Statistical Analysis Of Cost Effectiveness Data
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Statistical Analysis Of Cost Effectiveness Data
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Author : Andrew R. Willan
language : en
Publisher: John Wiley & Sons
Release Date : 2006-08-14
Statistical Analysis Of Cost Effectiveness Data written by Andrew R. Willan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-14 with Mathematics categories.
The statistical analysis of cost-effectiveness data is becoming increasingly important within health and medical research. Statistical Analysis of Cost-Effectiveness Data provides a practical book that synthesises the huge amount of research that has taken place in the area over the last two decades. Comprising an up-to-date overview of the statistical analysis of cost-effectiveness data, the book is supported by numerous worked examples from the author’s own experience. It has been written in a style suitable for medical statisticians and health care professionals alike. Key features include: an overview of statistical methods used in the analysis of cost-effectiveness data. coverage of Bayesian methodology. illustrated throughout by worked examples using real data. suitability for health care professionals with limited statistical knowledge. discussion of software used for data analysis. An essential reference for biostatisticians and health economists engaged in cost-effectiveness analysis of health-care interventions, both in academia and industry. Also of interest to graduate students of biostatistics, public health and economics.
Bayesian Cost Effectiveness Analysis Of Medical Treatments
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Author : Elias Moreno
language : en
Publisher: CRC Press
Release Date : 2019-01-30
Bayesian Cost Effectiveness Analysis Of Medical Treatments written by Elias Moreno and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-30 with Mathematics categories.
Cost-effectiveness analysis is becoming an increasingly important tool for decision making in the health systems. Cost-Effectiveness of Medical Treatments formulates the cost-effectiveness analysis as a statistical decision problem, identifies the sources of uncertainty of the problem, and gives an overview of the frequentist and Bayesian statistical approaches for decision making. Basic notions on decision theory such as space of decisions, space of nature, utility function of a decision and optimal decisions, are explained in detail using easy to read mathematics. Features Focuses on cost-effectiveness analysis as a statistical decision problem and applies the well-established optimal statistical decision methodology. Discusses utility functions for cost-effectiveness analysis. Enlarges the class of models typically used in cost-effectiveness analysis with the incorporation of linear models to account for covariates of the patients. This permits the formulation of the group (or subgroup) theory. Provides Bayesian procedures to account for model uncertainty in variable selection for linear models and in clustering for models for heterogeneous data. Model uncertainty in cost-effectiveness analysis has not been considered in the literature. Illustrates examples with real data. In order to facilitate the practical implementation of real datasets, provides the codes in Mathematica for the proposed methodology. The motivation for the book is to make the achievements in cost-effectiveness analysis accessible to health providers, who need to make optimal decisions, to the practitioners and to the students of health sciences. Elías Moreno is Professor of Statistics and Operational Research at the University of Granada, Spain, Corresponding Member of the Royal Academy of Sciences of Spain, and elect member of ISI. Francisco José Vázquez-Polo is Professor of Mathematics and Bayesian Methods at the University of Las Palmas de Gran Canaria, and Head of the Department of Quantitative Methods. Miguel Ángel Negrín is Senior Lecturer in the Department of Quantitative Methods at the ULPGC. His main research topics are Bayesian methods applied to Health Economics, economic evaluation and cost-effectiveness analysis, meta-analysis and equity in the provision of healthcare services.
Statistical Methods For Cost Effectiveness Analysis Using Observational Data
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Author : Elizabeth A. Handorf
language : en
Publisher:
Release Date : 2012
Statistical Methods For Cost Effectiveness Analysis Using Observational Data written by Elizabeth A. Handorf and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Cost Effectiveness Analysis In Health
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Author : Peter Muennig
language : en
Publisher: John Wiley & Sons
Release Date : 2016-02-29
Cost Effectiveness Analysis In Health written by Peter Muennig and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-29 with Medical categories.
