Comparison of Georgia's Tobacco and Alcoholic Beverage Excise Tax Rates - Brief

This brief provides a detailed comparison of excise tax rates across the United States. FRC Brief 19

Problem-driven scenario generation: an analytical approach for stochastic programs with tail risk measure

Scenario generation is the construction of a discrete random vector to represent parameters of uncertain values in a stochastic program. Most approaches to scenario generation are distribution-driven, that is, they attempt to construct a random vector which captures well in a probabilistic sense the uncertainty. On the other hand, a problem-driven approach may be able to exploit the structure of a problem to provide a more concise representation of the uncertainty. In this paper we propose an analytic approach to problem-driven scenario generation. This approach applies to stochastic programs where a tail risk measure, such as conditional value-at-risk, is applied to a loss function. Since tail risk measures only depend on the upper tail of a distribution, standard methods of scenario generation, which typically spread their scenarios evenly across the support of the random vector, struggle to adequately represent tail risk. Our scenario generation approach works by targeting the construction of scenarios in areas of the distribution corresponding to the tails of the loss distributions. We provide conditions under which our approach is consistent with sampling, and as proof-of-concept demonstrate how our approach could be applied to two classes of problem, namely network design and portfolio selection. Numerical tests on the portfolio selection problem demonstrate that our approach yields better and more stable solutions compared to standard Monte Carlo sampling

Problem-driven scenario generation:an analytical approach for stochastic programs with tail risk measure

Scenario generation is the construction of a discrete random vector to represent parameters of uncertain values in a stochastic program. Most approaches to scenario generation are distribution-driven, that is, they attempt to construct a random vector which captures well in a probabilistic sense the uncertainty. On the other hand, a problem-driven approach may be able to exploit the structure of a problem to provide a more concise representation of the uncertainty. There have been only a few problem-driven approaches proposed, and these have been heuristic in nature. In this paper we propose what is, as far as we are aware, the first analytic approach to problem-driven scenario generation. This approach applies to stochastic programs with a tail risk measure, such as conditional value-at-risk. Since tail risk measures only depend on the upper tail of a distribution, standard methods of scenario generation, which typically spread there scenarios evenly across the support of the solution, struggle to adequately represent tail risk well

Does the professional and working context of United Kingdom clinicians predict if they use practices to support patients with long term conditions to self manage?

INTRODUCTION: Our study examines how the professional and employment context may influence clinicians' practice self management support for patients with long term conditions (LTC). MATERIAL AND METHODS: We surveyed clinicians working with patients with depression, chronic obstructive pulmonary disorder (COPD), chronic musculo skeletal pain and diabetes. RESULTS: Clinicians most frequently endorsed items on a scale concerned with patient centeredness, and less frequently endorsed items concerned with clinical and organizational self management support. The most important factors predicting these latter activities were the intensity of working experience with patients with LTC and attending professional training addressing the principles and practice of self management support. Practicing patient centeredness was endorsed by nearly all respondents, and so was not sensitive to variation on work variables. CONCLUSIONS: The interaction of training and intensity of work with patients with LTC seems to have the most powerful effect on undertaking clinical and organizational self management support practices. To facilitate clinicians' practice of self management support for patients with LTC it is very important to provide relevant professional training and to build specialized patient care teams with professionals having complimentary skills

Is individual employment law displacing the role of trade unions?

peer-reviewedTrade unions have experienced significant turbulence over the past three decades. In the UK and Ireland, a key change has been a substantial increase in the individual rights-based employment legislation, raising important questions about its impact on trade unions. Based on a survey and interviews with union officials in Ireland, we examine whether individual employment law acts to undermine or enhance the role of trade unions and whether trade union officials use employment law to achieve change in the workplace and to mobilise workers. We find that while unions believe in the superiority of collective bargaining to pursue individual rights, and consider the law as having an individualising effect, they also recognise its benefits in the current environment. Given the legal restrictions on collective action in individual disputes, union officials believe that employment law can be used to support and protect vulnerable groups of workers. The increasing resort to individual employment rights in Ireland is contrasted with an alternative system in Sweden which has a strong collectivist ethos. We conclude that the dilemmas faced by unions regarding the pursuit of rights are symptoms of Ireland's weak statutory framework.ACCEPTEDpeer-reviewe

The views of health guideline developers on the use of automation in health evidence synthesis

