Volume-based referral for cardiovascular procedures in the United States: a cross-sectional regression analysis

BACKGROUND: We sought to estimate the numbers of patients affected and deaths avoided by adopting the Leapfrog Group's recommended hospital procedure volume minimums for coronary artery bypass graft (CABG) surgery and percutaneous coronary intervention (PCI). In addition to hospital risk-adjusted mortality standards, the Leapfrog Group recommends annual hospital procedure minimums of 450 for CABG and 400 for PCI to reduce procedure-associated mortality. METHODS: We conducted a retrospective analysis of a national hospital discharge database to evaluate in-hospital mortality among patients who underwent PCI (n = 2,500,796) or CABG (n = 1,496,937) between 1998 and 2001. We calculated the number of patients treated at low volume hospitals and simulated the number of deaths potentially averted by moving all patients to high volume hospitals under best-case conditions (i.e., assuming the full volume-associated reduction in mortality and the capacity to move all patients to high volume hospitals with no related harms). RESULTS: Multivariate adjusted odds of in-hospital mortality were higher for patients treated in low volume hospitals compared with high volume hospitals for CABG (OR 1.16, 95% CI 1.10–1.24) and PCI (OR 1.12, 95% CI 1.05–1.20). A policy of hospital volume minimums would have required moving 143,687 patients for CABG and 87,661 patients for PCI from low volume to high volume hospitals annually and prevented an estimated 619 CABG deaths and 109 PCI deaths. Thus, preventing a single death would have required moving 232 CABG patients or 805 PCI patients from low volume to high volume hospitals. CONCLUSION: Recommended hospital CABG and PCI volume minimums would prevent 728 deaths annually in the United States, fewer than previously estimated. It is unclear whether a policy requiring the movement of large numbers of patients to avoid relatively few deaths is feasible or effective

Multistability and dynamic transitions of intracellular Min protein patterns

Cells owe their internal organization to self-organized protein patterns, which originate and adapt to growth and external stimuli via a process that is as complex as it is little understood. Here, we study the emergence, stability, and state transitions of multistable Min protein oscillation patterns in live Escherichia coli bacteria during growth up to defined large dimensions. De novo formation of patterns from homogenous starting conditions is observed and studied both experimentally and in simulations. A new theoretical approach is developed for probing pattern stability under perturbations. Quantitative experiments and simulations show that, once established, Min oscillations tolerate a large degree of intracellular heterogeneity, allowing distinctly different patterns to persist in different cells with the same geometry. Min patterns maintain their axes for hours in experiments, despite imperfections, expansion, and changes in cell shape during continuous cell growth. Transitions between multistable Min patterns are found to be rare events induced by strong intracellular perturbations. The instances of multistability studied here are the combined outcome of boundary growth and strongly nonlinear kinetics, which are characteristic of the reaction-diffusion patterns that pervade biology at many scales

Incidence and mortality of incidental prostate cancer: a Swedish register-based study

In a national register-based study of incidence trends and mortality of incidental prostate cancer in Sweden, we found that a significant proportion (26.6%) of affected men diagnosed died of their disease, which challenges earlier descriptions of incidental prostate cancer as a non-lethal disease

Weakened magnetic braking as the origin of anomalously rapid rotation in old field stars

A knowledge of stellar ages is crucial for our understanding of many astrophysical phenomena, and yet ages can be difficult to determine. As they become older, stars lose mass and angular momentum, resulting in an observed slowdown in surface rotation. The technique of 'gyrochronology' uses the rotation period of a star to calculate its age. However, stars of known age must be used for calibration, and, until recently, the approach was untested for old stars (older than 1 gigayear, Gyr). Rotation periods are now known for stars in an open cluster of intermediate age (NGC 6819; 2.5 Gyr old), and for old field stars whose ages have been determined with asteroseismology. The data for the cluster agree with previous period-age relations, but these relations fail to describe the asteroseismic sample. Here we report stellar evolutionary modelling, and confirm the presence of unexpectedly rapid rotation in stars that are more evolved than the Sun. We demonstrate that models that incorporate dramatically weakened magnetic braking for old stars can---unlike existing models---reproduce both the asteroseismic and the cluster data. Our findings might suggest a fundamental change in the nature of ageing stellar dynamos, with the Sun being close to the critical transition to much weaker magnetized winds. This weakened braking limits the diagnostic power of gyrochronology for those stars that are more than halfway through their main-sequence lifetimes.Comment: 25 pages, 3 figures in main paper, 6 extended data figures, 1 table. Published in Nature, January 2016. Please see https://youtu.be/O6HzYgP5uyc for a video description of the resul

Development of a Web-based Resident Profiling Tool to Support Training in Practice-based Learning and Improvement

