Improving quality indicator report cards through Bayesian modeling

<p>Abstract</p> <p>Background</p> <p>The National Database for Nursing Quality Indicators^®(NDNQI^®) was established in 1998 to assist hospitals in monitoring indicators of nursing quality (eg, falls and pressure ulcers). Hospitals participating in NDNQI transmit data from nursing units to an NDNQI data repository. Data are summarized and published in reports that allow participating facilities to compare the results for their units with those from other units across the nation. A disadvantage of this reporting scheme is that the sampling variability is not explicit. For example, suppose a small nursing unit that has 2 out of 10 (rate of 20%) patients with pressure ulcers. Should the nursing unit immediately undertake a quality improvement plan because of the rate difference from the national average (7%)?</p> <p>Methods</p> <p>In this paper, we propose approximating 95% credible intervals (CrIs) for unit-level data using statistical models that account for the variability in unit rates for report cards.</p> <p>Results</p> <p>Bayesian CrIs communicate the level of uncertainty of estimates more clearly to decision makers than other significance tests.</p> <p>Conclusion</p> <p>A benefit of this approach is that nursing units would be better able to distinguish problematic or beneficial trends from fluctuations likely due to chance.</p

A systematic review of models to predict recruitment to multicentre clinical trials

<p>Abstract</p> <p>Background</p> <p>Less than one third of publicly funded trials managed to recruit according to their original plan often resulting in request for additional funding and/or time extensions. The aim was to identify models which might be useful to a major public funder of randomised controlled trials when estimating likely time requirements for recruiting trial participants. The requirements of a useful model were identified as usability, based on experience, able to reflect time trends, accounting for centre recruitment and contribution to a commissioning decision.</p> <p>Methods</p> <p>A systematic review of English language articles using MEDLINE and EMBASE. Search terms included: randomised controlled trial, patient, accrual, predict, enrol, models, statistical; Bayes Theorem; Decision Theory; Monte Carlo Method and Poisson. Only studies discussing prediction of recruitment to trials using a modelling approach were included. Information was extracted from articles by one author, and checked by a second, using a pre-defined form.</p> <p>Results</p> <p>Out of 326 identified abstracts, only 8 met all the inclusion criteria. Of these 8 studies examined, there are five major classes of model discussed: the unconditional model, the conditional model, the Poisson model, Bayesian models and Monte Carlo simulation of Markov models. None of these meet all the pre-identified needs of the funder.</p> <p>Conclusions</p> <p>To meet the needs of a number of research programmes, a new model is required as a matter of importance. Any model chosen should be validated against both retrospective and prospective data, to ensure the predictions it gives are superior to those currently used.</p

Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology

Contains fulltext : 97171.pdf (postprint version ) (Open Access)BACKGROUND: Current human resources planning models in nursing are unreliable and ineffective as they consider volumes, but ignore effects on quality in patient care. The project RN4CAST aims innovative forecasting methods by addressing not only volumes, but quality of nursing staff as well as quality of patient care. METHODS/DESIGN: A multi-country, multilevel cross-sectional design is used to obtain important unmeasured factors in forecasting models including how features of hospital work environments impact on nurse recruitment, retention and patient outcomes. In each of the 12 participating European countries, at least 30 general acute hospitals were sampled. Data are gathered via four data sources (nurse, patient and organizational surveys and via routinely collected hospital discharge data). All staff nurses of a random selection of medical and surgical units (at least 2 per hospital) were surveyed. The nurse survey has the purpose to measure the experiences of nurses on their job (e.g. job satisfaction, burnout) as well as to allow the creation of aggregated hospital level measures of staffing and working conditions. The patient survey is organized in a sub-sample of countries and hospitals using a one-day census approach to measure the patient experiences with medical and nursing care. In addition to conducting a patient survey, hospital discharge abstract datasets will be used to calculate additional patient outcomes like in-hospital mortality and failure-to-rescue. Via the organizational survey, information about the organizational profile (e.g. bed size, types of technology available, teaching status) is collected to control the analyses for institutional differences.This information will be linked via common identifiers and the relationships between different aspects of the nursing work environment and patient and nurse outcomes will be studied by using multilevel regression type analyses. These results will be used to simulate the impact of changing different aspects of the nursing work environment on quality of care and satisfaction of the nursing workforce. DISCUSSION: RN4CAST is one of the largest nurse workforce studies ever conducted in Europe, will add to accuracy of forecasting models and generate new approaches to more effective management of nursing resources in Europe

Natural and Vaccine-Mediated Immunity to Salmonella Typhimurium is Impaired by the Helminth Nippostrongylus brasiliensis

