Healthcare Business Intelligence
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| Author | : Laura Madsen |
| Publisher | : John Wiley & Sons |
| Total Pages | : 336 |
| Release | : 2012-09-04 |
| Genre | : Business & Economics |
| ISBN | : 1118217802 |
Solid business intelligence guidance uniquely designed for healthcare organizations Increasing regulatory pressures on healthcare organizations have created a national conversation on data, reporting and analytics in healthcare. Behind the scenes, business intelligence (BI) and data warehousing (DW) capabilities are key drivers that empower these functions. Healthcare Business Intelligence is designed as a guidebook for healthcare organizations dipping their toes into the areas of business intelligence and data warehousing. This volume is essential in how a BI capability can ease the increasing regulatory reporting pressures on all healthcare organizations. Explores the five tenets of healthcare business intelligence Offers tips for creating a BI team Identifies what healthcare organizations should focus on first Shows you how to gain support for your BI program Provides tools and techniques that will jump start your BI Program Explains how to market and maintain your BI Program The risk associated with doing BI/DW wrong is high, and failures are well documented. Healthcare Business Intelligence helps you get it right, with expert guidance on getting your BI program started and successfully keep it going.
| Author | : Khuntia, Jiban |
| Publisher | : IGI Global |
| Total Pages | : 322 |
| Release | : 2019-12-27 |
| Genre | : Medical |
| ISBN | : 1799823113 |
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 |
| Total Pages | : 110 |
| Release | : 2017-09-06 |
| Genre | : Data mining |
| ISBN | : 9781548829896 |
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 | : Christo El Morr |
| Publisher | : Springer |
| Total Pages | : 113 |
| Release | : 2019-01-21 |
| Genre | : Medical |
| ISBN | : 3030045064 |
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 | : Adam Bohr |
| Publisher | : Academic Press |
| Total Pages | : 385 |
| Release | : 2020-06-21 |
| Genre | : Computers |
| ISBN | : 0128184396 |
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 | : Dwight McNeill |
| Publisher | : Pearson Education |
| Total Pages | : 351 |
| Release | : 2014 |
| Genre | : Business & Economics |
| ISBN | : 0133407330 |
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 | : Vikas (Vik) Kumar |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 258 |
| Release | : 2018-07-31 |
| Genre | : Computers |
| ISBN | : 1787283224 |
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.
| Author | : Allam Hamdan |
| Publisher | : Springer Nature |
| Total Pages | : 503 |
| Release | : 2021-07-12 |
| Genre | : Technology & Engineering |
| ISBN | : 3030720802 |
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 | : Trevor L. Strome |
| Publisher | : John Wiley & Sons |
| Total Pages | : 246 |
| Release | : 2013-10-02 |
| Genre | : Business & Economics |
| ISBN | : 1118760158 |
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.
| Author | : Nate Moore |
| Publisher | : Medical Group Management Association/Center for Research in Ambulatory Health Care Administration |
| Total Pages | : 154 |
| Release | : 2013 |
| Genre | : Medical |
| ISBN | : 9781568294322 |
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.
