Healthcare Data Analytics

Healthcare Data Analytics
Author: Chandan K. Reddy
Publisher: CRC Press
Total Pages: 756
Release: 2015-06-23
Genre: Business & Economics
ISBN: 148223212X
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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

Competing on Analytics

Competing on Analytics
Author: Thomas H. Davenport
Publisher: Harvard Business Press
Total Pages: 243
Release: 2007-03-06
Genre: Business & Economics
ISBN: 1422156303
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You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool. In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics.

Handbook of Healthcare Analytics

Handbook of Healthcare Analytics
Author: Tinglong Dai
Publisher: John Wiley & Sons
Total Pages: 496
Release: 2018-07-30
Genre: Business & Economics
ISBN: 1119300967
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How can analytics scholars and healthcare professionals access the most exciting and important healthcare topics and tools for the 21st century? Editors Tinglong Dai and Sridhar Tayur, aided by a team of internationally acclaimed experts, have curated this timely volume to help newcomers and seasoned researchers alike to rapidly comprehend a diverse set of thrusts and tools in this rapidly growing cross-disciplinary field. The Handbook covers a wide range of macro-, meso- and micro-level thrusts—such as market design, competing interests, global health, personalized medicine, residential care and concierge medicine, among others—and structures what has been a highly fragmented research area into a coherent scientific discipline. The handbook also provides an easy-to-comprehend introduction to five essential research tools—Markov decision process, game theory and information economics, queueing games, econometric methods, and data science—by illustrating their uses and applicability on examples from diverse healthcare settings, thus connecting tools with thrusts. The primary audience of the Handbook includes analytics scholars interested in healthcare and healthcare practitioners interested in analytics. This Handbook: Instills analytics scholars with a way of thinking that incorporates behavioral, incentive, and policy considerations in various healthcare settings. This change in perspective—a shift in gaze away from narrow, local and one-off operational improvement efforts that do not replicate, scale or remain sustainable—can lead to new knowledge and innovative solutions that healthcare has been seeking so desperately. Facilitates collaboration between healthcare experts and analytics scholar to frame and tackle their pressing concerns through appropriate modern mathematical tools designed for this very purpose. The handbook is designed to be accessible to the independent reader, and it may be used in a variety of settings, from a short lecture series on specific topics to a semester-long course.

R for Health Data Science

R for Health Data Science
Author: Ewen Harrison
Publisher: CRC Press
Total Pages: 354
Release: 2020-12-31
Genre: Medical
ISBN: 1000226166
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In this age of information, the manipulation, analysis, and interpretation of data have become a fundamental part of professional life; nowhere more so than in the delivery of healthcare. From the understanding of disease and the development of new treatments, to the diagnosis and management of individual patients, the use of data and technology is now an integral part of the business of healthcare. Those working in healthcare interact daily with data, often without realising it. The conversion of this avalanche of information to useful knowledge is essential for high-quality patient care. R for Health Data Science includes everything a healthcare professional needs to go from R novice to R guru. By the end of this book, you will be taking a sophisticated approach to health data science with beautiful visualisations, elegant tables, and nuanced analyses. Features Provides an introduction to the fundamentals of R for healthcare professionals Highlights the most popular statistical approaches to health data science Written to be as accessible as possible with minimal mathematics Emphasises the importance of truly understanding the underlying data through the use of plots Includes numerous examples that can be adapted for your own data Helps you create publishable documents and collaborate across teams With this book, you are in safe hands – Prof. Harrison is a clinician and Dr. Pius is a data scientist, bringing 25 years’ combined experience of using R at the coal face. This content has been taught to hundreds of individuals from a variety of backgrounds, from rank beginners to experts moving to R from other platforms.

