Misalignment of Stakeholder Incentives in the Opioid Crisis.

The current opioid epidemic has killed more than 446,000 Americans over the past two decades. Despite the magnitude of the crisis, little is known to what degree the misalignment of incentives among stakeholders due to competing interests has contributed to the current situation. In this study, we explore evidence in the literature for the working hypothesis that misalignment rooted in the cost, quality, or access to care can be a significant contributor to the opioid epidemic. The review identified several problems that can contribute to incentive misalignment by compromising the triple aims (cost, quality, and access) in this epidemic. Some of these issues include the inefficacy of conventional payment mechanisms in providing incentives for providers, practice guidelines in pain management that are not easily implementable across different medical specialties, barriers in adopting multi-modal pain management strategies, low capacity of providers/treatments to address opioid/substance use disorders, the complexity of addressing the co-occurrence of chronic pain and opioid use disorders, and patients' non-adherence to opioid substitution treatments. In discussing these issues, we also shed light on factors that can facilitate the alignment of incentives among stakeholders to effectively address the current crisis.

Nurse-Reported Bullying and Documented Adverse Patient Events: An Exploratory Study in a US Hospital.

BACKGROUND: Negative nurse work environments have been associated with nurse bullying and poor nurse health. However, few studies have examined the influence of nurse bullying on actual patient outcomes. PURPOSE: The purpose of the study was to examine the association between nurse-reported bullying and documented nursing-sensitive patient outcomes. METHODS: Nurses (n = 432) in a large US hospital responded to a survey on workplace bullying. Unit-level data for 5 adverse patient events and nurse staffing were acquired from the National Database of Nursing Quality Indicators. Generalized linear models were used to examine the association between bullying and adverse patient events. A Bayesian regression analysis was used to confirm the findings. RESULTS: After controlling for nurse staffing and qualification, nurse-reported bullying was significantly associated with the incidence of central-line-associated bloodstream infections (P < .001). CONCLUSIONS: Interventions to address bullying, a malleable aspect of the nurse practice environment, may help to reduce adverse patient events.

A Bayesian analysis of longitudinal farm surveys in Central Malawi reveals yield determinants and site-specific management strategies.

Understanding the challenges to increasing maize productivity in sub-Saharan Africa, especially agronomic factors that reduce on-farm crop yield, has important implications for policies to reduce national and global food insecurity. Previous research on the maize yield gap has tended to emphasize the size of the gap (theoretical vs. achievable yields), rather than what determines maize yield in specific contexts. As a result, there is insufficient evidence on the key agronomic and environmental factors that influence maize yield in a smallholder farm environment. In this study, we implemented a Bayesian analysis with plot-level longitudinal household survey data covering 1,197 plots and 320 farms in Central Malawi. Households were interviewed and monitored three times per year, in 2015 and 2016, to document farmer management practices and seasonal rainfall, and direct measurements were taken of plant and soil characteristics to quantify impact on plot-level maize yield stability. The results revealed a high positive association between a leaf chlorophyll indicator and maize yield, with significance levels exceeding 95% Bayesian credibility at all sites and a regression coefficient posterior mean from 28% to 42% on a relative scale. A parasitic weed, Striga asiatica, was the variable most consistently negatively associated with maize yield, exceeding 95% credibility in most cases, of high intensity, with regression means ranging from 23% to 38% on a relative scale. The influence of rainfall, either directly or indirectly, varied by site and season. We conclude that the factors preventing Striga infestation and enhancing nitrogen fertility will lead to higher maize yield in Malawi. To improve plant nitrogen status, fertilizer was effective at higher productivity sites, whereas soil carbon and organic inputs were important at marginal sites. Uniquely, a Bayesian approach allowed differentiation of response by site for a relatively modest sample size study (given the complexity of farm environments and management practices). Considering the biophysical constraints, our findings highlight management strategies for crop yields, and point towards area-specific recommendations for nitrogen management and crop yield.

Neutron Drip Line in the Ca Region from Bayesian Model Averaging.

The region of heavy calcium isotopes forms the frontier of experimental and theoretical nuclear structure research where the basic concepts of nuclear physics are put to stringent test. The recent discovery of the extremely neutron-rich nuclei around ^{60}Ca O. B. Tarasov et al. [Phys. Rev. Lett. 121, 022501 (2018)10.1103/PhysRevLett.121.022501] and the experimental determination of masses for ^{55-57}Ca S. Michimasa et al. [Phys. Rev. Lett. 121, 022506 (2018)10.1103/PhysRevLett.121.022506] provide unique information about the binding energy surface in this region. To assess the impact of these experimental discoveries on the nuclear landscape's extent, we use global mass models and statistical machine learning to make predictions, with quantified levels of certainty, for bound nuclides between Si and Ti. Using a Bayesian model averaging analysis based on Gaussian-process-based extrapolations we introduce the posterior probability p_{ex} for each nucleus to be bound to neutron emission. We find that extrapolations for drip-line locations, at which the nuclear binding ends, are consistent across the global mass models used, in spite of significant variations between their raw predictions. In particular, considering the current experimental information and current global mass models, we predict that ^{68}Ca has an average posterior probability p_{ex}≈76% to be bound to two-neutron emission while the nucleus ^{61}Ca is likely to decay by emitting a neutron (p_{ex}≈46%).