Multiple factors are driving residency programs to explicitly address practice-based learning and improvement (PBLI), yet few information systems exist to facilitate such training. We developed, implemented, and evaluated a Web-based tool that provides Internal Medicine residents at the University of Virginia Health System with population-based reports about their ambulatory clinical experiences. Residents use Systems and Practice Analysis for Resident Competencies (SPARC) to identify potential areas for practice improvement. Thirty-three (65%) of 51 residents completed a survey assessing SPARC’s usefulness, with 94% agreeing that it was a useful educational tool. Twenty-six residents (51%) completed a before–after study indicating increased agreement (5-point Likert scale, with 5=strongly agree) with statements regarding confidence in ability to access population-based data about chronic disease management (mean [SD] 2.5 [1.2] vs. 4.5 [0.5], p < .001, sign test) and information comparing their practice style to that of their peers (2.2 [1.2] vs. 4.6 [0.5], p < .001)

Payer leverage and hospital compliance with a benchmark: a population-based observational study

<p>Abstract</p> <p>Background</p> <p>Since 1976, Medicare has linked reimbursement for hospitals performing organ transplants to the attainment of certain benchmarks, including transplant volume. While Medicare is a stakeholder in all transplant services, its role in renal transplantation is likely greater, given its coverage of end-stage renal disease. Thus, Medicare's transplant experience allows us to examine the role of payer leverage in motivating hospital benchmark compliance.</p> <p>Methods</p> <p>Nationally representative discharge data for kidney (<it>n </it>= 29,272), liver (<it>n </it>= 7,988), heart (<it>n </it>= 3,530), and lung (<it>n </it>= 1,880) transplants from the Nationwide Inpatient Sample (1993 – 2003) were employed. Logistic regression techniques with robust variance estimators were used to examine the relationship between hospital volume compliance and Medicare market share; generalized estimating equations were used to explore the association between patient-level operative mortality and hospital volume compliance.</p> <p>Results</p> <p>Medicare's transplant market share varied by organ [57%, 28%, 27%, and 18% for kidney, lung, heart, and liver transplants, respectively (<it>P </it>< 0.001)]. Volume-based benchmark compliance varied by transplant type [85%, 75%, 44%, and 39% for kidney, liver, heart, and lung transplants, respectively (<it>P </it>< 0.001)], despite a lower odds of operative mortality at compliant hospitals. Adjusting for organ supply, high market leverage was independently associated with compliance at hospitals transplanting kidneys (OR, 143.00; 95% CI, 18.53 – 1103.49), hearts (OR, 2.84; 95% CI, 1.51 – 5.34), and lungs (OR, 3.24; 95% CI, 1.57 – 6.67).</p> <p>Conclusion</p> <p>These data highlight the influence of payer leverage–an important contextual factor in value-based purchasing initiatives. For uncommon diagnoses, these data suggest that at least 30% of a provider's patients might need to be "at risk" for an incentive to motivate compliance.</p

Protocol for: Sheffield Obesity Trial (SHOT): A randomised controlled trial of exercise therapy and mental health outcomes in obese adolescents [ISRCNT83888112]

Background While obesity is known to have many physiological consequences, the psychopathology of this condition has not featured prominently in the literature. Cross-sectional studies have indicated that obese children have increased odds of experiencing poor quality of life and mental health. However, very limited trial evidence has examined the efficacy of exercise therapy for enhancing mental health outcomes in obese children, and the Sheffield Obesity Trial (SHOT) will provide evidence of the efficacy of supervised exercise therapy in obese young people aged 11–16 years versus usual care and an attention-control intervention. Method/design SHOT is a randomised controlled trial where obese young people are randomised to receive; (1) exercise therapy, (2) attention-control intervention (involving body-conditioning exercises and games that do not involve aerobic activity), or (3) usual care. The exercise therapy and attention-control sessions will take place three times per week for eight weeks and a six-week home programme will follow this. Ninety adolescents aged between 11–16 years referred from a children's hospital for evaluation of obesity or via community advertisements will need to complete the study. Participants will be recruited according to the following criteria: (1) clinically obese and aged 11–16 years (Body Mass Index Centile > 98th UK standard) (2) no medical condition that would restrict ability to be active three times per week for eight weeks and (3) not diagnosed with insulin dependent diabetes or receiving oral steroids. Assessments of outcomes will take place at baseline, as well as four (intervention midpoint) and eight weeks (end of intervention) from baseline. Participants will be reassessed on outcome measures five and seven months from baseline. The primary endpoint is physical self-perceptions. Secondary outcomes include physical activity, self-perceptions, depression, affect, aerobic fitness and BMI

Risk, Unexpected Uncertainty, and Estimation Uncertainty: Bayesian Learning in Unstable Settings

Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter) estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free) reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating