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Applied Health Analytics And Informatics Using Sas
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Book Synopsis Applied Health Analytics and Informatics Using SAS by : Joseph M. Woodside
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.
Book Synopsis Real World Health Care Data Analysis by : Douglas Faries
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
Book Synopsis Intelligent Computing by : Kohei Arai
Download or read book Intelligent Computing written by Kohei Arai and published by Springer Nature. This book was released on 2021-07-05 with total page 1108 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive collection of chapters focusing on the core areas of computing and their further applications in the real world. Each chapter is a paper presented at the Computing Conference 2021 held on 15-16 July 2021. Computing 2021 attracted a total of 638 submissions which underwent a double-blind peer review process. Of those 638 submissions, 235 submissions have been selected to be included in this book. The goal of this conference is to give a platform to researchers with fundamental contributions and to be a premier venue for academic and industry practitioners to share new ideas and development experiences. We hope that readers find this volume interesting and valuable as it provides the state-of-the-art intelligent methods and techniques for solving real-world problems. We also expect that the conference and its publications is a trigger for further related research and technology improvements in this important subject.
Book Synopsis Applying Data Science by : Gerhard Svolba
Download or read book Applying Data Science written by Gerhard Svolba and published by SAS Institute. This book was released on 2017-03-29 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: See how data science can answer the questions your business faces! Applying Data Science: Business Case Studies Using SAS, by Gerhard Svolba, shows you the benefits of analytics, how to gain more insight into your data, and how to make better decisions. In eight entertaining and real-world case studies, Svolba combines data science and advanced analytics with business questions, illustrating them with data and SAS code. The case studies range from a variety of fields, including performing headcount survival analysis for employee retention, forecasting the demand for new projects, using Monte Carlo simulation to understand outcome distribution, among other topics. The data science methods covered include Kaplan-Meier estimates, Cox Proportional Hazard Regression, ARIMA models, Poisson regression, imputation of missing values, variable clustering, and much more! Written for business analysts, statisticians, data miners, data scientists, and SAS programmers, Applying Data Science bridges the gap between high-level, business-focused books that skimp on the details and technical books that only show SAS code with no business context.
Book Synopsis Real World Health Care Data Analysis by : Douglas Faries
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
Book Synopsis Applied Medical Statistics Using SAS by : Geoff Der
Download or read book Applied Medical Statistics Using SAS written by Geoff Der and published by CRC Press. This book was released on 2012-10-01 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written with medical statisticians and medical researchers in mind, this intermediate-level reference explores the use of SAS for analyzing medical data. Applied Medical Statistics Using SAS covers the whole range of modern statistical methods used in the analysis of medical data, including regression, analysis of variance and covariance, longitudinal and survival data analysis, missing data, generalized additive models (GAMs), and Bayesian methods. The book focuses on performing these analyses using SAS, the software package of choice for those analysing medical data. Features Covers the planning stage of medical studies in detail; several chapters contain details of sample size estimation Illustrates methods of randomisation that might be employed for clinical trials Covers topics that have become of great importance in the 21st century, including Bayesian methods and multiple imputation Its breadth and depth, coupled with the inclusion of all the SAS code, make this book ideal for practitioners as well as for a graduate class in biostatistics or public health. Complete data sets, all the SAS code, and complete outputs can be found on an associated website: http://support.sas.com/amsus
Book Synopsis Administrative Healthcare Data by : Craig Dickstein
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.
