Leveraging Data In Healthcare
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Leveraging Data In Healthcare
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Author : Rebecca Mendoza Saltiel Busch
language : en
Publisher: CRC Press
Release Date : 2017-07-12
Leveraging Data In Healthcare written by Rebecca Mendoza Saltiel Busch and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-12 with categories.
The healthcare industry is in a state of accelerated transition. The proliferation of data and its assimilation, access, use, and security are ever-increasing challenges. Finding ways to operationalize business and clinical data management in the face of government and market mandates is enough to keep most chief officers up at night! Leveraging Data in Healthcare: Best Practices for Controlling, Analyzing, and Using Data argues that the key to survival for any healthcare organization in today�s data-saturated market is to fundamentally redefine the roles of chief information executives�CIOs, CFOs, CMIOs, CTOs, CNIOs, CTOs and CDOs�from suppliers of data to drivers of data intelligence. This book presents best practices for controlling, analyzing, and using data. The elements of preparing an actionable data strategy are exemplified on subjects such as revenue integrity, revenue management, and patient engagement. Further, the book illustrates how to operationalize the electronic integration of health and financial data within patient financial services, information management services, and patient engagement activities. An integrated environment will activate a data-driven intelligent decision support infrastructure. The increasing impact of consumer engagement will continue to affect the organization�s bottom line. Success in this new world will need collaboration among the chiefs, users, and data creators.
Leveraging Data Science For Global Health
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Author : Leo Anthony Celi
language : en
Publisher: Springer Nature
Release Date : 2020-07-31
Leveraging Data Science For Global Health written by Leo Anthony Celi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-31 with Medical categories.
This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.
Integrating Social Care Into The Delivery Of Health Care
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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2020-01-30
Integrating Social Care Into The Delivery Of Health Care written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-30 with Medical categories.
Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation's Health was released in September 2019, before the World Health Organization declared COVID-19 a global pandemic in March 2020. Improving social conditions remains critical to improving health outcomes, and integrating social care into health care delivery is more relevant than ever in the context of the pandemic and increased strains placed on the U.S. health care system. The report and its related products ultimately aim to help improve health and health equity, during COVID-19 and beyond. The consistent and compelling evidence on how social determinants shape health has led to a growing recognition throughout the health care sector that improving health and health equity is likely to depend â€" at least in part â€" on mitigating adverse social determinants. This recognition has been bolstered by a shift in the health care sector towards value-based payment, which incentivizes improved health outcomes for persons and populations rather than service delivery alone. The combined result of these changes has been a growing emphasis on health care systems addressing patients' social risk factors and social needs with the aim of improving health outcomes. This may involve health care systems linking individual patients with government and community social services, but important questions need to be answered about when and how health care systems should integrate social care into their practices and what kinds of infrastructure are required to facilitate such activities. Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation's Health examines the potential for integrating services addressing social needs and the social determinants of health into the delivery of health care to achieve better health outcomes. This report assesses approaches to social care integration currently being taken by health care providers and systems, and new or emerging approaches and opportunities; current roles in such integration by different disciplines and organizations, and new or emerging roles and types of providers; and current and emerging efforts to design health care systems to improve the nation's health and reduce health inequities.
Leveraging Data In Healthcare
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Author : Rebecca Mendoza Saltiel Busch
language : en
Publisher: CRC Press
Release Date : 2017-07-27
Leveraging Data In Healthcare written by Rebecca Mendoza Saltiel Busch and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-27 with Business & Economics categories.
The healthcare industry is in a state of accelerated transition. The proliferation of data and its assimilation, access, use, and security are ever-increasing challenges. Finding ways to operationalize business and clinical data management in the face of government and market mandates is enough to keep most chief officers up at night!Leveraging Dat
Leveraging Biomedical And Healthcare Data
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Author : Firas Kobeissy
language : en
Publisher: Academic Press
Release Date : 2018-11-23
Leveraging Biomedical And Healthcare Data written by Firas Kobeissy and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-23 with Medical categories.
Leveraging Biomedical and Healthcare Data: Semantics, Analytics and Knowledge provides an overview of the approaches used in semantic systems biology, introduces novel areas of its application, and describes step-wise protocols for transforming heterogeneous data into useful knowledge that can influence healthcare and biomedical research. Given the astronomical increase in the number of published reports, papers, and datasets over the last few decades, the ability to curate this data has become a new field of biomedical and healthcare research. This book discusses big data text-based mining to better understand the molecular architecture of diseases and to guide health care decision. It will be a valuable resource for bioinformaticians and members of several areas of the biomedical field who are interested in understanding more about how to process and apply great amounts of data to improve their research. Includes at each section resource pages containing a list of available curated raw and processed data that can be used by researchers in the field Provides demonstrative and relevant examples that serve as a general tutorial Presents a list of algorithm names and computational tools available for basic and clinical researchers
Leveraging Data Science For Global Health
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Author : Leo Anthony Celi
language : en
Publisher: Springer
Release Date : 2020-09-18
Leveraging Data Science For Global Health written by Leo Anthony Celi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-18 with Medical categories.