The impact of exposure to multiple pathogens concurrently or consecutively on immune function is unclear. Here, immune responses induced by combinations of the bacterium Salmonella Typhimurium (STm) and the helminth Nippostrongylus brasiliensis (Nb), which causes a murine hookworm infection and an experimental porin protein vaccine against STm, were examined. Mice infected with both STm and Nb induced similar numbers of Th1 and Th2 lymphocytes compared with singly infected mice, as determined by flow cytometry, although lower levels of secreted Th2, but not Th1 cytokines were detected by ELISA after re-stimulation of splenocytes. Furthermore, the density of FoxP3+ T cells in the T zone of co-infected mice was lower compared to mice that only received Nb, but was greater than those that received STm. This reflected the intermediate levels of IL-10 detected from splenocytes. Co-infection compromised clearance of both pathogens, with worms still detectable in mice weeks after they were cleared in the control group. Despite altered control of bacterial and helminth colonization in co-infected mice, robust extrafollicular Th1 and Th2-reflecting immunoglobulin-switching profiles were detected, with IgG2a, IgG1 and IgE plasma cells all detected in parallel. Whilst extrafollicular antibody responses were maintained in the first weeks after co-infection, the GC response was less than that in mice infected with Nb only. Nb infection resulted in some abrogation of the longer-term development of anti-STm IgG responses. This suggested that prior Nb infection may modulate the induction of protective antibody responses to vaccination. To assess this we immunized mice with porins, which confer protection in an antibody-dependent manner, before challenging with STm. Mice that had resolved a Nb infection prior to immunization induced less anti-porin IgG and had compromised protection against infection. These findings demonstrate that co-infection can radically alter the development of protective immunity during natural infection and in response to immunization

Missense mutation of Brain Derived Neurotrophic Factor (BDNF) alters neurocognitive performance in patients with mild traumatic brain injury: a longitudinal study

The predictability of neurocognitive outcomes in patients with traumatic brain injury is not straightforward. The extent and nature of recovery in patients with mild traumatic brain injury (mTBI) are usually heterogeneous and not substantially explained by the commonly known demographic and injury-related prognostic factors despite having sustained similar injuries or injury severity. Hence, this study evaluated the effects and association of the Brain Derived Neurotrophic Factor (BDNF) missense mutations in relation to neurocognitive performance among patients with mTBI. 48 patients with mTBI were prospectively recruited and MRI scans of the brain were performed within an average 10.1 (SD 4.2) hours post trauma with assessment of their neuropsychological performance post full Glasgow Coma Scale (GCS) recovery. Neurocognitive assessments were repeated again at 6 months follow-up. The paired t-test, Cohen’s d effect size and repeated measure ANOVA were performed to delineate statistically significant differences between the groups [wildtype G allele (Val homozygotes) vs. minor A allele (Met carriers)] and their neuropsychological performance across the time point (T1 = baseline/ admission vs. T2 = 6th month follow-up). Minor A allele carriers in this study generally performed more poorly on neuropsychological testing in comparison wildtype G allele group at both time points. Significant mean differences were observed among the wildtype group in the domains of memory (M = -11.44, SD = 10.0, p = .01, d = 1.22), executive function (M = -11.56, SD = 11.7, p = .02, d = 1.05) and overall performance (M = -6.89 SD = 5.3, p = .00, d = 1.39), while the minor A allele carriers showed significant mean differences in the domains of attention (M = -11.0, SD = 13.1, p = .00, d = .86) and overall cognitive performance (M = -5.25, SD = 8.1, p = .01, d = .66).The minor A allele carriers in comparison to the wildtype G allele group, showed considerably lower scores at admission and remained impaired in most domains across the timepoints, although delayed signs of recovery were noted to be significant in the domains attention and overall cognition. In conclusion, the current study has demonstrated the role of the BDNF rs6265 Val66Met polymorphism in influencing specific neurocognitive outcomes in patients with mTBI. Findings were more detrimentally profound among Met allele carriers

Metabolic engineering of Rhizopus oryzae for the production of platform chemicals

Rhizopus oryzae is a filamentous fungus belonging to the Zygomycetes. It is among others known for its ability to produce the sustainable platform chemicals l-(+)-lactic acid, fumaric acid, and ethanol. During glycolysis, all fermentable carbon sources are metabolized to pyruvate and subsequently distributed over the pathways leading to the formation of these products. These platform chemicals are produced in high yields on a wide range of carbon sources. The yields are in excess of 85 % of the theoretical yield for l-(+)-lactic acid and ethanol and over 65 % for fumaric acid. The study and optimization of the metabolic pathways involved in the production of these compounds requires well-developed metabolic engineering tools and knowledge of the genetic makeup of this organism. This review focuses on the current metabolic engineering techniques available for R. oryzae and their application on the metabolic pathways of the main fermentation products