Better Healthcare Through Math
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Better Healthcare Through Math
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Author : Sanjeev Agrawal
language : en
Publisher: Forbesbooks
Release Date : 2020-11-17
Better Healthcare Through Math written by Sanjeev Agrawal and has been published by Forbesbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-17 with categories.
GETTING A DOCTOR'S APPOINTMENT SHOULDN'T BE HARDER THAN BOOKING A VACATION The US healthcare system excels in research, innovation, and clinical care, but is failing to keep up with the operational challenges of the digital age. Today's healthcare organizations face immense financial challenges, and their most valuable resources--people, rooms, and equipment--are being used inefficiently. The result? Long wait times for patients, overstressed staff, underused assets, and poor ROI for organizations. Why do health systems struggle with optimization? The fundamental problem is one of matching an unpredictable demand for services with a constrained supply. The math being used to solve this problem is a holdover from the paper-and-pencil era. In Better Healthcare Through Math, authors Mohan Giridharadas and Sanjeev Agrawal show you that there is a better way. Healthcare systems can harness the power of sophisticated, analytics-driven mathematics to optimize the matching of supply and demand. By upgrading to software systems built on better math, they can enable staff to make data-based decisions to flatten peaks of demand and create smoother patient flow.
Using Predictive Analytics To Improve Healthcare Outcomes
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Author : John W. Nelson
language : en
Publisher: John Wiley & Sons
Release Date : 2021-07-09
Using Predictive Analytics To Improve Healthcare Outcomes written by John W. Nelson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-09 with Mathematics categories.
Using Predictive Analytics to Improve Healthcare Outcomes Winner of the American Journal of Nursing (AJN) Informatics Book of the Year Award 2021! Discover a comprehensive overview, from established leaders in the field, of how to use predictive analytics and other analytic methods for healthcare quality improvement. Using Predictive Analytics to Improve Healthcare Outcomes delivers a 16-step process to use predictive analytics to improve operations in the complex industry of healthcare. The book includes numerous case studies that make use of predictive analytics and other mathematical methodologies to save money and improve patient outcomes. The book is organized as a “how-to” manual, showing how to use existing theory and tools to achieve desired positive outcomes. You will learn how your organization can use predictive analytics to identify the most impactful operational interventions before changing operations. This includes: A thorough introduction to data, caring theory, Relationship-Based Care®, the Caring Behaviors Assurance System©, and healthcare operations, including how to build a measurement model and improve organizational outcomes. An exploration of analytics in action, including comprehensive case studies on patient falls, palliative care, infection reduction, reducing rates of readmission for heart failure, and more—all resulting in action plans allowing clinicians to make changes that have been proven in advance to result in positive outcomes. Discussions of how to refine quality improvement initiatives, including the use of “comfort” as a construct to illustrate the importance of solid theory and good measurement in adequate pain management. An examination of international organizations using analytics to improve operations within cultural context. Using Predictive Analytics to Improve Healthcare Outcomes is perfect for executives, researchers, and quality improvement staff at healthcare organizations, as well as educators teaching mathematics, data science, or quality improvement. Employ this valuable resource that walks you through the steps of managing and optimizing outcomes in your clinical care operations.
Systems Analysis Tools For Better Health Care Delivery
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Author : Panos M. Pardalos
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-01-04
Systems Analysis Tools For Better Health Care Delivery written by Panos M. Pardalos and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-04 with Mathematics categories.
This book presents some recent systems engineering and mathematical tools for health care along with their real-world applications by health care practitioners and engineers. Advanced approaches, tools, and algorithms used in operating room scheduling and patient flow are covered. State-of-the-art results from applications of data mining, business process modeling, and simulation in healthcare, together with optimization methods, form the core of the volume. Systems Analysis Tools for Better Health Care Delivery illustrates the increased need of partnership between engineers and health care professionals. This book will benefit researchers and practitioners in health care delivery institutions, staff members and professionals of specialized hospital units, and lecturers and graduate students in engineering, applied mathematics, business administration and health care.
Math Basics For The Health Care Professional
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Author : Michele Lesmeister
language : en
Publisher: Pearson
Release Date : 2017-07-23
Math Basics For The Health Care Professional written by Michele Lesmeister and has been published by Pearson this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-23 with Mathematics categories.
"Math Basics for the Health Care Professional helps trainees in a wide variety of healthcare professions to master a vital skill toward their career success. This workbook incorporates every aspect of math relevant to health care applications with a wealth practice opportunities throughout. The third edition continues to promote critical thinking through an organized presentation of instruction, practice, and self assessment. Its new features make for an even better guide to increase math proficiency. These new features include: a supplementary CD-ROM with additional sets of challenging practice tests; coverage of occupation-based units that are essential for health care personnel, including reading drug labels, medicine cups, syringes, and intravenous fluid, apothecary measurement and conversions, parenteral dosages, basic intravenous administration and basic dosage by weight units; two extra units reviewing pre-algebra basics and the metric system; and an appendix of extra practice unit tests with answer keys for easy self-checking."--Google Books viewed Sept. 21, 2021.
Math Basics For The Health Care Professional
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Author : Michele Benjamin-Lesmeister
language : en
Publisher: Prentice Hall
Release Date : 2008-02-06
Math Basics For The Health Care Professional written by Michele Benjamin-Lesmeister and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-02-06 with Medical categories.
Math Basics for the Health Care Professional helps trainees in a wide variety of healthcare professions to master a vital skill toward their career success. This workbook incorporates every aspect of math relevant to health care applications with a wealth practice opportunities throughout. The third edition continues to promote critical thinking through an organized presentation of instruction, practice, and self assessment. Its new features make for an even better guide to increase math proficiency. These new features include: a supplementary CD-ROM with additional sets of challenging practice tests; coverage of occupation-based units that are essential for health care personnel, including reading drug labels, medicine cups, syringes, and intravenous fluid, apothecary measurement and conversions, parenteral dosages, basic intravenous administration and basic dosage by weight units; two extra units reviewing pre-algebra basics and the metric system; and an appendix of extra practice unit tests with answer keys for easy self-checking.
Mathematics For Healthcare Professionals
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Author : Edward M. Stumpf
language : en
Publisher:
Release Date : 2007-01-01
Mathematics For Healthcare Professionals written by Edward M. Stumpf and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-01-01 with Mathematics categories.
"Mathematics for Healthcare Professionals is a one-semester course text that covers the basic computations with fractions and decimals, ratio and proportion, percentage, measurement systems, diluting of solutions, graphs, dosage and concentration problems, and basic algebra and statistics. The course, offered in a workbook style, allows for completion at the learner's particular pace or in a more structured instructor-driven environment. The text is in easy-to-read format, avoiding formal math proofs in favor of simple syntax and a focus on learning the mechanics of the math involved.Examples of problems, computation procedures and plenty of exercises are provided for the student to master the material. Complete solutions as well as quizzes and test questions are provided to the instructor."
Improving Health Care Quality
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Author : Mary Ann Shifflet
language : en
Publisher: John Wiley & Sons
Release Date : 2020-05-04
Improving Health Care Quality written by Mary Ann Shifflet and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-04 with Medical categories.
Learn how to improve the quality of health care offered by your institution using data you already have Improving Health Care Quality: Case Studies with JMP® teaches readers how to systematically identify problems, collect and interpret data, and solve issues in the real world. Relying on JMP® software, the authors walk readers through the process of applying quality improvement techniques to real-life health care problems. The case studies provided in the book vary significantly and provide a wide-ranging view of the application of quality improvement techniques in the health care field. Studies regarding length of stay of diabetes patients to benchmarking the costs of hip replacement all serve to illuminate and explain the underlying concepts of statistical analysis. The authors break each case study down into several sections, including: Background and Task Data and Data Management Analysis Summary Concepts and Tools Exercises and Discussion Questions Each section reinforces the lessons learned in each case study and helps the reader learn to apply statistical data to their own health care quality problems.
Data Mining And Analytics In Healthcare Management
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Author : David L. Olson
language : en
Publisher: Springer Nature
Release Date : 2023-04-20
Data Mining And Analytics In Healthcare Management written by David L. Olson and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-20 with Medical categories.
This book presents data mining methods in the field of healthcare management in a practical way. Healthcare quality and disease prevention are essential in today’s world. Healthcare management faces a number of challenges, e.g. reducing patient growth through disease prevention, stopping or slowing disease progression, and reducing healthcare costs while improving quality of care. The book provides an overview of current healthcare management problems and highlights how analytics and knowledge management have been used to better cope with them. It then demonstrates how to use descriptive and predictive analytics tools to help address these challenges. In closing, it presents applications of software solutions in the context of healthcare management. Given its scope, the book will appeal to a broad readership, from researchers and students in the operations research and management field to practitioners such as data analysts and decision-makers who work in the healthcare sector.
Analytics In Healthcare And The Life Sciences
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Author : Thomas H. Davenport
language : en
Publisher: Pearson Education
Release Date : 2013-11-04
Analytics In Healthcare And The Life Sciences written by Thomas H. Davenport and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-04 with Business & Economics categories.
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.
Data Science And Predictive Analytics
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Author : Ivo D. Dinov
language : en
Publisher: Springer
Release Date : 2018-08-27
Data Science And Predictive Analytics written by Ivo D. Dinov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-27 with Computers categories.
Over the past decade, Big Data have become ubiquitous in all economic sectors, scientific disciplines, and human activities. They have led to striking technological advances, affecting all human experiences. Our ability to manage, understand, interrogate, and interpret such extremely large, multisource, heterogeneous, incomplete, multiscale, and incongruent data has not kept pace with the rapid increase of the volume, complexity and proliferation of the deluge of digital information. There are three reasons for this shortfall. First, the volume of data is increasing much faster than the corresponding rise of our computational processing power (Kryder’s law > Moore’s law). Second, traditional discipline-bounds inhibit expeditious progress. Third, our education and training activities have fallen behind the accelerated trend of scientific, information, and communication advances. There are very few rigorous instructional resources, interactive learning materials, and dynamic training environments that support active data science learning. The textbook balances the mathematical foundations with dexterous demonstrations and examples of data, tools, modules and workflows that serve as pillars for the urgently needed bridge to close that supply and demand predictive analytic skills gap. Exposing the enormous opportunities presented by the tsunami of Big data, this textbook aims to identify specific knowledge gaps, educational barriers, and workforce readiness deficiencies. Specifically, it focuses on the development of a transdisciplinary curriculum integrating modern computational methods, advanced data science techniques, innovative biomedical applications, and impactful health analytics. The content of this graduate-level textbook fills a substantial gap in integrating modern engineering concepts, computational algorithms, mathematical optimization, statistical computing and biomedical inference. Big data analytic techniques and predictive scientific methods demand broad transdisciplinary knowledge, appeal to an extremely wide spectrum of readers/learners, and provide incredible opportunities for engagement throughout the academy, industry, regulatory and funding agencies. The two examples below demonstrate the powerful need for scientific knowledge, computational abilities, interdisciplinary expertise, and modern technologies necessary to achieve desired outcomes (improving human health and optimizing future return on investment). This can only be achieved by appropriately trained teams of researchers who can develop robust decision support systems using modern techniques and effective end-to-end protocols, like the ones described in this textbook. • A geriatric neurologist is examining a patient complaining of gait imbalance and posture instability. To determine if the patient may suffer from Parkinson’s disease, the physician acquires clinical, cognitive, phenotypic, imaging, and genetics data (Big Data). Most clinics and healthcare centers are not equipped with skilled data analytic teams that can wrangle, harmonize and interpret such complex datasets. A learner that completes a course of study using this textbook will have the competency and ability to manage the data, generate a protocol for deriving biomarkers, and provide an actionable decision support system. The results of this protocol will help the physician understand the entire patient dataset and assist in making a holistic evidence-based, data-driven, clinical diagnosis. • To improve the return on investment for their shareholders, a healthcare manufacturer needs to forecast the demand for their product subject to environmental, demographic, economic, and bio-social sentiment data (Big Data). The organization’s data-analytics team is tasked with developing a protocol that identifies, aggregates, harmonizes, models and analyzes these heterogeneous data elements to generate a trend forecast. This system needs to provide an automated, adaptive, scalable, and reliable prediction of the optimal investment, e.g., R&D allocation, that maximizes the company’s bottom line. A reader that complete a course of study using this textbook will be able to ingest the observed structured and unstructured data, mathematically represent the data as a computable object, apply appropriate model-based and model-free prediction techniques. The results of these techniques may be used to forecast the expected relation between the company’s investment, product supply, general demand of healthcare (providers and patients), and estimate the return on initial investments.