Functional central limit theorems for vicious walkers

We consider the diffusion scaling limit of the vicious walker model that is a system of nonintersecting random walks. We prove a functional central limit theorem for the model and derive two types of nonintersecting Brownian motions, in which the nonintersecting condition is imposed in a finite time interval $(0,T]$ for the first type and in an infinite time interval $(0,\infty)$ for the second type, respectively. The limit process of the first type is a temporally inhomogeneous diffusion, and that of the second type is a temporally homogeneous diffusion that is identified with a Dyson's model of Brownian motions studied in the random matrix theory. We show that these two types of processes are related to each other by a multi-dimensional generalization of Imhof's relation, whose original form relates the Brownian meander and the three-dimensional Bessel process. We also study the vicious walkers with wall restriction and prove a functional central limit theorem in the diffusion scaling limit.Comment: AMS-LaTeX, 20 pages, 2 figures, v6: minor corrections made for publicatio

Medical school faculty discontent: prevalence and predictors of intent to leave academic careers

<p>Abstract</p> <p>Background</p> <p>Medical school faculty are less enthusiastic about their academic careers than ever before. In this study, we measured the prevalence and determinants of intent to leave academic medicine.</p> <p>Methods</p> <p>A 75-question survey was administered to faculty at a School of Medicine. Questions addressed quality of life, faculty responsibilities, support for teaching, clinical work and scholarship, mentoring and participation in governance.</p> <p>Results</p> <p>Of 1,408 eligible faculty members, 532 (38%) participated. Among respondents, 224 (40%; CI95: 0.35, 0.44) reported that their careers were not progressing satisfactorily; 236 (42%; CI95: 0.38, 0.46) were "seriously considering leaving academic medicine in the next five years." Members of clinical departments (OR = 1.71; CI95: 1.01, 2.91) were more likely to consider leaving; members of inter-disciplinary centers were less likely (OR = 0.68; CI95: 0.47, 0.98). The predictors of "serious intent to leave" included: Difficulties balancing work and family (OR = 3.52; CI95: 2.34, 5.30); inability to comment on performance of institutional leaders (OR = 3.08; CI95: 2.07, 4.72); absence of faculty development programs (OR = 3.03; CI95: 2.00, 4.60); lack of recognition of clinical work (OR = 2.73; CI95: 1.60, 4.68) and teaching (OR = 2.47; CI95: 1.59, 3.83) in promotion evaluations; absence of "academic community" (OR = 2.67; CI95: 1.86, 3.83); and failure of chairs to evaluate academic progress regularly (OR = 2.60; CI95: 1.80, 3.74).</p> <p>Conclusion</p> <p>Faculty are a medical school's key resource, but 42 percent are seriously considering leaving. Medical schools should refocus faculty retention efforts on professional development programs, regular performance feedback, balancing career and family, tangible recognition of teaching and clinical service and meaningful faculty participation in institutional governance.</p

Can computerized clinical decision support systems improve practitioners' diagnostic test ordering behavior? A decision-maker-researcher partnership systematic review

<p>Abstract</p> <p>Background</p> <p>Underuse and overuse of diagnostic tests have important implications for health outcomes and costs. Decision support technology purports to optimize the use of diagnostic tests in clinical practice. The objective of this review was to assess whether computerized clinical decision support systems (CCDSSs) are effective at improving ordering of tests for diagnosis, monitoring of disease, or monitoring of treatment. The outcome of interest was effect on the diagnostic test-ordering behavior of practitioners.</p> <p>Methods</p> <p>We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for eligible articles published up to January 2010. We included randomized controlled trials comparing the use of CCDSSs to usual practice or non-CCDSS controls in clinical care settings. Trials were eligible if at least one component of the CCDSS gave suggestions for ordering or performing a diagnostic procedure. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of test ordering outcomes.</p> <p>Results</p> <p>Thirty-five studies were identified, with significantly higher methodological quality in those published after the year 2000 (<it>p </it>= 0.002). Thirty-three trials reported evaluable data on diagnostic test ordering, and 55% (18/33) of CCDSSs improved testing behavior overall, including 83% (5/6) for diagnosis, 63% (5/8) for treatment monitoring, 35% (6/17) for disease monitoring, and 100% (3/3) for other purposes. Four of the systems explicitly attempted to reduce test ordering rates and all succeeded. Factors of particular interest to decision makers include costs, user satisfaction, and impact on workflow but were rarely investigated or reported.</p> <p>Conclusions</p> <p>Some CCDSSs can modify practitioner test-ordering behavior. To better inform development and implementation efforts, studies should describe in more detail potentially important factors such as system design, user interface, local context, implementation strategy, and evaluate impact on user satisfaction and workflow, costs, and unintended consequences.</p

Biomedical informatics and translational medicine

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams