During the past forty years, thousands of studies have been carried out on the subject of happiness. Some have explored the levels of happiness or dissatisfaction associated with typical daily ...activities, such as working, seeing friends, or doing household chores. Others have tried to determine the extent to which income, family, religion, and other factors are associated with the satisfaction people feel about their lives. The Gallup organization has begun conducting global surveys of happiness, and several countries are considering publishing periodic reports on the growth or decline of happiness among their people. One nation, tiny Bhutan, has actually made "Gross National Happiness" the central aim of its domestic policy. How might happiness research affect government policy in the United States--and beyond? In The Politics of Happiness, former Harvard president Derek Bok examines how governments could use the rapidly growing research data on what makes people happy--in a variety of policy areas to increase well-being and improve the quality of life for all their citizens.
BACKGROUND Quality improvement (QI) efforts have become widespread in healthcare, however there is significant variability in their success. Differences in context are thought to be responsible for ...some of the variability seen.
To develop a conceptual model that can be used by organisations and QI researchers to understand and optimise contextual factors affecting the success of a QI project.
10 QI experts were provided with the results of a systematic literature review and then participated in two rounds of opinion gathering to identify and define important contextual factors. The experts subsequently met in person to identify relationships among factors and to begin to build the model.
The Model for Understanding Success in Quality (MUSIQ) is organised based on the level of the healthcare system and identifies 25 contextual factors likely to influence QI success. Contextual factors within microsystems and those related to the QI team are hypothesised to directly shape QI success, whereas factors within the organisation and external environment are believed to influence success indirectly.
The MUSIQ framework has the potential to guide the application of QI methods in healthcare and focus research. The specificity of MUSIQ and the explicit delineation of relationships among factors allows a deeper understanding of the mechanism of action by which context influences QI success. MUSIQ also provides a foundation to support further studies to test and refine the theory and advance the field of QI science.
The primary reference for the modeling of hydrodynamics and water quality in rivers, lake, estuaries, coastal waters, and wetlands This comprehensive text perfectly illustrates the principles, basic ...processes, mathematical descriptions, case studies, and practical applications associated with surface waters. It focuses on solving practical problems in rivers, lakes, estuaries, coastal waters, and wetlands. Most of the theories and technical approaches presented within have been implemented in mathematical models and applied to solve practical problems. Throughout the book, case studies are presented to demonstrate how the basic theories and technical approaches are implemented into models, and how these models are applied to solve practical environmental/water resources problems. This new edition of Hydrodynamics and Water Quality: Modeling Rivers, Lakes, and Estuaries has been updated with more than 40% new information. It features several new chapters, including one devoted to shallow water processes in wetlands as well as another focused on extreme value theory and environmental risk analysis. It is also supplemented with a new website that provides files needed for sample applications, such as source codes, executable codes, input files, output files, model manuals, reports, technical notes, and utility programs. This new edition of the book: * Includes more than 120 new/updated figures and 450 references * Covers state-of-the-art hydrodynamics, sediment transport, toxics fate and transport, and water quality in surface waters * Provides essential and updated information on mathematical models * Focuses on how to solve practical problems in surface waters—presenting basic theories and technical approaches so that mathematical models can be understood and applied to simulate processes in surface waters Hailed as "a great addition to any university library" by the Journal of the American Water Resources Association (July 2009), Hydrodynamics and Water Quality, Second Edition is an essential reference for practicing engineers, scientists, and water resource managers worldwide.
Seeking Value Sowers, Wesley E; Ranz, Jules M; Psychiatry, Group for the Advancement of
2020, 2020-11-13
eBook
This comprehensive volume examines the myriad factors that have led to the current state of health care in the United States -- starting with an analysis of the meaning and history of value ...measurement -- but it does not stop there. It offers a holistic vision for health care reform, one in which psychiatric professionals play a pivotal role.
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.
The topics of visual and audio quality assessment (QA) have been widely researched for decades, yet nearly all of this prior work has focused only on single-mode visual or audio signals. However, ...visual signals rarely are presented without accompanying audio, including heavy-bandwidth video streaming applications. Moreover, the distortions that may separately (or conjointly) afflict the visual and audio signals collectively shape user-perceived quality of experience (QoE). This motivated us to conduct a subjective study of audio and video (A/V) quality, which we then used to compare and develop A/V quality measurement models and algorithms. The new LIVE-SJTU Audio and Video Quality Assessment (A/V-QA) Database includes 336 A/V sequences that were generated from 14 original source contents by applying 24 different A/V distortion combinations on them. We then conducted a subjective A/V quality perception study on the database towards attaining a better understanding of how humans perceive the overall combined quality of A/V signals. We also designed four different families of objective A/V quality prediction models, using a multimodal fusion strategy. The different types of A/V quality models differ in both the unimodal audio and video quality prediction models comprising the direct signal measurements and in the way that the two perceptual signal modes are combined. The objective models are built using both existing state-of-the-art audio and video quality prediction models and some new prediction models, as well as quality-predictive features delivered by a deep neural network. The methods of fusing audio and video quality predictions that are considered include simple product combinations as well as learned mappings. Using the new subjective A/V database as a tool, we validated and tested all of the objective A/V quality prediction models. We will make the database publicly available to facilitate further research.