Book Synopsis Handbook of Data Analysis of Electronic Health Records (EHR) Using SAS Software by : Behrouz Ehsani-Moghaddam
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"--
Book Synopsis Statistical Analytics for Health Data Science with SAS and R by : Jeffrey Wilson
Download or read book Statistical Analytics for Health Data Science with SAS and R written by Jeffrey Wilson and published by CRC Press. This book was released on 2023-03-27 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to compile typical fundamental-to-advanced statistical methods to be used for health data sciences. Although the book promotes applications to health and health-related data, the models in the book can be used to analyze any kind of data. The data are analyzed with the commonly used statistical software of R/SAS (with online supplementary on SPSS/Stata). The data and computing programs will be available to facilitate readers’ learning experience. There has been considerable attention to making statistical methods and analytics available to health data science researchers and students. This book brings it all together to provide a concise point-of-reference for the most commonly used statistical methods from the fundamental level to the advanced level. We envisage this book will contribute to the rapid development in health data science. We provide straightforward explanations of the collected statistical theory and models, compilations of a variety of publicly available data, and illustrations of data analytics using commonly used statistical software of SAS/R. We will have the data and computer programs available for readers to replicate and implement the new methods. The primary readers would be applied data scientists and practitioners in any field of data science, applied statistical analysts and scientists in public health, academic researchers, and graduate students in statistics and biostatistics. The secondary readers would be R&D professionals/practitioners in industry and governmental agencies. This book can be used for both teaching and applied research.
Book Synopsis Analysis of Observational Health Care Data Using SAS by : Douglas E. Faries
Download or read book Analysis of Observational Health Care Data Using SAS written by Douglas E. Faries and published by SAS Press. This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data. This book is part of the SAS Press program.
Download or read book Healthcare Analytics written by Hui Yang and published by John Wiley & Sons. This book was released on 2016-10-10 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: Features of statistical and operational research methods and tools being used to improve the healthcare industry With a focus on cutting-edge approaches to the quickly growing field of healthcare, Healthcare Analytics: From Data to Knowledge to Healthcare Improvement provides an integrated and comprehensive treatment on recent research advancements in data-driven healthcare analytics in an effort to provide more personalized and smarter healthcare services. Emphasizing data and healthcare analytics from an operational management and statistical perspective, the book details how analytical methods and tools can be utilized to enhance healthcare quality and operational efficiency. Organized into two main sections, Part I features biomedical and health informatics and specifically addresses the analytics of genomic and proteomic data; physiological signals from patient-monitoring systems; data uncertainty in clinical laboratory tests; predictive modeling; disease modeling for sepsis; and the design of cyber infrastructures for early prediction of epidemic events. Part II focuses on healthcare delivery systems, including system advances for transforming clinic workflow and patient care; macro analysis of patient flow distribution; intensive care units; primary care; demand and resource allocation; mathematical models for predicting patient readmission and postoperative outcome; physician–patient interactions; insurance claims; and the role of social media in healthcare. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement also features: • Contributions from well-known international experts who shed light on new approaches in this growing area • Discussions on contemporary methods and techniques to address the handling of rich and large-scale healthcare data as well as the overall optimization of healthcare system operations • Numerous real-world examples and case studies that emphasize the vast potential of statistical and operational research tools and techniques to address the big data environment within the healthcare industry • Plentiful applications that showcase analytical methods and tools tailored for successful healthcare systems modeling and improvement The book is an ideal reference for academics and practitioners in operations research, management science, applied mathematics, statistics, business, industrial and systems engineering, healthcare systems, and economics. Healthcare Analytics: From Data to Knowledge to Healthcare Improvement is also appropriate for graduate-level courses typically offered within operations research, industrial engineering, business, and public health departments.
Book Synopsis Big Data and Health Analytics by : Katherine Marconi
Download or read book Big Data and Health Analytics written by Katherine Marconi and published by CRC Press. This book was released on 2014-12-20 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data availability is surpassing existing paradigms for governing, managing, analyzing, and interpreting health data. Big Data and Health Analytics 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 healt
Book Synopsis Data Management and Analysis Using JMP by : Jane E Oppenlander
Download or read book Data Management and Analysis Using JMP written by Jane E Oppenlander and published by SAS Institute. This book was released on 2017-10-17 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: A holistic, step-by-step approach to analyzing health care data! Written for both beginner and intermediate JMP users working in or studying health care, Data Management and Analysis Using JMP: Health Care Case Studies bridges the gap between taking traditional statistics courses and successfully applying statistical analysis in the workplace. Authors Jane Oppenlander and Patricia Schaffer begin by illustrating techniques to prepare data for analysis, followed by presenting effective methods to summarize, visualize, and analyze data. The statistical analysis methods covered in the book are the foundational techniques commonly applied to meet regulatory, operational, budgeting, and research needs in the health care field. This example-driven book shows practitioners how to solve real-world problems by using an approach that includes problem definition, data management, selecting the appropriate analysis methods, step-by-step JMP instructions, and interpreting statistical results in context. Practical strategies for selecting appropriate statistical methods, remediating data anomalies, and interpreting statistical results in the domain context are emphasized. The cases presented in Data Management and Analysis Using JMP use multiple statistical methods. A progression of methods--from univariate to multivariate--is employed, illustrating a logical approach to problem-solving. Much of the data used in these cases is open source and drawn from a variety of health care settings. The book offers a welcome guide to working professionals as well as students studying statistics in health care-related fields.
