Healthcare Business Intelligence PDF Download
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Author: Laura Madsen
Publisher:
ISBN: 9781119205326
Category : Business intelligence
Languages : en
Pages :
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Book Description
"This book will be constructed as a guidebook for healthcare organizations that are attempting BI/DW. It will address the primary functions of a business intelligence capability and how BI can ease the increasing regulatory reporting pressures on all healthcare organizations. Also included will be tables, checklists and a few forms. Tenative chapter contents: Chapter 1: What is Healthcare BI? Chapter 2: The Five Disciplines of Business Intelligence Chapter 3: The Importance of ETL Chapter 4: Starting with Data Governance Chapter 5: Creating a BI team Chapter 6: Data Modeling for Healthcare Chapter 7: Gaining Support for your BI program Chapter 8: Ensuring good User Adoption Chapter 9: Marketing Your BI Program Chapter 10: Maintaining Your BI Program"--
Author: Laura Madsen
Publisher:
ISBN: 9781119205326
Category : Business intelligence
Languages : en
Pages :
Get Book Here
Book Description
"This book will be constructed as a guidebook for healthcare organizations that are attempting BI/DW. It will address the primary functions of a business intelligence capability and how BI can ease the increasing regulatory reporting pressures on all healthcare organizations. Also included will be tables, checklists and a few forms. Tenative chapter contents: Chapter 1: What is Healthcare BI? Chapter 2: The Five Disciplines of Business Intelligence Chapter 3: The Importance of ETL Chapter 4: Starting with Data Governance Chapter 5: Creating a BI team Chapter 6: Data Modeling for Healthcare Chapter 7: Gaining Support for your BI program Chapter 8: Ensuring good User Adoption Chapter 9: Marketing Your BI Program Chapter 10: Maintaining Your BI Program"--
Author: Khuntia, Jiban
Publisher: IGI Global
ISBN: 1799823113
Category : Medical
Languages : en
Pages : 322
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Book Description
Business intelligence supports managers in enterprises to make informed business decisions in various levels and domains such as in healthcare. These technologies can handle large structured and unstructured data (big data) in the healthcare industry. Because of the complex nature of healthcare data and the significant impact of healthcare data analysis, it is important to understand both the theories and practices of business intelligence in healthcare. Theory and Practice of Business Intelligence in Healthcare is a collection of innovative research that introduces data mining, modeling, and analytic techniques to health and healthcare data; articulates the value of big volumes of data to health and healthcare; evaluates business intelligence tools; and explores business intelligence use and applications in healthcare. While highlighting topics including digital health, operations intelligence, and patient empowerment, this book is ideally designed for healthcare professionals, IT consultants, hospital directors, data management staff, data analysts, hospital administrators, executives, managers, academicians, students, and researchers seeking current research on the digitization of health records and health systems integration.
Author: Shilpa Balan
Publisher: Createspace Independent Publishing Platform
ISBN: 9781548829896
Category : Data mining
Languages : en
Pages : 110
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Book Description
Healthcare generates enormous amounts of data. Left unstructured and unanalyzed, this data does little to help hospitals and healthcare facilities offer better care or develop more effective practices. "Big data" isn't an issue confined to the healthcare industry-many other industries struggle to capitalize on the possibilities lurking within unmined data. In response to this need, analytical software such as IBM(R) Watson(TM)Analytics has become vital for long-term success. Working with a sample Medicaid data set, business intelligence experts Dr. Shilpa Balan and Dr. Joseph Otto reveal how to use IBM Watson Analytics to analyze healthcare data and transform unstructured data into actionable information. Balan and Otto break down the complex task of data analysis into easily understood sections, demonstrating vital aspects of data set analysis, such as creating a cloud-based data environment, data refinement, data exploration, predictive analytics, dashboard building, and social media data analysis. Used correctly, healthcare data sets can provide valuable insight into costs and claims, research and development, patient behavior, and medical records. Let Balan and Otto provide your facility with the data analysis techniques and skills needed to uncover the secrets of your facility's data collection.
Author: Allam Hamdan
Publisher: Springer Nature
ISBN: 3030720802
Category : Technology & Engineering
Languages : en
Pages : 503
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Book Description
This book focuses on the implementation of Artificial Intelligence in Business, Education and Healthcare, It includes research articles and expository papers on the applications of Artificial Intelligence on Decision Making, Entrepreneurship, Social Media, Healthcare, Education, Public Sector, FinTech, and RegTech. It also discusses the role of Artificial Intelligence in the current COVID-19 pandemic, in the health sector, education, and others. It also discusses the impact of Artificial Intelligence on decision-making in vital sectors of the economy.
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
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Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Author: Thomas H. Davenport
Publisher: Pearson Education
ISBN: 0133408701
Category : Business & Economics
Languages : en
Pages : 351
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Book Description
Make healthcare analytics work: leverage its powerful opportunities for improving outcomes, cost, and efficiency.This book gives you thepractical frameworks, strategies, tactics, and case studies you need to go beyond talk to action. The contributing healthcare analytics innovators survey the field’s current state, present start-to-finish guidance for planning and implementation, and help decision-makers prepare for tomorrow’s advances. They present in-depth case studies revealing how leading organizations have organized and executed analytic strategies that work, and fully cover the primary applications of analytics in all three sectors of the healthcare ecosystem: Provider, Payer, and Life Sciences. Co-published with the International Institute for Analytics (IIA), this book features the combined expertise of IIA’s team of leading health analytics practitioners and researchers. Each chapter is written by a member of the IIA faculty, and bridges the latest research findings with proven best practices. This book will be valuable to professionals and decision-makers throughout the healthcare ecosystem, including provider organization clinicians and managers; life sciences researchers and practitioners; and informaticists, actuaries, and managers at payer organizations. It will also be valuable in diverse analytics, operations, and IT courses in business, engineering, and healthcare certificate programs.
Author: Christo El Morr
Publisher: Springer
ISBN: 3030045064
Category : Medical
Languages : en
Pages : 113
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Book Description
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.
Author: Miltiadis Lytras
Publisher: Academic Press
ISBN: 0128220627
Category : Medical
Languages : en
Pages : 292
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Book Description
Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. - Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine - Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them - Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers
Author: Nate Moore
Publisher: Medical Group Management Association/Center for Research in Ambulatory Health Care Administration
ISBN: 9781568294322
Category : Medical
Languages : en
Pages : 154
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Book Description
Data flows into medical practices daily from practice management systems, electronic medical record (EMR) systems, accounting systems and many other sources. Too many practices extract only the bare minimum of data to file claims and meet reporting obligations, without recognizing the value in the flood of data that passes through the practice.
Author: Zbigniew Michalewicz
Publisher: Springer Science & Business Media
ISBN: 3540329293
Category : Computers
Languages : en
Pages : 249
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Book Description
Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address fundamental questions: What is likely to happen in the future? What is the best course of action? Adaptive Business Intelligence explores elements of data mining, predictive modeling, forecasting, optimization, and adaptability. The book explains the application of numerous prediction and optimization techniques, and shows how these concepts can be used to develop adaptive systems. Coverage includes linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy systems, genetic algorithms, simulated annealing, tabu search, ant systems, and agent-based modeling.