When rain falls on the city, it creates urban runoff that cause flooding, erosion, and water pollution. Municipal engineers manage a complex network of technical and natural systems to treat and ...remove these temporary water flows from cities as quickly as possible. Urban runoff is frequently discussed in terms of technical expertise and environmental management, but it encompasses a multitude of such nontechnical issues as land use, quality of life, governance, aesthetics, and community identity, and is central to the larger debates on creating more sustainable and livable cities. In this book, Andrew Karvonen uses urban runoff as a lens to view the relationships among nature, technology, and society. Offering theoretical insights from urban environmental history, human geography, landscape and ecological planning, and science and technology studies as well as empirical evidence from case studies, Karvonen proposes a new relational politics of urban nature.After describing the evolution of urban runoff practices, Karvonen analyzes the urban runoff activities in Austin and Seattle--two cities known for their highly contested public debates over runoff issues and exemplary stormwater management practices. The Austin case study highlights the tensions among urban development, property rights, land use planning, and citizen activism; the Seattle case study explores the city's long-standing reputation for being in harmony with nature. Drawing on these accounts, Karvonen suggests a new relational politics of urban nature that is situated, inclusive, and action-oriented to address the tensions among nature, technology, and society.
Since the publication of Standards for QUality Improvement Reporting Excellence (SQUIRE 1.0) guidelines in 2008, the science of the field has advanced considerably. In this manuscript, we describe ...the development of SQUIRE 2.0 and its key components. We undertook the revision between 2012 and 2015 using (1) semistructured interviews and focus groups to evaluate SQUIRE 1.0 plus feedback from an international steering group, (2) two face-to-face consensus meetings to develop interim drafts and (3) pilot testing with authors and a public comment period. SQUIRE 2.0 emphasises the reporting of three key components of systematic efforts to improve the quality, value and safety of healthcare: the use of formal and informal theory in planning, implementing and evaluating improvement work; the context in which the work is done and the study of the intervention(s). SQUIRE 2.0 is intended for reporting the range of methods used to improve healthcare, recognising that they can be complex and multidimensional. It provides common ground to share these discoveries in the scholarly literature (http://www.squire-statement.org).
In 2018, three independent reports were published, emphasizing the need for attention to, and improvements in, quality of care to achieve effective universal health coverage. A key aspect of high ...quality health care and health systems is that they are person-centred, a characteristic that is at the same time intrinsically important (all individuals have the right to be treated with dignity and respect) and instrumentally important (person-centred care is associated with improved health-care utilization and health outcomes). Following calls to make 2019 a year of action, we provide guidance to policy-makers, researchers and implementers on how they can take on the task of measuring person-centred care. Theoretically, measures of person-centred care allow quality improvement efforts to be evaluated and ensure that health systems are accountable to those they aim to serve. However, in practice, the utility of these measures is limited by lack of clarity and precision in designing and by using measures for different aspects of person-centeredness. We discuss the distinction between two broad categories of measures of patient-centred care: patient experience and patient satisfaction. We frame our discussion of these measures around three key questions: (i) how will the results of this measure be used?; (ii) how will patient subjectivity be accounted for?; and (iii) is this measure validated or tested? By addressing these issues during the design phase, researchers will increase the usability of their measures.
The American College of Surgeons, National Surgical Quality Improvement Program (ACS NSQIP) surgical quality feedback models are recalibrated every 6 months, and each hospital is given risk-adjusted, ...hierarchical model, odds ratios that permit comparison to an estimated average NSQIP hospital at a particular point in time. This approach is appropriate for "relative" benchmarking, and for targeting quality improvement efforts, but does not permit evaluation of hospital or program-wide changes in quality over time. We report on long-term improvement in surgical outcomes associated with participation in ACS NSQIP.
ACS NSQIP data (2006-2013) were used to create prediction models for mortality, morbidity (any of several distinct adverse outcomes), and surgical site infection (SSI). For each model, for each hospital, and for year of first participation (hospital cohort), hierarchical model observed/expected (O/E) ratios were computed. The primary performance metric was the within-hospital trend in logged O/E ratios over time (slope) for mortality, morbidity, and SSI.
Hospital-averaged log O/E ratio slopes were generally negative, indicating improving performance over time. For all hospitals, 62%, 70%, and 65% of hospitals had negative slopes for mortality, morbidity, and any SSI, respectively. For hospitals currently in the program for at least 3 years, 69%, 79%, and 71% showed improvement in mortality, morbidity, and SSI, respectively. For these hospitals, we estimate 0.8%, 3.1%, and 2.6% annual reductions (with respect to prior year's rates) for mortality, morbidity, and SSI, respectively.
Participation in ACS NSQIP is associated with reductions in adverse events after surgery. The magnitude of quality improvement increases with time in the program.
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