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Statistical Topics in Health Economics and Outcomes Research

Statistical Topics in Health Economics and Outcomes Research PDF Author: Demissie Alemayehu, PhD
Publisher: CRC Press
ISBN: 1498781888
Category : Mathematics
Languages : en
Pages : 210

Book Description
With ever-rising healthcare costs, evidence generation through Health Economics and Outcomes Research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. Accordingly, it is now customary for health technology assessment and reimbursement agencies to request for HEOR evidence, in addition to data from clinical trials, to inform decisions about patient access to new treatment options. While there is a great deal of literature on HEOR, there is a need for a volume that presents a coherent and unified review of the major issues that arise in application, especially from a statistical perspective. Statistical Topics in Health Economics and Outcomes Research fulfils that need by presenting an overview of the key analytical issues and best practice. Special attention is paid to key assumptions and other salient features of statistical methods customarily used in the area, and appropriate and relatively comprehensive references are made to emerging trends. The content of the book is purposefully designed to be accessible to readers with basic quantitative backgrounds, while providing an in-depth coverage of relatively complex statistical issues. The book will make a very useful reference for researchers in the pharmaceutical industry, academia, and research institutions involved with HEOR studies. The targeted readers may include statisticians, data scientists, epidemiologists, outcomes researchers, health economists, and healthcare policy and decision-makers.

Statistical Topics in Health Economics and Outcomes Research

Statistical Topics in Health Economics and Outcomes Research PDF Author: Demissie Alemayehu, PhD
Publisher: CRC Press
ISBN: 1498781888
Category : Mathematics
Languages : en
Pages : 210

Book Description
With ever-rising healthcare costs, evidence generation through Health Economics and Outcomes Research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. Accordingly, it is now customary for health technology assessment and reimbursement agencies to request for HEOR evidence, in addition to data from clinical trials, to inform decisions about patient access to new treatment options. While there is a great deal of literature on HEOR, there is a need for a volume that presents a coherent and unified review of the major issues that arise in application, especially from a statistical perspective. Statistical Topics in Health Economics and Outcomes Research fulfils that need by presenting an overview of the key analytical issues and best practice. Special attention is paid to key assumptions and other salient features of statistical methods customarily used in the area, and appropriate and relatively comprehensive references are made to emerging trends. The content of the book is purposefully designed to be accessible to readers with basic quantitative backgrounds, while providing an in-depth coverage of relatively complex statistical issues. The book will make a very useful reference for researchers in the pharmaceutical industry, academia, and research institutions involved with HEOR studies. The targeted readers may include statisticians, data scientists, epidemiologists, outcomes researchers, health economists, and healthcare policy and decision-makers.

Statistical Topics in Health Economics and Outcomes Research

Statistical Topics in Health Economics and Outcomes Research PDF Author: Taylor & Francis Group
Publisher: CRC Press
ISBN: 9781032096049
Category :
Languages : en
Pages : 190

Book Description
With ever-rising healthcare costs, evidence generation through Health Economics and Outcomes Research (HEOR) plays an increasingly important role in decision-making about the allocation of resources. Accordingly, it is now customary for health technology assessment and reimbursement agencies to request for HEOR evidence, in addition to data from clinical trials, to inform decisions about patient access to new treatment options. While there is a great deal of literature on HEOR, there is a need for a volume that presents a coherent and unified review of the major issues that arise in application, especially from a statistical perspective. Statistical Topics in Health Economics and Outcomes Research fulfils that need by presenting an overview of the key analytical issues and best practice. Special attention is paid to key assumptions and other salient features of statistical methods customarily used in the area, and appropriate and relatively comprehensive references are made to emerging trends. The content of the book is purposefully designed to be accessible to readers with basic quantitative backgrounds, while providing an in-depth coverage of relatively complex statistical issues. The book will make a very useful reference for researchers in the pharmaceutical industry, academia, and research institutions involved with HEOR studies. The targeted readers may include statisticians, data scientists, epidemiologists, outcomes researchers, health economists, and healthcare policy and decision-makers.

A Primer on Bayesian Statistics in Health Economics and Outcomes Research

A Primer on Bayesian Statistics in Health Economics and Outcomes Research PDF Author: Bryan Luce
Publisher:
ISBN: 9780974364100
Category :
Languages : en
Pages :

Book Description


Statistical Evaluation of Diagnostic Performance

Statistical Evaluation of Diagnostic Performance PDF Author: Kelly H. Zou
Publisher: CRC Press
ISBN: 1439812233
Category : Mathematics
Languages : en
Pages : 245

Book Description
Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers, as well as for evaluating predictive models or algorithms. This book presents innovative approaches in ROC analysis, which are relevant to a wide variety of applications, including medical imaging, cancer research, epidemiology, and bioinformatics. Statistical Evaluation of Diagnostic Performance: Topics in ROC Analysis covers areas including monotone-transformation techniques in parametric ROC analysis, ROC methods for combined and pooled biomarkers, Bayesian hierarchical transformation models, sequential designs and inferences in the ROC setting, predictive modeling, multireader ROC analysis, and free-response ROC (FROC) methodology. The book is suitable for graduate-level students and researchers in statistics, biostatistics, epidemiology, public health, biomedical engineering, radiology, medical imaging, biomedical informatics, and other closely related fields. Additionally, clinical researchers and practicing statisticians in academia, industry, and government could benefit from the presentation of such important and yet frequently overlooked topics.

