Download or read book Handbook of Data Analysis of Electronic Health Records EHR Using SAS Software written by Behrouz Ehsani-Moghaddam and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Electronic Health Records (EHR) are longitudinal data that are stored in a database that captures current and new patients at different points in time. Since EHR data come from multiple different vendors and open-source products, they can be messy, inconsistent, and often need to be harmonized and reformatted properly before they can provide real-world insights about patients using statistical techniques. This book goes beyond the general data manipulation, viewing the data analysis issues in a wider and more practical context. It covers all major steps of analysis of EHR data, even those instructions that cannot be taught in any classroom. The reader can have hands-on experience using the codes that are provided in the book and by utilizing the accompanying data that are available for free. This book is not restricted to one specific discipline but rather will be of interest to scientists working in any area where analyzing electronic public health data using SAS program is necessary. The material is aimed at the reader who are already familiar with applied statistics at an undergraduate level or higher"--

Download or read book A Researcher s Guide to Using Electronic Health Records written by Neal D. Goldstein and published by CRC Press. This book was released on 2023-07-25 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an age when electronic health records (EHRs) are an increasingly important source of data, this essential textbook provides both practical and theoretical guidance to researchers conducting epidemiological or clinical analysis through EHRs. Split into three parts, the book covers the research journey from start to finish. Part 1 focuses on the challenges inherent when working with EHRs, from access to data management, and raising issues such as completeness and accuracy which impact the validity of any research project. Part 2 examines the core research process itself, with chapters on research design, sampling, and analysis, as well as emerging methodological techniques. Part 3 demonstrates how EHR research can be made meaningful, from presentation to publication, and includes how findings can be applied to real-world issues of public health. Supported by case studies throughout, and applicable across a range of research software programs (including R, SPSS, and SAS), this is the ideal text for students and researchers engaging with EHRs across epidemiological and clinical research.

Download or read book Big Data in Healthcare written by Farrokh Alemi and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book introduces health administrators, nurses, physician assistants, medical students, and data scientists to statistical analysis of electronic health records (EHRs). The future of medicine depends on understanding patterns in EHRs. This book shows how to use EHRs for precision and predictive medicine"--

Download or read book Applied Health Analytics and Informatics Using SAS written by Joseph M. Woodside and published by SAS Institute. This book was released on 2018-11-08 with total page 429 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage health data into insight! Applied Health Analytics and Informatics Using SAS describes health anamatics, a result of the intersection of data analytics and health informatics. Healthcare systems generate nearly a third of the world’s data, and analytics can help to eliminate medical errors, reduce readmissions, provide evidence-based care, demonstrate quality outcomes, and add cost-efficient care. This comprehensive textbook includes data analytics and health informatics concepts, along with applied experiential learning exercises and case studies using SAS Enterprise MinerTM within the healthcare industry setting. Topics covered include: Sampling and modeling health data – both structured and unstructured Exploring health data quality Developing health administration and health data assessment procedures Identifying future health trends Analyzing high-performance health data mining models Applied Health Analytics and Informatics Using SAS is intended for professionals, lifelong learners, senior-level undergraduates, graduate-level students in professional development courses, health informatics courses, health analytics courses, and specialized industry track courses. This textbook is accessible to a wide variety of backgrounds and specialty areas, including administrators, clinicians, and executives. This book is part of the SAS Press program.

Download or read book Administrative Healthcare Data written by Craig Dickstein and published by SAS Institute. This book was released on 2014-10 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explains the source and content of administrative healthcare data, which is the product of financial reimbursement for healthcare services. The book integrates the business knowledge of healthcare data with practical and pertinent case studies as shown in SAS Enterprise Guide.