BACKGROUND: The increasingly rapid rate of evidence publication has made it difficult for evidence synthesis-systematic reviews and health guidelines-to be continually kept up to date. One proposed solution for this is the use of automation in health evidence synthesis. Guideline developers are key gatekeepers in the acceptance and use of evidence, and therefore, their opinions on the potential use of automation are crucial. METHODS: The objective of this study was to analyze the attitudes of guideline developers towards the use of automation in health evidence synthesis. The Diffusion of Innovations framework was chosen as an initial analytical framework because it encapsulates some of the core issues which are thought to affect the adoption of new innovations in practice. This well-established theory posits five dimensions which affect the adoption of novel technologies: Relative Advantage, Compatibility, Complexity, Trialability, and Observability. Eighteen interviews were conducted with individuals who were currently working, or had previously worked, in guideline development. After transcription, a multiphase mixed deductive and grounded approach was used to analyze the data. First, transcripts were coded with a deductive approach using Rogers' Diffusion of Innovation as the top-level themes. Second, sub-themes within the framework were identified using a grounded approach. RESULTS: Participants were consistently most concerned with the extent to which an innovation is in line with current values and practices (i.e., Compatibility in the Diffusion of Innovations framework). Participants were also concerned with Relative Advantage and Observability, which were discussed in approximately equal amounts. For the latter, participants expressed a desire for transparency in the methodology of automation software. Participants were noticeably less interested in Complexity and Trialability, which were discussed infrequently. These results were reasonably consistent across all participants. CONCLUSIONS: If machine learning and other automation technologies are to be used more widely and to their full potential in systematic reviews and guideline development, it is crucial to ensure new technologies are in line with current values and practice. It will also be important to maximize the transparency of the methods of these technologies to address the concerns of guideline developers

An evaluation of a self-management program for patients with long-term conditions

Objective: To evaluate a group-based self-management program (SMP) delivered as part of a quality improvement program, Co-Creating Health, for patients living with one of four long-term conditions (LTCs): chronic obstructive pulmonary disease, depression, diabetes, and musculoskeletal pain. Methods: The 7 week SMP was co-delivered by lay and health professional tutors. Patients completed self-reported outcome measures at pre-course and 6 months follow-up. Results: 486 patients completed (attended ≥5 sessions) the SMP and returned pre-course and 6 months follow up data. Patients reported significant improvements in patient activation (ES 0.65, pp= 0.04), and health status (ES 0.33, pppp values from pp= 0.028). Conclusion: Attending the SMP led to improvements in a range of outcomes. Improvement in patient activation is important, as activated patients are more likely to perform self-care activities. Practice implications: Co-delivered SMPs provide meaningful improvements in activation for >50 of those who complete and are a useful addition to self-management support provision

Standardized Patient Encounters Periodic Versus Postencounter Evaluation of Nontechnical Clinical Performance

Introduction: Standardized patients are a beneficial component of modern healthcare education and training, but few studies have explored cognitive factors potentially impacting clinical skills assessment during standardized patient encounters. This study examined the impact of a periodic (vs. traditional postencounter) evaluation approach and the appearance of critical verbal and nonverbal behaviors throughout a standardized patient encounter on scoring accuracy in a video-based scenario. Methods: Forty-nine standardized patients scored either periodically or at only 1 point in time (postencounter) a healthcare provider\u27s verbal and nonverbal clinical performance during a videotaped standardized patient encounter. The healthcare provider portrayed in this study was actually a standardized patient delivering carefully scripted verbal and nonverbal behaviors in their portrayal of an actual physician. The encounter itself was subdivided into 3 distinct segments for the purpose of supporting periodic evaluation, with the expectation that both verbal and nonverbal cues occurring in the middle segment would be more challenging to accurately report for participants in the postscenario evaluation group as a result of working memory decay. Results: Periodic evaluators correctly identified a significantly greater number of critical verbal cues midscenario than postencounter evaluators (P \u3c 0.01) and correctly identified a significantly greater number of critical nonverbal cues than their postscenario counterparts across all 3 scenario segments (P \u3c 0.001). Further, postscenario evaluations exhibited a performance decrement in terms of midscenario correct identifications that periodic evaluators did not (P \u3c 0.01). Also, periodic evaluators exhibited fewer verbal cue false-positives during the first segment of the scenario than postscenario evaluators (P \u3c 0.001), but this effect did not extend to other segments regardless of the cue type (ie, verbal or nonverbal). Discussion: Pausing lengthier standardized patient encounters periodically to allow for more frequent scoring may result in better reporting accuracy for certain clinical behavioral cues. This could enable educators to provide more specific formative feedback to individual learners at the session\u27s conclusion. The most effective encounter design will ultimately depend on the specific goals and training objectives of the exercise itself