The field's bestselling reference, updated with the latest tools, data, techniques, and the latest recommendations from the Second Panel on Cost-Effectiveness in Health and Medicine Cost-Effectiveness Analysis in Health is a practical introduction to the tools, methods, and procedures used worldwide to perform cost-effective research. Covering every aspect of a complete cost-effectiveness analysis, this book shows you how to find which data you need, where to find it, how to analyze it, and how to prepare a high-quality report for publication. Designed for the classroom or the individual learner, the material is presented in simple and accessible language for those who lack a biostatistics or epidemiology background, and each chapter includes real-world examples and "tips and tricks" that highlight key information. Exercises throughout allow you to test your understanding with practical application, and the companion website features downloadable data sets for students, as well as lecture slides and a test bank for instructors. This new third edition contains new discussion on meta-analysis and advanced modeling techniques, a long worked example using visual modeling software TreeAge Pro, and updated recommendations from the U.S. Public Health Service's Panel on Cost-Effectiveness in Health and Medicine. This is the second printing of the 3rd Edition, which has been corrected and revised for 2018 to reflect the latest standards and methods. Cost-effectiveness analysis is used to evaluate medical interventions worldwide, in both developed and developing countries. This book provides process-specific instruction in a concise, structured format to give you a robust working knowledge of common methods and techniques. Develop a thoroughly fleshed-out research project Work accurately with costs, probabilities, and models Calculate life expectancy and quality-adjusted life years Prepare your study and your data for publication Comprehensive analysis skills are essential for students seeking careers in public health, medicine, biomedical research, health economics, health policy, and more. Cost-Effectiveness Analysis in Health walks you through the process from a real-world perspective to help you build a skillset that's immediately applicable in the field.
Bayesian Cost Effectiveness Analysis With The R Package Bcea
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Author : Gianluca Baio
language : en
Publisher: Springer
Release Date : 2017-05-25
Bayesian Cost Effectiveness Analysis With The R Package Bcea written by Gianluca Baio and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-25 with Medical categories.
The book provides a description of the process of health economic evaluation and modelling for cost-effectiveness analysis, particularly from the perspective of a Bayesian statistical approach. Some relevant theory and introductory concepts are presented using practical examples and two running case studies. The book also describes in detail how to perform health economic evaluations using the R package BCEA (Bayesian Cost-Effectiveness Analysis). BCEA can be used to post-process the results of a Bayesian cost-effectiveness model and perform advanced analyses producing standardised and highly customisable outputs. It presents all the features of the package, including its many functions and their practical application, as well as its user-friendly web interface. The book is a valuable resource for statisticians and practitioners working in the field of health economics wanting to simplify and standardise their workflow, for example in the preparation of dossiers in support of marketing authorisation, or academic and scientific publications.
Statistical Tools For Program Evaluation
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Author : Jean-Michel Josselin
language : en
Publisher: Springer
Release Date : 2017-05-23
Statistical Tools For Program Evaluation written by Jean-Michel Josselin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-23 with Business & Economics categories.
This book provides a self-contained presentation of the statistical tools required for evaluating public programs, as advocated by many governments, the World Bank, the European Union, and the Organization for Economic Cooperation and Development. After introducing the methodological framework of program evaluation, the first chapters are devoted to the collection, elementary description and multivariate analysis of data as well as the estimation of welfare changes. The book then successively presents the tools of ex-ante methods (financial analysis, budget planning, cost-benefit, cost-effectiveness and multi-criteria evaluation) and ex-post methods (benchmarking, experimental and quasi-experimental evaluation). The step-by-step approach and the systematic use of numerical illustrations equip readers to handle the statistics of program evaluation. It not only offers practitioners from public administrations, consultancy firms and nongovernmental organizations the basic tools and advanced techniques used in program assessment, it is also suitable for executive management training, upper undergraduate and graduate courses, as well as for self-study.
Statistical Methods And Cost Effectiveness In Clinical Trials
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Author : Godfred Abledu
language : en
Publisher:
Release Date : 2014
Statistical Methods And Cost Effectiveness In Clinical Trials written by Godfred Abledu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
This paper looks at how cost in clinical trials can be kept at the barest minimum. The paper attempts to find a statistical method to obtain the maximum benefit in the conduct of clinical trials at low cost. The standard approach to the statistical estimation of cost-effectiveness based on data collected alongside clinical trials has been outlined. The predominant approach in the paper is to estimate a single Incremental Cost-Effectiveness Ratio (ICER) for the trial as a whole, and has focused on the appropriate way to characterize statistical uncertainty in the estimated cost-effectiveness. The standard approach proposed by Willan and Briggs (2006) and Hock and Blume (2008), will then be extended to consider issues associated with covariate adjustment and subgroup analysis in economic evaluation studies, within a net-benefit regression framework. A more general framework of statistical modeling is proposed, based on modeling the separate components of cost and effect.
Use Of Statistical Analysis Data Mining Decision Analysis And Cost Effectiveness Analysis To Analyze Medical Data
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Author : Beatrice Ugiliweneza
language : en
Publisher:
Release Date : 2011
Use Of Statistical Analysis Data Mining Decision Analysis And Cost Effectiveness Analysis To Analyze Medical Data written by Beatrice Ugiliweneza and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Bioinformatics categories.
Statistical models have been the first choice for comparative effectiveness in clinical research. Though effective, these models are limited when the data to be analyzed do not fit the assumed distributions; which is mostly the case when the study is not a clinical trial. In this project, data mining, decision analysis and cost effectiveness analysis methods were used to supplement statistical models in comparing lumpectomy to mastectomy for surgical treatment of breast cancer. Mastectomy has been the gold standard for breast cancer treatment for since the 1800s. In the 20th century, an equivalence of mastectomy and lumpectomy was established in terms of long-term survival and disease free survival. However, short term comparative effectiveness in post-operative outcomes has not been fully explored. Studies using administrative data are lacking and no study has used new technologies of self-expression, particularly the internet discussion board. In this study, data used were from the Nationwide Inpatient Sample (NIS) 2005, the Thomson Reuter's MarketScan 2000 - 2001, the medical literature on clinical trials and online individuals' posts in discussion boards on breastcancer.org. The NIS was used to compare lumpectomy to mastectomy in terms of hospital length of stay, total charges and in-hospital death at the time of surgery. MarketScan data was used to evaluate the comparative follow-up outcomes in terms of risk of repeat hospitalization, risk of repeat operation, number of outpatient services, number of prescribed medications, length of stay, and total charges per post-operative hospital admission on a period of eight months average. The MarketScan was also used to construct a simple post-operative hospital admission predictive model and to perform short-term cost-effectiveness analysis. The medical literature was used to analyze long term -10 years- mortality and recurrence for both treatments. The web postings were used to evaluate the comparative cost to improve quality of life in terms of patient satisfaction. In NIS and MarketScan data, International Classification of Disease, 9th revision, Clinical Modification (lCD-9-CM) diagnosis codes were used to extract cases of breast cancer; and ICD-9-CM procedure codes and Current Procedural Terminology, 4th edition procedure codes were used to form groups of treatment. Data were pre-processed and prepared for analysis using data mining techniques such as clustering, sampling and text mining. To clean the data for statistical models, some continuous variables were normalized using methods such as logarithmic transformation. Statistical models such as linear regression, generalized linear models, logistic and proportional hazard (Cox) regressions were used to compare post-operative outcomes of lumpectomy versus mastectomy. Neural networks, decision tree and logistic regression predictive modeling techniques were compared to create a simple predictive model predicting 90-day post-operative hospital re-admission. Cost and effectiveness were compared with the Incremental Cost Effectiveness Ratio (ICER). A simple method to process and analyze online po stings was created and used for patients' input in the comparison of lumpectomy to mastectomy. All statistical analyses were performed in SAS 9.2. Data Mining was performed in SAS Enterprise Miner (EM) 6.1 and SAS Text Miner. Decision analysis and Cost Effectiveness Analysis were performed in TreeAge Pro 2011. A simple comparison of the two procedures using the NIS 2005, a discharge-level data, showed that in general, a lumpectomy surgery is associated with a significantly longer stay and more charges on average. From the MarketScan data, a person-level data where a patient can be followed longitudinally, it was found that for the initial hospitalization, patients who underwent mastectomy had a non-significant longer hospital stay and significantly lower charges. The post-operative number of outpatient services, prescribed medications as well as length of stay and charges for post-operative hospital admissions were not statistically significant. Using the MarketScan data, it was also found that the best model to predict 90-day post-operative hospital admission was logistic regression. A logistic regression revealed that the risk of a hospital re-admission within 90 days after surgery was 65% for a patient who underwent lumpectomy and 48% for a patient who underwent mastectomy. A cost effectiveness analysis using Markov models for up to 100 days after surgery showed that having lumpectomy saved hospital related costs every day with a minimum saving of $33 on day 10. In terms of long-term outcomes, the use of decision analysis methods on the literature review data revealed that, 10-years after surgery, 739 recurrences and 84 deaths were prevented among 10,000 women who had mastectomy instead of lumpectomy. Factoring patients' preferences in the comparison of the two procedures, it was found that patients who undergo lumpectomy are non-significantly more satisfied than their peers who undergo mastectomy. In terms of cost, it was found that lumpectomy saves $517 for each satisfied individual in comparison to mastectomy. In conclusion, the current project showed how to use data mining, decision analysis and cost effectiveness methods to supplement statistical analysis when using real world nonclinical trial data for a more complete analysis. The application of this combination of methods on the comparative effectiveness of lumpectomy and mastectomy showed that in terms of cost and patients' quality of life measured as satisfaction, lumpectomy was found to be the better choice.
Essentials Of Economic Evaluation In Healthcare
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Author : Rachel Elliott
language : en
Publisher: Pharmaceutical Press
Release Date : 2005
Essentials Of Economic Evaluation In Healthcare written by Rachel Elliott and has been published by Pharmaceutical Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Medical categories.
"This book is an introduction to economic evaluation for those with little or no knowledge of economics or health economics. Essentials of Economic Evaluation in Healthcare gives an overview of economic issues specific to healthcare, and describes the main types of economic evaluation: cost effectiveness, cost utility and cost benefit analysis. The use of decision analysis to design and carry out economic evaluations is discussed. Preferred statistical methods for handling costs, current approaches to dealing with uncertainty and quantifying patient preferences using discrete choice experiments are explained. Each chapter contains worked examples and questions. With increasing pressure on national healthcare budgets, all healthcare professionals should have a basic understanding of the finite nature of healthcare resources, and the need to make choices between treatments based on a cost-benefit comparison. This book will be invaluable to pharmacists and pharmacy students as well as to other healthcare professionals, researchers and managers." -- publisher website.
Statistical Inference For Medical Costs And Incremental Cost Effectiveness Ratios With Censored Data
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Author : Shuai Chen
language : en
Publisher:
Release Date : 2015
Statistical Inference For Medical Costs And Incremental Cost Effectiveness Ratios With Censored Data written by Shuai Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Cost-effectiveness analysis is widely conducted in the economic evaluation of new treatments, due to skyrocketing health care costs and limited resource available. Censored costs data poses a unique problem for cost estimation due to "induced informative censoring" problem. Thus, many standard approaches for survival analysis are not valid for the analysis of cost data. We first derive the confidence interval for the incremental cost-effectiveness ratio for a special case, when terminating events are different for survival time and costs. Then we study how to intuitively explain some existing estimators for costs, based on the generalized redistribute-to-the-right algorithm. Motivated by that idea, we also propose two improved survival estimators of costs, based on generalized redistribute-to-the-right algorithm and kernel method. We first consider one special situation in conducting cost-effectiveness analysis, when the terminating events for survival time and costs are different. Traditional methods for statistical inference cannot deal with such data. We propose a new method for deriving the confidence interval for the incremental cost-effectiveness ratio under this situation, based on the counting process theory and the general theory for missing data process. The simulation studies and real data example show that our method performs very well for some practical settings. In addition, we provide intuitive explanation to a mean cost estimator and a survival estimator for costs, based on generalized redistribute-to-the-right algorithm. Since those estimators are derived based on the inverse probability weighting principle and semiparametric efficiency theory, it is not always easy to understand how these methods work. Therefore, our work engenders a better understanding of those theoretically derived cost estimators. Motivated by the idea of generalized redistribute-to-the-right algorithm, we propose an estimator for the survival function of costs. The proposed estimator is naturally monotone, more efficient than some existing survival estimators, and has a quite small bias in many realistic settings. We further propose a kernel-based survival estimator for costs. The latter estimator, which is asymptotically unbiased, overcomes the deficiency of the former estimator, while preserving the nice properties. Our proposed estimators outperform existing estimators under various scenarios in simulation and real data example. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/155096
