and other unregulated waste from power plants Medical errors Information Technology New information/discussion on: H1N1 swine flu Conflicts of interest in drug trials Problems in planning for the 2010 census Genomic medicine Cell phones/texting while driving National birth defects prevention study The new HPV vaccine controversy Lead paint in toys imported from china Bisphenol A (BPA) and phthalates The recent Salmonella outbreak in Peanut Butter Contaminated drug imports from China Managed care efforts to control medical costs Evaluation of Healthy People 2010 and planning for Healthy People 2020 New examples including: Andrew Speaker/Extremely Drug Resistant (XDR) Tuberculosis Football players and increased risk for dementia later in life. |
| data management in public health: Improving Health Service Delivery in Developing Countries David H. Peters, 2009 Reliable information on how health service strategies affect the poor is in short supply. In an attempt to redress the imbalance, 'Improving Health Service Delivery in Developing Countries' presents evidence on strategies for strengthening health service delivery, based on systematic reviews of the literature, quantitative and qualitative analyses of existing data, and seven country case studies. The authors also explore how changes in coverage of different health services affect each other on the national level. Finally, the authors explain why setting international targets for health services has been not been successful and offer an alternative approach based on a specific country's experience.The book's findings are clear and hopeful: There are many ways to improve health services. Measuring change and using information to guide decisions and inform stakeholders are critically important for successful implementation. Asking difficult questions, using information intelligently, and involving key stakeholders and institutions are central to the learning and doing practices that underlie successful health service delivery. |
| data management in public health: Epidemiology with R Bendix Carstensen, 2021-01-14 This practical guide is designed for students and researchers with an existing knowledge of R who wish to learn how to apply it in an epidemiological context and exploit its versatility. It also serves as a broader introduction to the quantitative aspects of modern practical epidemiology. The standard tools used in epidemiology are described and the practical use of R for these is clearly explained and laid out. R code examples, many with output, are embedded throughout the text. The entire code is also available on the companion website so that readers can reproduce all the results and graphs featured in the book. Epidemiology with R is an advanced textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners in the fields of human and non-human epidemiology, public health, veterinary science, and biostatistics. |
| data management in public health: Public Health Research Methods Greg Guest, Emily E. Namey, 2015 Providing a comprehensive foundation for planning, executing, and monitoring public health research of all types, this book goes beyond traditional epidemiologic research designs to cover technology-based approaches emerging in the new public health landscape. |
| data management in public health: Assessing the National Health Information System Health Metrics Network, World Health Organization, 2008 The Health Metrics Network (HMN) was launched in 2005 to help countries ... improve global health by strengthening the systems that generate health-related information for evidence-based decision-making.--Introd. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
