Practical Predictive Analytics And Decisioning Systems For Medicine Informatics Accuracy And Cost Effectiveness For Healthcare Administration And Del
Download Practical Predictive Analytics And Decisioning Systems For Medicine Informatics Accuracy And Cost Effectiveness For Healthcare Administration And Del PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Practical Predictive Analytics And Decisioning Systems For Medicine Informatics Accuracy And Cost Effectiveness For Healthcare Administration And Del book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Practical Predictive Analytics and Decisioning Systems for Medicine
With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are sitting on growing mountains of data. Not only does the data grow from patient volume but the type of data we store is also growing exponentially. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses some of the most pressing issues and challenges where data integrity is compromised: patient safety, patient communication, and patient information. Through the use of predictive analytic models and applications, this book is an invaluable resource to predict more accurate outcomes to help improve quality care in the healthcare and medical industries in the most cost–efficient manner.Practical Predictive Analytics and Decisioning Systems for Medicine provides the basics of predictive analytics for those new to the area and focuses on general philosophy and activities in the healthcare and medical system. It explains why predictive models are important, and how they can be applied to the predictive analysis process in order to solve real industry problems. Researchers need this valuable resource to improve data analysis skills and make more accurate and cost-effective decisions. - Includes models and applications of predictive analytics why they are important and how they can be used in healthcare and medical research - Provides real world step-by-step tutorials to help beginners understand how the predictive analytic processes works and to successfully do the computations - Demonstrates methods to help sort through data to make better observations and allow you to make better predictions
Practical Predictive Analytics and Decisioning Systems for Medicine
With the advent of electronic medical records years ago and the increasing capabilities of computers, our healthcare systems are sitting on growing mountains of data. Not only does the data grow from patient volume but the type of data we store is also growing exponentially. Practical Predictive Analytics and Decisioning Systems for Medicine provides research tools to analyze these large amounts of data and addresses some of the most pressing issues and challenges where data integrity is compromised: patient safety, patient communication, and patient information. Through the use of predictive analytic models and applications, this book is an invaluable resource to predict more accurate outcomes to help improve quality care in the healthcare and medical industries in the most cost-efficient manner. Practical Predictive Analytics and Decisioning Systems for Medicine provides the basics of predictive analytics for those new to the area and focuses on general philosophy and activities in the healthcare and medical system. It explains why predictive models are important, and how they can be applied to the predictive analysis process in order to solve real industry problems. Researchers need this valuable resource to improve data analysis skills and make more accurate and cost-effective decisions.
Real-World Evidence in the Pharmaceutical Landscape
In Real-World Evidence in the Pharmaceutical Landscape, life science industry experts Sunil Dravida and his co-authors have developed the first comprehensive overview of its kind on Real-World Data (RWD) in the pharmaceutical industry. The authors examine the challenges and opportunities in applying real-world data along the pharmaceutical continuum, from clinical development to medical affairs, health economics and outcomes, and marketing. They address the difficulties identifying the suitable data sources, ensuring compliance with privacy, security and regulatory requirements, and the big job of translating data into Real-World Evidence (RWE) to generate meaningful insights that can improve decision making by stakeholders and measurable outcomes that can enhance people’s health and well-being. This book is a must-read for those in the pharmaceutical industry involved with RWD, which includes just about every role, as healthcare is now dominated by the need for high-quality data that can enable better decision-making. This book is especially critical for those designing and leading RWD Centers of Excellence in pharmaceutical companies and the service providers supporting the RWD ecosystem.