Download or read book Essentials of Healthcare Analytics written by Prof. Dr. R Gopal, Prof. Dr. Gagandeep Kaur Nagra, Dr. Priya Vij and published by Notion Press. This book was released on 2024-08-28 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a world where data-driven decisions can lead to changes in the land in health care, "Essentials of Healthcare Analytics" is the unique source of how to leverage that data to deliver better care at a lower cost and with better margins. This book delves deep into the great yet critical role that analytics play in health care and looks forward to how the technologies, methodologies, and best practices in this field are set to have their future defined. It could entail such diverse topics as foundational concepts through advanced applications, data integration, predictive modeling, and real-time analytics. Learn how to leverage state-of-the-art tools such as Python and R in data analysis and find out how machine learning and AI have changed patient care, personalized medicine, and healthcare management. Whether you are a working professional in healthcare, a data analyst, or a student who seeks to break into such an exciting field, Essentials of Healthcare Analytics will prepare you with knowledge and the right skill set to negotiate the complexities of healthcare through data and make this knowledge actionable for informed decisions. Embrace the future of healthcare with the deep understanding of how analytics can drive your organization towards innovation and efficiency.

Download or read book Analytics in Healthcare written by Christo El Morr and published by Springer. This book was released on 2019-01-21 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a practical introduction to healthcare analytics that does not require a background in data science or statistics. It presents the basics of data, analytics and tools and includes multiple examples of their applications in the field. The book also identifies practical challenges that fuel the need for analytics in healthcare as well as the solutions to address these problems. In the healthcare field, professionals have access to vast amount of data in the form of staff records, electronic patient record, clinical findings, diagnosis, prescription drug, medical imaging procedure, mobile health, resources available, etc. Managing the data and analyzing it to properly understand it and use it to make well-informed decisions can be a challenge for managers and health care professionals. A new generation of applications, sometimes referred to as end-user analytics or self-serve analytics, are specifically designed for non-technical users such as managers and business professionals. The ability to use these increasingly accessible tools with the abundant data requires a basic understanding of the core concepts of data, analytics, and interpretation of outcomes. This book is a resource for such individuals to demystify and learn the basics of data management and analytics for healthcare, while also looking towards future directions in the field.

Download or read book Healthcare Analytics for Quality and Performance Improvement written by Trevor L. Strome and published by John Wiley & Sons. This book was released on 2013-10-02 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Improve patient outcomes, lower costs, reduce fraud—all with healthcare analytics Healthcare Analytics for Quality and Performance Improvement walks your healthcare organization from relying on generic reports and dashboards to developing powerful analytic applications that drive effective decision-making throughout your organization. Renowned healthcare analytics leader Trevor Strome reveals in this groundbreaking volume the true potential of analytics to harness the vast amounts of data being generated in order to improve the decision-making ability of healthcare managers and improvement teams. Examines how technology has impacted healthcare delivery Discusses the challenge facing healthcare organizations: to leverage advances in both clinical and information technology to improve quality and performance while containing costs Explores the tools and techniques to analyze and extract value from healthcare data Demonstrates how the clinical, business, and technology components of healthcare organizations (HCOs) must work together to leverage analytics Other industries are already taking advantage of big data. Healthcare Analytics for Quality and Performance Improvement helps the healthcare industry make the most of the precious data already at its fingertips for long-overdue quality and performance improvement.

Download or read book Fundamentals of Clinical Data Science written by Pieter Kubben and published by Springer. This book was released on 2018-12-21 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.

Download or read book Healthcare Data Analytics written by Chandan K. Reddy and published by CRC Press. This book was released on 2015-06-23 with total page 756 pages. Available in PDF, EPUB and Kindle. Book excerpt: At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available

Download or read book Healthcare Analytics Made Simple written by Vikas (Vik) Kumar and published by Packt Publishing Ltd. This book was released on 2018-07-31 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Add a touch of data analytics to your healthcare systems and get insightful outcomes Key Features Perform healthcare analytics with Python and SQL Build predictive models on real healthcare data with pandas and scikit-learn Use analytics to improve healthcare performance Book Description In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists’ work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed. By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples. What you will learn Gain valuable insight into healthcare incentives, finances, and legislation Discover the connection between machine learning and healthcare processes Use SQL and Python to analyze data Measure healthcare quality and provider performance Identify features and attributes to build successful healthcare models Build predictive models using real-world healthcare data Become an expert in predictive modeling with structured clinical data See what lies ahead for healthcare analytics Who this book is for Healthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.