This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure – and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources – including news media, social media, Google Trends, and Google Street View – can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.
Leveraging Data Analytics To Improve Outpatient Healthcare Operations
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Author : Michael Hu (Ph.D.)
language : en
Publisher:
Release Date : 2020
Leveraging Data Analytics To Improve Outpatient Healthcare Operations written by Michael Hu (Ph.D.) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Healthcare reform in the United States has received significant attention from the public, physicians, health administrators, and insurance payors. The important policy discussions surrounding healthcare reform have a wide-reaching impact, and often require quantitative data and analytics to support successful changes. This thesis studies a number of burning healthcare problems and offers actionable insights driven by data and analytics. In Chapter 2, we examine the effect of the EHR phenomenon and how it has fundamentally transformed physicians’ work. While these computer systems are designed in part to streamline workflows and increase employee efficiency, physician experiences are often the exact opposite. Instead of having more face-to-face time seeing their patients, physicians are forced to spend the majority of their time completing EHR tasks. In this chapter, we establish rigorous, quantitative methods for measuring and analyzing this problem to help health systems curb the exploding population of burned out physicians. In Chapter 3, we demonstrate how the methods established in Chapter 2 can also be used to predict physician workload, which may assist in the design of physician compensation models. While health systems are shifting away from fee-for-service payment schemes, alternative payment schemes often encounter significant implementation challenges. There are many open questions that need to be resolved before these new payment schemes can achieve widespread adoption. In this chapter, we address one such question, which involves how to properly risk adjust for different patient populations. We leverage the techniques from Chapter 2 to measure the workload imposed on physicians by individual patients. This enables us to subsequently develop a risk adjustment model that substantially outperforms existing risk adjustment methods in determining the physician workload associated with managing different patient populations. In Chapter 4, we examine the problem of relaxing hospital capacity. Many hospitals frequently operate close to full-capacity which poses serious safety concerns. Most attempted solutions in this space focus on inpatient interventions such as optimizing patient flow and surgery schedules. In contrast to this, we propose an approach based on changes in the longitudinal care delivered by ambulatory services, specifically for the treatment of heart failure patients. Lastly, in Chapter 5, we develop a new modeling framework for real-time appointment scheduling. While others have applied existing algorithms from online binpacking to solve this problem, our modeling framework leverages unique aspects of appointment scheduling to further optimize scheduling decisions and reduce resource requirements. In doing so, we demonstrate that our modeling framework generalizes the classical bin-packing framework thereby enabling a potentially larger number of problems to be studied using similar techniques.
Demystifying Big Data And Machine Learning For Healthcare
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Author : Prashant Natarajan
language : en
Publisher: CRC Press
Release Date : 2017-02-15
Demystifying Big Data And Machine Learning For Healthcare written by Prashant Natarajan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-15 with Medical categories.
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.
Transforming Healthcare With Big Data And Ai
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Author : Mingbo Gong
language : en
Publisher: IAP
Release Date : 2020-04-01
Transforming Healthcare With Big Data And Ai written by Mingbo Gong and has been published by IAP this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-01 with Computers categories.
Healthcare and technology are at a convergence point where significant changes are poised to take place. The vast and complex requirements of medical record keeping, coupled with stringent patient privacy laws, create an incredibly unwieldy maze of health data needs. While the past decade has seen giant leaps in AI, machine learning, wearable technologies, and data mining capacities that have enabled quantities of data to be accumulated, processed, and shared around the globe. Transforming Healthcare with Big Data and AI examines the crossroads of these two fields and looks to the future of leveraging advanced technologies and developing data ecosystems to the healthcare field. This book is the product of the Transforming Healthcare with Data conference, held at the University of Southern California. Many speakers and digital healthcare industry leaders contributed multidisciplinary expertise to chapters in this work. Authors’ backgrounds range from data scientists, healthcare experts, university professors, and digital healthcare entrepreneurs. If you have an understanding of data technologies and are interested in the future of Big Data and A.I. in healthcare, this book will provide a wealth of insights into the new landscape of healthcare.
Leveraging Real Time Patient Experience Data To Improve Healthcare Delivery
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Author : Mustafa Khanbhai
language : en
Publisher:
Release Date : 2023
Leveraging Real Time Patient Experience Data To Improve Healthcare Delivery written by Mustafa Khanbhai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.