Data Driven Management In The Health Care Sector
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Healthcare Service Management
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Author : Li Tao
language : en
Publisher: Springer
Release Date : 2019-05-08
Healthcare Service Management written by Li Tao and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-08 with Computers categories.
Healthcare service systems are of profound importance in promoting the public health and wellness of people. This book introduces a data-driven complex systems modeling approach (D2CSM) to systematically understand and improve the essence of healthcare service systems. In particular, this data-driven approach provides new perspectives on health service performance by unveiling the causes for service disparity, such as spatio-temporal variations in wait times across different hospitals. The approach integrates four methods -- Structural Equation Modeling (SEM)-based analysis; integrated projection; service management strategy design and evaluation; and behavior-based autonomy-oriented modeling -- to address respective challenges encountered in performing data analytics and modeling studies on healthcare services. The thrust and uniqueness of this approach lies in the following aspects: Ability to explore underlying complex relationships between observed or latent impact factors and service performance. Ability to predict the changes and demonstrate the corresponding dynamics of service utilization and service performance. Ability to strategically manage service resources with the adaptation of unpredictable patient arrivals. Ability to figure out the working mechanisms that account for certain spatio-temporal patterns of service utilization and performance. To show the practical effectiveness of the proposed systematic approach, this book provides a series of pilot studies within the context of cardiac care in Ontario, Canada. The exemplified studies have unveiled some novel findings, e.g., (1) service accessibility and education may relieve the pressure of population size on service utilization; (2) functionally coupled units may have a certain cross-unit wait-time relationship potentially because of a delay cascade phenomena; (3) strategically allocating time blocks in operating rooms (ORs) based on a feedback mechanism may benefit OR utilization; (4) patients’ and hospitals’ autonomous behavior, and their interactions via wait times may bear the responsible for the emergence of spatio-temporal patterns observed in the real-world cardiac care system. Furthermore, this book presents an intelligent healthcare decision support (iHDS) system, an integrated architecture for implementing the data-driven complex systems modeling approach to developing, analyzing, investigating, supporting and advising healthcare related decisions. In summary, this book provides a data-driven systematic approach for addressing practical decision-support problems confronted in healthcare service management. This approach will provide policy makers, researchers, and practitioners with a practically useful way for examining service utilization and service performance in various ``what-if" scenarios, inspiring the design of effectiveness resource-allocation strategies, and deepening the understanding of the nature of complex healthcare service systems.
Data Driven Healthcare
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Author : Laura B. Madsen
language : en
Publisher: John Wiley & Sons
Release Date : 2014-10-27
Data Driven Healthcare written by Laura B. Madsen 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 2014-10-27 with Business & Economics categories.
Healthcare is changing, and data is the catalyst Data is taking over in a powerful way, and it's revolutionizing the healthcare industry. You have more data available than ever before, and applying the right analytics can spur growth. Benefits extend to patients, providers, and board members, and the technology can make centralized patient management a reality. Despite the potential for growth, many in the industry and government are questioning the value of data in health care, wondering if it's worth the investment. Data-Driven Healthcare: How Analytics and BI are Transforming the Industry tackles the issue and proves why BI is not only worth it, but necessary for industry advancement. Healthcare BI guru Laura Madsen challenges the notion that data have little value in healthcare, and shows how BI can ease regulatory reporting pressures and streamline the entire system as it evolves. Madsen illustrates how a data-driven organization is created, and how it can transform the industry. Learn why BI is a boon to providers Create powerful infographics to communicate data more effectively Find out how Big Data has transformed other industries, and how it applies to healthcare Data-Driven Healthcare: How Analytics and BI are Transforming the Industry provides tables, checklists, and forms that allow you to take immediate action in implementing BI in your organization. You can't afford to be behind the curve. The industry is moving on, with or without you. Data-Driven Healthcare: How Analytics and BI are Transforming the Industry is your guide to utilizing data to advance your operation in an industry where data-fueled growth will be the new norm.
Data Driven Management In The Health Care Sector
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Author :
language : en
Publisher:
Release Date : 2018
Data Driven Management In The Health Care Sector written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Data Driven Technology For Engineering Systems Health Management
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Author : Gang Niu
language : en
Publisher: Springer
Release Date : 2016-07-27
Data Driven Technology For Engineering Systems Health Management written by Gang Niu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-27 with Technology & Engineering categories.
This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the data-driven methodology for feature construction, as well as feature-based fault diagnosis and prognosis. The book includes a wealth of illustrations and tables to help explain the algorithms, as well as practical examples showing how to use this tool to solve situations for which analytic solutions are poorly suited. It equips readers to apply the concepts discussed in order to analyze and solve a variety of problems in PHM system design, feature construction, fault diagnosis and prognosis.