Competing on Healthcare Analytics

Competing on Healthcare Analytics
Author: J. Bryan Bennett
Publisher: Createspace Independent Publishing Platform
Total Pages: 108
Release: 2016-04-02
Genre: Medical care
ISBN: 9781530745203
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The rate of change in the healthcare industry has been staggering. From Electronic Health Records to ICD-10 to Population Health, few industries have undergone such change in such a short amount of time. The silver lining is the treasure trove of digital data, which will enable providers to analyze and compare information across thousands of patients instead of relying on the anecdotal evidence they previously used. To access this knowledge, organizations are turning to analytics. Unfortunately, many organizations are rushing to implement any type of healthcare analytics program without consideration of the steps that must take place to build an effective, long-term analytics solution. Competing on Healthcare Analytics is a practical guide to implementing population health analytics. The book makes a clear argument for how an analytics initiative should be implemented using Mr. Bennett's foundational approach and identifies the most critical success factors. Healthcare organizations should re-access their approach to implementing population health analytics after reading this book. This book includes: - A detailed healthcare transformation model which tracks the progression of analytics to become an "Analytics Focused" healthcare organization;- A discussion of the value of using the foundational approach;- Research studies performed with healthcare organization participants supporting the approach;- A healthcare organization readiness assessment;- An implementation roadmap with critical success factors;- A discussion on what it takes to be a healthcare analytics competitor.Professor Bennett has been presenting his approach to implementing population health analytics to audiences across the country to rave reviews since the summer of 2014. Now it is your turn to access this knowledge that has been honed through his work in healthcare as well as in other industries with clients such as Microsoft, BellSouth, Chase and many others.

Adaptive Health Management Information Systems

Adaptive Health Management Information Systems
Author: Joseph Tan
Publisher: Jones & Bartlett Learning
Total Pages: 456
Release: 2010-03-09
Genre: Business & Economics
ISBN: 0763756911
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Health management information systems : a managerial perspective / Joseph Tan -- Health management information systems executives : roles and responsibilities of chief executive officers and chief information officers in healthcare services organizations / Joseph Tan -- Online health information seeking : access and digital equity considerations / Fay Cobb Payton and Joseph Tan -- Health management information system enterprise software : the new generation of HMIS administrative applications / Joshia Tan with Joseph Tan -- Community health information networks : building virtual communities and networking health provider organizations / Jayfus T. Doswell, SherRhonda R. Gibbs, and Kelley M. Duncanson -- Trending toward patient-centric management systems / Joseph Tan with Joshia Tan -- Health management information system integration : achieving systems interoperability with Web services / J.K. Zhang and Joseph Tan -- Health management strategic information system planning/information requirements / Jon Blue and Joseph Tan -- Systems development : health management information system analysis and developmental methodologies / Joseph Tan -- Data stewardship : foundation for health management information system design, implementation, and evaluation / Bryan Bennett -- Managing health management information system projects : system implementation and information technology services management / Joseph Tan -- Health management information system standards : standards adoption in healthcare information technologies / Sanjay P. Sood ... [et al.] -- Health management information system governance, policy, and international perspectives : HMIS globalization through e-health / Anantachai Panjamapirom and Philip F. Musa -- Health management information system innovation : managing innovation diffusion in healthcare services organizations / Tugrul U. Daim, Nuri Basoglu, and Joseph Tan.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare
Author: Adam Bohr
Publisher: Academic Press
Total Pages: 385
Release: 2020-06-21
Genre: Computers
ISBN: 0128184396
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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

Predictive Analytics

Predictive Analytics
Author: Eric Siegel
Publisher: John Wiley & Sons
Total Pages: 368
Release: 2016-01-12
Genre: Business & Economics
ISBN: 1119153654
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"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a

Redefining Health Care

Redefining Health Care
Author: Michael E. Porter
Publisher: Harvard Business Press
Total Pages: 540
Release: 2006-04-24
Genre: Business & Economics
ISBN: 1422133362
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The U.S. health care system is in crisis. At stake are the quality of care for millions of Americans and the financial well-being of individuals and employers squeezed by skyrocketing premiums—not to mention the stability of state and federal government budgets. In Redefining Health Care, internationally renowned strategy expert Michael Porter and innovation expert Elizabeth Teisberg reveal the underlying—and largely overlooked—causes of the problem, and provide a powerful prescription for change. The authors argue that competition currently takes place at the wrong level—among health plans, networks, and hospitals—rather than where it matters most, in the diagnosis, treatment, and prevention of specific health conditions. Participants in the system accumulate bargaining power and shift costs in a zero-sum competition, rather than creating value for patients. Based on an exhaustive study of the U.S. health care system, Redefining Health Care lays out a breakthrough framework for redefining the way competition in health care delivery takes place—and unleashing stunning improvements in quality and efficiency. With specific recommendations for hospitals, doctors, health plans, employers, and policy makers, this book shows how to move health care toward positive-sum competition that delivers lasting benefits for all.

Analytics in Healthcare and the Life Sciences

Analytics in Healthcare and the Life Sciences
Author: Dwight McNeill
Publisher: Pearson Education
Total Pages: 351
Release: 2014
Genre: Business & Economics
ISBN: 0133407330
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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.