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 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book 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 health care professionals and executives, this book presents the current thinking of academic and industry researchers and leaders from around the world. Using non-technical language, it includes case studies that illustrate the business processes that underlie the use of big data and health analytics to improve health care delivery.

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.

Download or read book Essentials of Clinical Informatics written by Mark E. Frisse MD, MS, MBA and published by Oxford University Press. This book was released on 2019-04-15 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essentials of Clinical Informatics provides a concise and user-friendly overview on important topics such as technical infrastructure, team members and their roles, informatics methods, policies and laws, implementation, and operations. With increased interest in training and expertise in order to participate in all aspects of medical technology from basic function of electronic health record to data analytics and quality improvement to population health, this work serves as a foundational guide to better understand and analyze medical data. The book is separated into six parts: Part 1, "Areas of Focus", is an introduction to the healthcare system and healthcare information systems; Part 2, "The Framework", discusses the theoretical and procedural infrastructure of informatics, including data, knowledge, people, policies, procedures, and regulations; Part 3, "The Foundation", covers the fundamentals of clinical informatics in detail, including data representation, computer science, logic and programming, decision-making and decision support, analytics, user experience, and project management; Part 4, "Application of Informatics in Healthcare", looks at the roles of informatics in the spectrum of healthcare environments from home to hospital to population health; Part 5, "Future Trends', presents a view of future trends and methods to stay current; and Part 6, "Appendix", has reference data, glossary, case discussions, citations, recommendations for further reading, and self-assessment questions which may be of interest to professionals who are preparing for certification examinations.

Download or read book Essentials of Applied Quantitative Methods for Health Services written by James Lewis and published by Jones & Bartlett Learning. This book was released on 2011 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essentials of Applied Quantitative Methods for Health Services Management shows students how to use statistics in all aspects of health care administration. Offering careful, step-by-step instructions for calculations using Microsoft Excel, this hands-on resource begins with basic foundational competencies in statistics, and then walks the reader through forecasting, designing and analyzing systems, and project analysis. The text stresses the application of concepts, models, and techniques and provides problems involving all of the methods. It is intended to build a student management and planning tools repertoire. Ideal for junior and seniors in baccalaureate level health administration programs as well as first year graduate students in non-MBA health administration programs, this book requires limited previous knowledge of statistics; its mathematical dimension is equal to basic high school algebra.

Download or read book Essentials of Statistics in Health Information Technology written by Carol E. Osborn and published by Jones & Bartlett Publishers. This book was released on 2007-08-24 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the author of Statistical Applications for Health Information Management, this text provides a solid foundation of the fundamentals of statistics in health information technology in an accessible and reader-friendly format. A single case study is woven throughout the book to serve as an example for each statistical process covered. Attention is given to morbidity and mortality measures, graphical display of data, measurement, central tendency and variability, normal distribution and statistical inference, and inferential statistics. Written specifically for health information technology students who need a basic understanding of the topic, this text is ideal for those with a modest background in mathematics and no prior training in statistics. Features: • Introduces students to how statistical techniques can be used to describe and make inferences from healthcare data. • Includes traditional hospital statistics such as average length of stay and total inpatient service days. • Uses examples in both SPSS and Microsoft Excel.

Download or read book Essentials of Health Information Systems and Technology written by Jean A Balgrosky and published by Jones & Bartlett Publishers. This book was released on 2014-08-11 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Key Terms; Discussion Questions; References; Chapter 2 HIS Scope, Definition, and Conceptual Model; Learning Objectives; Introduction; HIS Uses in Organizational and Community Settings; Summary; Key Terms; Discussion Questions; References; Section II: Systems and Management; Chapter 3 HIS Strategic Planning; Learning Objectives; Introduction; HIS Strategy: Organizational Strategy as Its Roadmap; HIS Strategy: Where Do We Begin?; Why HIS Strategy Matters; HIS and Technology Strategy: Advancing Public Health; HIS and Technology Strategy: Architecture Builds a Strong House.

Download or read book Big Data Analytics in Healthcare written by Anand J. Kulkarni and published by Springer Nature. This book was released on 2019-10-01 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes state-of-the-art discussions on various issues and aspects of the implementation, testing, validation, and application of big data in the context of healthcare. The concept of big data is revolutionary, both from a technological and societal well-being standpoint. This book provides a comprehensive reference guide for engineers, scientists, and students studying/involved in the development of big data tools in the areas of healthcare and medicine. It also features a multifaceted and state-of-the-art literature review on healthcare data, its modalities, complexities, and methodologies, along with mathematical formulations. The book is divided into two main sections, the first of which discusses the challenges and opportunities associated with the implementation of big data in the healthcare sector. In turn, the second addresses the mathematical modeling of healthcare problems, as well as current and potential future big data applications and platforms.

Download or read book Data Science for Healthcare written by Sergio Consoli and published by Springer. This book was released on 2019-02-23 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern recognition, computer vision, and Semantic Web technologies, and focuses on their direct application to healthcare. Building on three tutorial-like chapters on data science in healthcare, the following eleven chapters highlight success stories on the application of data science in healthcare, where data science and artificial intelligence technologies have proven to be very promising. This book is primarily intended for data scientists involved in the healthcare or medical sector. By reading this book, they will gain essential insights into the modern data science technologies needed to advance innovation for both healthcare businesses and patients. A basic grasp of data science is recommended in order to fully benefit from this book.

Download or read book Essentials of Health Policy and Law written by Joel Bern Teitelbaum and published by Jones & Bartlett Publishers. This book was released on 2013 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given the prominent role played by policy and law in the health of all Americans, the aim of this book is to help readers understand the broad context of health policy and law. The essential policy and legal issues impacting and flowing out of the health care and public health systems, and the way health policies and laws are formulated. Think of this textbook as an extended manual.introductory, concise, and straightforward.to the seminal issues in U.S. health policy and law, and thus as a jumping off point for discussion, reflection, research, and analysis.

Download or read book Demystifying Big Data and Machine Learning for Healthcare written by Prashant Natarajan and published by CRC Press. This book was released on 2017-02-15 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it. Demystifying Big Data and Machine Learning for Healthcare investigates how healthcare organizations can leverage this tapestry of big data to discover new business value, use cases, and knowledge as well as how big data can be woven into pre-existing business intelligence and analytics efforts. This book focuses on teaching you how to: Develop skills needed to identify and demolish big-data myths Become an expert in separating hype from reality Understand the V’s that matter in healthcare and why Harmonize the 4 C’s across little and big data Choose data fi delity over data quality Learn how to apply the NRF Framework Master applied machine learning for healthcare Conduct a guided tour of learning algorithms Recognize and be prepared for the future of artificial intelligence in healthcare via best practices, feedback loops, and contextually intelligent agents (CIAs) The variety of data in healthcare spans multiple business workflows, formats (structured, un-, and semi-structured), integration at point of care/need, and integration with existing knowledge. In order to deal with these realities, the authors propose new approaches to creating a knowledge-driven learning organization-based on new and existing strategies, methods and technologies. This book will address the long-standing challenges in healthcare informatics and provide pragmatic recommendations on how to deal with them.

Download or read book Healthcare Data Analytics and Management written by Nilanjan Dey and published by Academic Press. This book was released on 2018-11-15 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare Data Analytics and Management help readers disseminate cutting-edge research that delivers insights into the analytic tools, opportunities, novel strategies, techniques and challenges for handling big data, data analytics and management in healthcare. As the rapidly expanding and heterogeneous nature of healthcare data poses challenges for big data analytics, this book targets researchers and bioengineers from areas of machine learning, data mining, data management, and healthcare providers, along with clinical researchers and physicians who are interested in the management and analysis of healthcare data. Covers data analysis, management and security concepts and tools in the healthcare domain Highlights electronic medical health records and patient information records Discusses the different techniques to integrate Big data and Internet-of-Things in healthcare, including machine learning and data mining Includes multidisciplinary contributions in relation to healthcare applications and challenges