Data Driven Decision Making Under Uncertainty With Applications In Healthcare And Energy Management
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Author : Saeed Ghodsi
language : en
Publisher:
Release Date : 2022
Data Driven Decision Making Under Uncertainty With Applications In Healthcare And Energy Management written by Saeed Ghodsi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Decision-making under uncertainty has been studied for a long time by the operations management research community. In the past, uncertainty models were often derived based on domain knowledge. However, the availability of vast amounts of data in the recent years has shifted interests towards data-driven approaches for uncertainty quantification. More specifically, statistical models are employed within this framework for characterizing the uncertain components of a stochastic optimization problem based on historical data. In this dissertation, we focus on applications of data-driven decision-making under uncertainty in the healthcare and energy management sectors. The first part of our work provides a mathematical framework for efficient call assignment under Direct Load Control (DLC) contracts (i.e. an incentive-based demand-response program that is widely used by utility firms for balancing the supply and demand of electricity during peak times). Specifically, we employ a model for forecasting energy consumption and develop a large-scale integer stochastic dynamic optimization problem. We then propose a novel hierarchical approximation scheme for efficient execution of the contracts. We evaluate the quality of our proposed approach using real-world data obtained from California Independent System Operator (CAISO), which is the umbrella organization of utility firms in California. A large utility firm in California has implemented our model and informed us that they have experienced a 4\% additional r duction in their cost. Following a similar predict-then-optimize methodological framework, the second part of this dissertation studies data-driven healthcare intervention planning. Specifically, we develop a continuous-time latent-space Markovian model for describing disease progression based on discrete-time irregularly-spaced observations. Our model is capable of incorporating the effect of interventions on progression of disease. We discuss the computational challenges of parameter estimation for this model and present a novel efficient estimation approach based on the Expectation-Maximization (EM) algorithm. A population-level optimization model for intervention planning in the behavioral healthcare sector is then developed using the fitted disease progression model. Afterward, we present an extension of the model, which is more appropriate for medical healthcare domains such as cancer maintenance therapy, and formulate an EM algorithm for estimating the model parameters. Finally, we develop an individual-level intervention planning problem based on the patient's historical data using the estimated model.
Data Driven Quality Improvement And Sustainability In Health Care
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Author : Patricia L. Thomas, PhD, RN, FAAN, FNAP, FACHE, NEA-BC, ACNS-BC, CNL
language : en
Publisher: Springer Publishing Company
Release Date : 2020-11-19
Data Driven Quality Improvement And Sustainability In Health Care written by Patricia L. Thomas, PhD, RN, FAAN, FNAP, FACHE, NEA-BC, ACNS-BC, CNL and has been published by Springer Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-19 with Medical categories.
Data-Driven Quality Improvement and Sustainability in Health Care: An Interprofessional Approach provides nurse leaders and healthcare administrators of all disciplines with a solid understanding of data and how to leverage data to improve outcomes, fuel innovation, and achieve sustained results. It sets the stage by examining the current state of the healthcare landscape; new imperatives to meet policy, regulatory, and consumer demands; and the role of data in administrative and clinical decision-making. It helps the professional identify the methods and tools that support thoughtful and thorough data analysis and offers practical application of data-driven processes that determine performance in healthcare operations, value- and performance-based contracts, and risk contracts. Misuse or inconsistent use of data leads to ineffective and errant decision-making. This text highlights common barriers and pitfalls related to data use and provide strategies for how to avoid these pitfalls. In addition, chapters feature key points, reflection questions, and real-life interprofessional case exemplars to help the professional draw distinctions and apply principles to their own practice. Key Features: Provides nurse leaders and other healthcare administrators with an understanding of the role of data in the current healthcare landscape and how to leverage data to drive innovative and sustainable change Offers frameworks, methodology, and tools to support quality improvement measures Demonstrates the application of data and how it shapes quality and safety initiatives through real-life case exemplars Highlights common barriers and pitfalls related to data use and provide strategies for how to avoid these pitfalls
Data Driven Analytics For Clinical Decision Making Healthcare Operations Management And Public Health Policy
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Author : Michael Charles Zinzan Fairley
language : en
Publisher:
Release Date : 2021
Data Driven Analytics For Clinical Decision Making Healthcare Operations Management And Public Health Policy written by Michael Charles Zinzan Fairley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
Health care costs in the United States exceed $3.5 trillion annually, with between $760 billion and $935 billion considered waste. Data-driven analytics could reduce costs and provide higher quality care to patients by more efficiently allocating limited resources, just as analytics has done in other industries such as logistics, manufacturing and aviation. In this dissertation, I demonstrate three levels at which analytics provide value in health: clinical decision making, healthcare operations management and public health policy. Clinical decision making refers to decisions at the individual patient level: for example, determining which treatment to provide a patient or predicting an individual's risk of disease. Healthcare operations management refers to decisions about the system that delivers care to patients: for example, determining how to organize patient flow through a hospital or schedule procedures. Finally, public health policy refers to decisions about the overall health of a population: for example, determining how to control an infectious disease or distribute limited resources across different diseases.
Secondary Analysis Of Electronic Health Records
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Author : MIT Critical Data
language : en
Publisher: Springer
Release Date : 2016-09-09
Secondary Analysis Of Electronic Health Records written by MIT Critical Data and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-09 with Medical categories.
This book trains the next generation of scientists representing different disciplines to leverage the data generated during routine patient care. It formulates a more complete lexicon of evidence-based recommendations and support shared, ethical decision making by doctors with their patients. Diagnostic and therapeutic technologies continue to evolve rapidly, and both individual practitioners and clinical teams face increasingly complex ethical decisions. Unfortunately, the current state of medical knowledge does not provide the guidance to make the majority of clinical decisions on the basis of evidence. The present research infrastructure is inefficient and frequently produces unreliable results that cannot be replicated. Even randomized controlled trials (RCTs), the traditional gold standards of the research reliability hierarchy, are not without limitations. They can be costly, labor intensive, and slow, and can return results that are seldom generalizable to every patient population. Furthermore, many pertinent but unresolved clinical and medical systems issues do not seem to have attracted the interest of the research enterprise, which has come to focus instead on cellular and molecular investigations and single-agent (e.g., a drug or device) effects. For clinicians, the end result is a bit of a “data desert” when it comes to making decisions. The new research infrastructure proposed in this book will help the medical profession to make ethically sound and well informed decisions for their patients.
New Horizons For A Data Driven Economy
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Author : José María Cavanillas
language : en
Publisher: Springer
Release Date : 2016-04-04
New Horizons For A Data Driven Economy written by José María Cavanillas and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-04 with Computers categories.
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.
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.