Using Discrete Choice Experiments to Value Health and Health Care

Using Discrete Choice Experiments to Value Health and Health Care PDF Author: Mandy Ryan
Publisher: Springer Science & Business Media
ISBN: 1402057539
Category : Business & Economics
Languages : en
Pages : 265

Book Description
This work takes a fresh and contemporary look at the growing interest in the development and application of discrete choice experiments (DCEs) within the field of health economics. The book comprises chapters by highly regarded academics with experience of applying DCEs in the area of health. Thus the book is relevant to post-graduate students and applied researchers with an interest in the use of DCEs for valuing health and health care and has international appeal.

Applied Health Economics

Applied Health Economics PDF Author: Andrew M. Jones
Publisher: Routledge
ISBN: 1134152361
Category : Business & Economics
Languages : en
Pages : 355

Book Description
Large-scale survey datasets, in particular complex survey designs such as panel data, provide a rich source of information for health economists. They offer the scope to control for individual heterogeneity and to model the dynamics of individual behaviour. However the measures of outcome used in health economics are often qualitative or categorical. These create special problems for estimating econometric models. The dramatic growth in computing power over recent years has been accompanied by the development of methods that help to solve these problems. This book provides a practical guide to the skills required to put these techniques into practice. This book illustrates practical applications of these methods using data on health from, among others, the British Health and Lifestyle Survey (HALS), the British Household Panel Survey (BHPS), the European Community Household Panel (ECHP) and the WHO Multi-Country Survey (WHO-MCS). Assuming a familiarity with the basic syntax and structure of Stata, this book presents and explains the statistical output using empirical case studies rather than general theory. Never before has a health economics text brought theory and practice together and this book will be of great benefit to applied economists, as well as advanced undergraduate and post graduate students in health economics and applied econometrics.

Big Data for Twenty-First-Century Economic Statistics

Big Data for Twenty-First-Century Economic Statistics PDF Author: Katharine G. Abraham
Publisher: University of Chicago Press
ISBN: 022680125X
Category : Business & Economics
Languages : en
Pages : 502

Book Description
Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.

Statistics in Public Health

Statistics in Public Health PDF Author: Donna F. Stroup Ph.D, M.Sc.
Publisher: Oxford University Press
ISBN: 9780199771332
Category : Medical
Languages : en
Pages : 252

Book Description
Public health strives to improve the health of human populations, and prevent disease, disability, and death. Statistics--the science of finding underlying patterns by analyzing variability and errors in collected data--is essential to the understanding of disease patterns in human populations. Other quantitative methods, such as economics, decision theory, and mathematics, now constitute integral parts of the scientific basis for priority-setting and evaluation in public health. This book provides a broad conceptual treatment of the statistical issues underlying core public health functions: outbreak investigations, policy development, economic and program evaluation, managed care, and program operations. The theoretical analysis is illustrated with examples from public health practice. For readers interested in a more detailed treatment, there are extensive references to specialized publications. The authors present a series of quantitative approaches that significantly help public health professionals solve the problems they confront in their day-to-day work. Unlike traditional how-to books in statistics, this volume starts with an overview of the range of problems encountered in public health practice, and then presents methods for facilitating decision making. Statistics in Public Health: Quantitative Approaches to Public Health Problems will serve as a comprehensive desk reference for public health practitioners and as a teaching text for students of public health.

Comparative Effectiveness Research in Health Services

Comparative Effectiveness Research in Health Services PDF Author:
Publisher:
ISBN: 9781489975867
Category :
Languages : en
Pages :

Book Description


Decision Modelling for Health Economic Evaluation

Decision Modelling for Health Economic Evaluation PDF Author: Andrew Briggs
Publisher: OUP Oxford
ISBN: 0191004952
Category : Medical
Languages : en
Pages : 256

Book Description
In financially constrained health systems across the world, increasing emphasis is being placed on the ability to demonstrate that health care interventions are not only effective, but also cost-effective. This book deals with decision modelling techniques that can be used to estimate the value for money of various interventions including medical devices, surgical procedures, diagnostic technologies, and pharmaceuticals. Particular emphasis is placed on the importance of the appropriate representation of uncertainty in the evaluative process and the implication this uncertainty has for decision making and the need for future research. This highly practical guide takes the reader through the key principles and approaches of modelling techniques. It begins with the basics of constructing different forms of the model, the population of the model with input parameter estimates, analysis of the results, and progression to the holistic view of models as a valuable tool for informing future research exercises. Case studies and exercises are supported with online templates and solutions. This book will help analysts understand the contribution of decision-analytic modelling to the evaluation of health care programmes. ABOUT THE SERIES: Economic evaluation of health interventions is a growing specialist field, and this series of practical handbooks will tackle, in-depth, topics superficially addressed in more general health economics books. Each volume will include illustrative material, case histories and worked examples to encourage the reader to apply the methods discussed, with supporting material provided online. This series is aimed at health economists in academia, the pharmaceutical industry and the health sector, those on advanced health economics courses, and health researchers in associated fields.