Book Synopsis Biostatistics and Computer-based Analysis of Health Data Using SAS by : Christophe Lalanne
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 174 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
Book Synopsis Analyzing Health Data in R for SAS Users by : Monika Maya Wahi
Download or read book Analyzing Health Data in R for SAS Users written by Monika Maya Wahi and published by CRC Press. This book was released on 2017-11-22 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyzing Health Data in R for SAS Users is aimed at helping health data analysts who use SAS accomplish some of the same tasks in R. It is targeted to public health students and professionals who have a background in biostatistics and SAS software, but are new to R. For professors, it is useful as a textbook for a descriptive or regression modeling class, as it uses a publicly-available dataset for examples, and provides exercises at the end of each chapter. For students and public health professionals, not only is it a gentle introduction to R, but it can serve as a guide to developing the results for a research report using R software. Features: Gives examples in both SAS and R Demonstrates descriptive statistics as well as linear and logistic regression Provides exercise questions and answers at the end of each chapter Uses examples from the publicly available dataset, Behavioral Risk Factor Surveillance System (BRFSS) 2014 data Guides the reader on producing a health analysis that could be published as a research report Gives an example of hypothesis-driven data analysis Provides examples of plots with a color insert
Book Synopsis Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner by : Olivia Parr-Rud
Download or read book Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner written by Olivia Parr-Rud and published by SAS Institute. This book was released on 2014-10 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. This beginnner's guide with clear, illustrated, step-by-step instructions will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. --
Book Synopsis The Analytics Lifecycle Toolkit by : Gregory S. Nelson
Download or read book The Analytics Lifecycle Toolkit written by Gregory S. Nelson and published by John Wiley & Sons. This book was released on 2018-03-07 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: An evidence-based organizational framework for exceptional analytics team results The Analytics Lifecycle Toolkit provides managers with a practical manual for integrating data management and analytic technologies into their organization. Author Gregory Nelson has encountered hundreds of unique perspectives on analytics optimization from across industries; over the years, successful strategies have proven to share certain practices, skillsets, expertise, and structural traits. In this book, he details the concepts, people and processes that contribute to exemplary results, and shares an organizational framework for analytics team functions and roles. By merging analytic culture with data and technology strategies, this framework creates understanding for analytics leaders and a toolbox for practitioners. Focused on team effectiveness and the design thinking surrounding product creation, the framework is illustrated by real-world case studies to show how effective analytics team leadership works on the ground. Tools and templates include best practices for process improvement, workforce enablement, and leadership support, while guidance includes both conceptual discussion of the analytics life cycle and detailed process descriptions. Readers will be equipped to: Master fundamental concepts and practices of the analytics life cycle Understand the knowledge domains and best practices for each stage Delve into the details of analytical team processes and process optimization Utilize a robust toolkit designed to support analytic team effectiveness The analytics life cycle includes a diverse set of considerations involving the people, processes, culture, data, and technology, and managers needing stellar analytics performance must understand their unique role in the process of winnowing the big picture down to meaningful action. The Analytics Lifecycle Toolkit provides expert perspective and much-needed insight to managers, while providing practitioners with a new set of tools for optimizing results.
