Understanding implementation processes of clinical pathways and clinical practice guidelines in pediatric contexts: a study protocol

<p>Abstract</p> <p>Background</p> <p>Canada is among the most prosperous nations in the world, yet the health and wellness outcomes of Canadian children are surprisingly poor. There is some evidence to suggest that these poor health outcomes are partly due to clinical practice variation, which can stem from failure to apply the best available research evidence in clinical practice, otherwise known as knowledge translation (KT). Surprisingly, clinical practice variation, even for common acute paediatric conditions, is pervasive. Clinical practice variation results in unnecessary medical treatments, increased suffering, and increased healthcare costs. This study focuses on improving health outcomes for common paediatric acute health concerns by evaluating strategies that improve KT and reduce clinical practice variation.</p> <p>Design/Methods</p> <p>Using a multiple case study design, qualitative and quantitative data will be collected from four emergency departments in western Canada. Data sources will include: pre- and post-implementation focus group data from multidisciplinary healthcare professionals; individual interviews with the local champions, KT intervention providers, and unit/site leaders/managers; Alberta Context Tool (ACT) survey data; and aggregated patient outcome data. Qualitative and quantitative data will be systematically triangulated, and matrices will be built to do cross-case comparison. Explanations will be built about the success or lack of success of the clinical practice guidelines (CPG) and clinical pathways (CPs) uptake based upon the cross-case comparisons.</p> <p>Significance</p> <p>This study will generate new knowledge about the potential causal mechanisms and factors which shape implementation. Future studies will track the impact of the CPG/CPs implementation on children's health outcome, and healthcare costs.</p

Dealing with heterogeneity of treatment effects: is the literature up to the challenge?

<p>Abstract</p> <p>Background</p> <p>Some patients will experience more or less benefit from treatment than the averages reported from clinical trials; such variation in therapeutic outcome is termed heterogeneity of treatment effects (HTE). Identifying HTE is necessary to individualize treatment. The degree to which heterogeneity is sought and analyzed correctly in the general medical literature is unknown. We undertook this literature sample to track the use of HTE analyses over time, examine the appropriateness of the statistical methods used, and explore the predictors of such analyses.</p> <p>Methods</p> <p>Articles were selected through a probability sample of randomized controlled trials (RCTs) published in <it>Annals of Internal Medicine</it>, <it>BMJ</it>, <it>JAMA</it>, <it>The Lancet</it>, and <it>NEJM </it>during odd numbered months of 1994, 1999, and 2004. RCTs were independently reviewed and coded by two abstractors, with adjudication by a third. Studies were classified as reporting: (1) HTE analysis, utilizing a formal test for heterogeneity or treatment-by-covariate interaction, (2) subgroup analysis only, involving no formal test for heterogeneity or interaction; or (3) neither. Chi-square tests and multiple logistic regression were used to identify variables associated with HTE reporting.</p> <p>Results</p> <p>319 studies were included. Ninety-two (29%) reported HTE analysis; another 88 (28%) reported subgroup analysis only, without examining HTE formally. Major covariates examined included individual risk factors associated with prognosis, responsiveness to treatment, or vulnerability to adverse effects of treatment (56%); gender (30%); age (29%); study site or center (29%); and race/ethnicity (7%). Journal of publication and sample size were significant independent predictors of HTE analysis (p < 0.05 and p < 0.001, respectively).</p> <p>Conclusion</p> <p>HTE is frequently ignored or incorrectly analyzed. An iterative process of exploratory analysis followed by confirmatory HTE analysis will generate the data needed to facilitate an individualized approach to evidence-based medicine.</p

Dedifferentiation of Foetal CNS Stem Cells to Mesendoderm-Like Cells through an EMT Process

Tissue-specific stem cells are considered to have a limited differentiation potential. Recently, this notion was challenged by reports that showed a broader differentiation potential of neural stem cells, in vitro and in vivo, although the molecular mechanisms that regulate plasticity of neural stem cells are unknown. Here, we report that neural stem cells derived from mouse embryonic cortex respond to Lif and serum in vitro and undergo epithelial to mesenchymal transition (EMT)-mediated dedifferentiation process within 48 h, together with transient upregulation of pluripotency markers and, more notably, upregulation of mesendoderm genes, Brachyury (T) and Sox17. These induced putative mesendoderm cells were injected into early gastrulating chick embryos, which revealed that they integrated more efficiently into mesoderm and endoderm lineages compared to non-induced cells. We also found that TGFβ and Jak/Stat pathways are necessary but not sufficient for the induction of mesendodermal phenotype in neural stem cells. These results provide insights into the regulation of plasticity of neural stem cells through EMT. Dissecting the regulatory pathways involved in these processes may help to gain control over cell fate decisions

Do People Taking Flu Vaccines Need Them the Most?

Background: A well targeted flu vaccine strategy can ensure that vaccines go to those who are at the highest risk of getting infected if unvaccinated. However, prior research has not explicitly examined the association between the risk of flu infection and vaccination rates. Purpose: This study examines the relationship between the risk of flu infection and the probability of getting vaccinated. Methods: Nationally representative data from the US and multivariate regression models were used to estimate what individual characteristics are associated with (1) the risk of flu infection when unvaccinated and (2) flu vaccination rates. These results were used to estimate the correlation between the probability of infection and the probability of getting vaccinated. Separate analyses were performed for the general population and the high priority population that is at increased risk of flu related complications. Results: We find that the high priority population was more likely to get vaccinated compared to the general population. However, within both the high priority and general populations the risk of flu infection when unvaccinated was negatively correlated with vaccination rates (r = 20.067, p,0.01). This negative association between the risk of infection when unvaccinated and the probability of vaccination was stronger for the high priority population (r = 20.361, p,0.01). Conclusions: There is a poor match between those who get flu vaccines and those who have a high risk of flu infectio