Download or read book Statistics and Machine Learning Methods for EHR Data written by Hulin Wu and published by CRC Press. This book was released on 2020-12-09 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: The use of Electronic Health Records (EHR)/Electronic Medical Records (EMR) data is becoming more prevalent for research. However, analysis of this type of data has many unique complications due to how they are collected, processed and types of questions that can be answered. This book covers many important topics related to using EHR/EMR data for research including data extraction, cleaning, processing, analysis, inference, and predictions based on many years of practical experience of the authors. The book carefully evaluates and compares the standard statistical models and approaches with those of machine learning and deep learning methods and reports the unbiased comparison results for these methods in predicting clinical outcomes based on the EHR data. Key Features: Written based on hands-on experience of contributors from multidisciplinary EHR research projects, which include methods and approaches from statistics, computing, informatics, data science and clinical/epidemiological domains. Documents the detailed experience on EHR data extraction, cleaning and preparation Provides a broad view of statistical approaches and machine learning prediction models to deal with the challenges and limitations of EHR data. Considers the complete cycle of EHR data analysis. The use of EHR/EMR analysis requires close collaborations between statisticians, informaticians, data scientists and clinical/epidemiological investigators. This book reflects that multidisciplinary perspective.

Download or read book Secondary Analysis of Electronic Health Records written by MIT Critical Data and published by Springer. This book was released on 2016-09-09 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.

Download or read book Real World Health Care Data Analysis written by Douglas Faries and published by SAS Institute. This book was released on 2020-01-15 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover best practices for real world data research with SAS code and examples Real world health care data is common and growing in use with sources such as observational studies, patient registries, electronic medical record databases, insurance healthcare claims databases, as well as data from pragmatic trials. This data serves as the basis for the growing use of real world evidence in medical decision-making. However, the data itself is not evidence. Analytical methods must be used to turn real world data into valid and meaningful evidence. Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS brings together best practices for causal comparative effectiveness analyses based on real world data in a single location and provides SAS code and examples to make the analyses relatively easy and efficient. The book focuses on analytic methods adjusted for time-independent confounding, which are useful when comparing the effect of different potential interventions on some outcome of interest when there is no randomization. These methods include: propensity score matching, stratification methods, weighting methods, regression methods, and approaches that combine and average across these methods methods for comparing two interventions as well as comparisons between three or more interventions algorithms for personalized medicine sensitivity analyses for unmeasured confounding

Download or read book Improving Population Health Using Electronic Health Records written by Neal D. Goldstein and published by CRC Press. This book was released on 2017-03-16 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Electronic health records (EHRs) have become commonplace in the medical profession. Health data are readily captured and permanently stored in a digital fashion, and consequently, are increasingly being utilized in health research. The quality of this research depends upon the investigator’s ability to obtain the correct data to answer the correct question. It is easy to churn out poor quality research from the EHR; it is much harder to produce meaningful results that influence the population’s health. Improving Population Health Using Electronic Health Records takes the reader through the process of conducting meaningful research from data in the EHR. It de-mystifies the entire research process, from how to ask the right kind of research questions, to obtaining data with particular emphasis on data management and manipulation, to performing a valid statistical analyses, and interpreting and presenting the results in a clear, concise fashion that has the potential to improve population health. This book can be used as a hands-on how-to guide of performing research from EHR data in either a piece-meal fashion, selecting only the topics of greatest interest, or a complete guide to the entire research process. Readers will benefit from the intuitive presentation of complex methods with a multitude of examples. It is invaluable reading for researchers and clinicians who are not otherwise familiar with the complexities of working with large data sets.

Download or read book Electronic Health Record written by Pradeep K. Sinha and published by John Wiley & Sons. This book was released on 2012-11-27 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover How Electronic Health Records Are Built to Drive the Next Generation of Healthcare Delivery The increased role of IT in the healthcare sector has led to the coining of a new phrase "health informatics," which deals with the use of IT for better healthcare services. Health informatics applications often involve maintaining the health records of individuals, in digital form, which is referred to as an Electronic Health Record (EHR). Building and implementing an EHR infrastructure requires an understanding of healthcare standards, coding systems, and frameworks. This book provides an overview of different health informatics resources and artifacts that underlie the design and development of interoperable healthcare systems and applications. Electronic Health Record: Standards, Coding Systems, Frameworks, and Infrastructures compiles, for the first time, study and analysis results that EHR professionals previously had to gather from multiple sources. It benefits readers by giving them an understanding of what roles a particular healthcare standard, code, or framework plays in EHR design and overall IT-enabled healthcare services along with the issues involved. This book on Electronic Health Record: Offers the most comprehensive coverage of available EHR Standards including ISO, European Union Standards, and national initiatives by Sweden, the Netherlands, Canada, Australia, and many others Provides assessment of existing standards Includes a glossary of frequently used terms in the area of EHR Contains numerous diagrams and illustrations to facilitate comprehension Discusses security and reliability of data

Download or read book Real World Health Care Data Analysis written by Douglas Faries and published by . This book was released on 2020-01-15 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover best practices for real world data research with SAS code and examples Real world health care data is common and growing in use with sources such as observational studies, patient registries, electronic medical record databases, insurance healthcare claims databases, as well as data from pragmatic trials. This data serves as the basis for the growing use of real world evidence in medical decision-making. However, the data itself is not evidence. Analytical methods must be used to turn real world data into valid and meaningful evidence. Real World Health Care Data Analysis: Causal Methods and Implementation Using SAS brings together best practices for causal comparative effectiveness analyses based on real world data in a single location and provides SAS code and examples to make the analyses relatively easy and efficient. The book focuses on analytic methods adjusted for time-independent confounding, which are useful when comparing the effect of different potential interventions on some outcome of interest when there is no randomization. These methods include: propensity score matching, stratification methods, weighting methods, regression methods, and approaches that combine and average across these methods methods for comparing two interventions as well as comparisons between three or more interventions algorithms for personalized medicine sensitivity analyses for unmeasured confounding

Download or read book Statistical Analysis of Medical Data Using SAS written by Geoff Der and published by CRC Press. This book was released on 2005-09-20 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical analysis is ubiquitous in modern medical research. Logistic regression, generalized linear models, random effects models, and Cox's regression all have become commonplace in the medical literature. But while statistical software such as SAS make routine application of these techniques possible, users who are not primarily statisticians must take care to correctly implement the various procedures and correctly interpret the output. Statistical Analysis of Medical Data Using SAS demonstrates how to use SAS to analyze medical data. Each chapter addresses a particular analysis method. The authors briefly describe each procedure, but focus on its SAS implementation and properly interpreting the output. The carefully designed presentation relegates the theoretical details to "Displays," so that the code and results can be explored without interruption. All of the code and data sets used in the book are available for download from either the SAS Web site or www.crcpress.com. Der and Everitt, authors of the best-selling Handbook of Statistical Analyses Using SAS, bring all of their considerable talent and experience to bear in this book. Step-by-step instructions, lucid explanations and clear examples combine to form an outstanding, self-contained guide--suitable for medical researchers and statisticians alike--to using SAS to analyze medical data.

Download or read book Health Informatics Practical Guide Seventh Edition written by William R. Hersh and published by Lulu.com. This book was released on 2018 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Health informatics is the discipline concerned with the management of healthcare data and information through the application of computers and other information technologies. The field focuses more on identifying and applying information in the healthcare field and less on the technology involved. Our goal is to stimulate and educate healthcare and IT professionals and students about the key topics in this rapidly changing field. This seventh edition reflects the current knowledge in the topics listed below and provides learning objectives, key points, case studies and extensive references. Available as a paperback and eBook. Visit the textbook companion website at http://informaticseducation.org for more information.--Page 4 de la couverture.

Download or read book A Handbook of Statistical Graphics Using SAS ODS written by Geoff Der and published by CRC Press. This book was released on 2014-08-15 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Easily Use SAS to Produce Your Graphics Diagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they have been fitted to the data. Harnessing the full graphics capabilities of SAS, A Handbook of Statistical Graphics Using SAS ODS covers essential graphical methods needed in every statistician’s toolkit. It explains how to implement the methods using SAS 9.4. The handbook shows how to use SAS to create many types of statistical graphics for exploring data and diagnosing fitted models. It uses SAS’s newer ODS graphics throughout as this system offers a number of advantages, including ease of use, high quality of results, consistent appearance, and convenient semiautomatic graphs from the statistical procedures. Each chapter deals graphically with several sets of example data from a wide variety of areas, such as epidemiology, medicine, and psychology. These examples illustrate the use of graphic displays to give an overview of data, to suggest possible hypotheses for testing new data, and to interpret fitted statistical models. The SAS programs and data sets are available online.

Download or read book Statistical Analysis of Medical Data Using SAS written by Brian S. Der and published by CRC Press. This book was released on 2017-12-13 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical analysis is ubiquitous in modern medical research. Logistic regression, generalized linear models, random effects models, and Cox's regression all have become commonplace in the medical literature. But while statistical software such as SAS make routine application of these techniques possible, users who are not primarily statisticians must take care to correctly implement the various procedures and correctly interpret the output. Statistical Analysis of Medical Data Using SAS demonstrates how to use SAS to analyze medical data. Each chapter addresses a particular analysis method. The authors briefly describe each procedure, but focus on its SAS implementation and properly interpreting the output. The carefully designed presentation relegates the theoretical details to "Displays," so that the code and results can be explored without interruption. All of the code and data sets used in the book are available for download from either the SAS Web site or www.crcpress.com. Der and Everitt, authors of the best-selling Handbook of Statistical Analyses Using SAS, bring all of their considerable talent and experience to bear in this book. Step-by-step instructions, lucid explanations and clear examples combine to form an outstanding, self-contained guide--suitable for medical researchers and statisticians alike--to using SAS to analyze medical data.

Download or read book Biostatistics and Computer based Analysis of Health Data Using SAS written by Christophe Lalanne and published by Elsevier. This book was released on 2017-06-22 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Implementing CDISC Using SAS written by Chris Holland and published by SAS Institute. This book was released on 2019-05-30 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: For decades researchers and programmers have used SAS to analyze, summarize, and report clinical trial data. Now Chris Holland and Jack Shostak have updated their popular Implementing CDISC Using SAS, the first comprehensive book on applying clinical research data and metadata to the Clinical Data Interchange Standards Consortium (CDISC) standards. Implementing CDISC Using SAS: An End-to-End Guide, Revised Second Edition, is an all-inclusive guide on how to implement and analyze the Study Data Tabulation Model (SDTM) and the Analysis Data Model (ADaM) data and prepare clinical trial data for regulatory submission. Updated to reflect the 2017 FDA mandate for adherence to CDISC standards, this new edition covers creating and using metadata, developing conversion specifications, implementing and validating SDTM and ADaM data, determining solutions for legacy data conversions, and preparing data for regulatory submission. The book covers products such as Base SAS, SAS Clinical Data Integration, and the SAS Clinical Standards Toolkit, as well as JMP Clinical. Topics included in this edition include an implementation of the Define-XML 2.0 standard, new SDTM domains, validation with Pinnacle 21 software, event narratives in JMP Clinical, STDM and ADAM metadata spreadsheets, and of course new versions of SAS and JMP software. The second edition was revised to add the latest C-Codes from the most recent release as well as update the make_define macro that accompanies this book in order to add the capability to handle C-Codes. The metadata spreadsheets were updated accordingly. Any manager or user of clinical trial data in this day and age is likely to benefit from knowing how to either put data into a CDISC standard or analyzing and finding data once it is in a CDISC format. If you are one such person--a data manager, clinical and/or statistical programmer, biostatistician, or even a clinician--then this book is for you.