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 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.
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.
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.
PurposeThis research aimed at developing the Quality 4.0 transition framework for Tanzanian manufacturing industries.Design/methodology/approachThe survey method was used in this study to gather ...practitioners' perspectives. The approach included open-ended and closed-ended structured questionnaires to assess respondents' perceptions of Quality 4.0 awareness and manufacturers' readiness to transit to Quality 4.0. The study's objective was to adopt non-probability and purposive sampling strategies. The study focused on fifteen Tanzanian manufacturing industries. The data were analysed qualitatively and quantitatively using MAXQADA 2020 and Minitab 20 software packages, respectively.FindingsThe study demonstrated a high level of awareness of Quality 4.0 among Tanzanian manufacturing industries (i.e. 100% in Quality 4.0 traditional attributes and 53% in Quality 4.0 modern attributes). Individuals acquire knowledge in various ways, including through quality training, work experience, self-reading and Internet surfing. The result also revealed that most manufacturing industries in Tanzania use Quality 3.0 or a lower approach to manage quality. However, Tanzanian manufacturing industries are ready to embrace Quality 4.0 since practitioners are aware of the concepts and could see benefits such as customer satisfaction, product improvement, process and continuous improvement, waste reduction and decision support when using the Quality 4.0 approach. The challenges hindering Quality 4.0 adoption in Tanzania include reliable electricity, high-speed Internet and infrastructure inadequacy to support the adoption, skilled workforces familiar with Quality 4.0-enabled technologies and a financial set-up to support technology investment. Moreover, the study developed a transition framework for an organisation to transition from traditional quality approaches such as quality control, quality assurance and total quality management to Quality 4.0, a modern quality approach aligned with the fourth industrial revolution era.Research limitations/implicationsThe current study solely looked at manufacturing industries, leaving other medical, service, mining and construction sectors. Furthermore, no focus was laid on the study's Quality 4.0 implementation frameworks.Originality/valueThis is probably the first Quality 4.0 transition framework for Tanzanian manufacturing industries, perhaps with other developing countries.
In the recent times, water quality of most of the rivers in India has been steadily degrading due to increasing numbers of point and non-point sources of pollution. The tremendous increase in ...population, rapid urbanization, change in irrigation patterns, and unplanned growth of industries without proper enforcement of environmental standards are some of the major causes for poor quality of river water. In addition, unpredictable and scanty rainfall is resulting in uncertain natural stream flow which further leads to uncertainty in assessing and predicting the quality of river water. This paper deals with the assessment of the overall status of water quality of a river by developing a fuzzy-based water quality evaluation system. The quality of water needed for different beneficial uses is based on the value of various parameters. Since the quality attributes of the parameters are fuzzy in nature, they have been described by the linguistic variables. The water quality index of each specific site is then calculated by aggregating the attributes with respect to their degree of importance, which is also expressed in the form of linguistic terms. Finally, a case study of the river Yamuna has been carried out to evaluate the fuzzy comprehensive water quality index (FCWQI). In this study, the FCWQI has been determined only for the use of water for drinking purposes though this model can be applied for other uses as well. The FCWQI developed herein is based on an integrated approach, which clearly describes the overall state of the water quality by a single rational number. Spatial and parametric sensitivity of the FCWQI model of the river basin is also determined using GIS-based geographically weighted regression technique. The methodology suggests a novel way of introducing parametric sensitivity in defining water quality indices used for surface water quality assessment.