Improved quality and efficiency after the introduction of physician-led team triage in an emergency department

Background: Overcrowding in the emergency department (ED) may negatively affect patient outcomes, so different triage models have been introduced to improve performance. Physician-led team triage obtains better results than other triage models. We compared efficiency and quality measures before and after reorganization of the triage model in the ED at our county hospital. Materials and methods: We retrospectively compared two study periods with different triage models: nurse triage in 2008 (baseline) and physician-led team triage in 2012 (follow-up). Physician-led team triage was in use during day-time and early evenings on weekdays. Data were collected from electronic medical charts and the National Mortality Register. Results: We included 20,073 attendances in 2008 and 23,765 in 2012. The time from registration to physician presentation decreased from 80 to 33 min (P <0.001), and the length of stay decreased from 219 to 185 min (P <0.001) from 2008 to 2012, respectively. All of the quality variables differed significantly between the two periods, with better results in 2012. The odds ratio for patients who left before being seen or before treatment was completed was 0.62 (95% confidence interval 0.54-0.72). The corresponding result for unscheduled returns was 0.36 (0.32-0.40), and for the mortality rates within 7 and 30 days 0.72 (0.59-0.88) and 0.84 (0.73-0.97), respectively. The admission rate was 37% at baseline and 32% at follow-up (P <0.001). Conclusion: Physician-led team triage improved the efficiency and quality in EDs.Peer reviewe

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Physician-led team triage based on lean principles may be superior for efficiency and quality? A comparison of three emergency departments with different triage models

<p>Abstract</p> <p>Background</p> <p>The management of emergency departments (EDs) principally involves maintaining effective patient flow and care. Different triage models are used today to achieve these two goals. The aim of this study was to compare the performance of different triage models used in three Swedish EDs. Using efficiency and quality indicators, we compared the following triage models: physician-led team triage, nurse first/emergency physician second, and nurse first/junior physician second.</p> <p>Methods</p> <p>All data of patients arriving at the three EDs between 08:00- and 21:00 throughout 2008 were collected and merged into a database. The following efficiency indicators were measured: length of stay (LOS) including time to physician, time from physician to discharge, and 4-hour turnover rate. The following quality indicators were measured: rate of patients left before treatment was completed, unscheduled return within 24 and 72 hours, and mortality rate within 7 and 30 days.</p> <p>Results</p> <p>Data from 147,579 patients were analysed. The median length of stay was 158 minutes for physician-led team triage, compared with 243 and 197 minutes for nurse/emergency physician and nurse/junior physician triage, respectively (p < 0.001). The rate of patients left before treatment was completed was 3.1% for physician-led team triage, 5.3% for nurse/emergency physician, and 9.6% for nurse/junior physician triage (p < 0.001). Further, the rates of unscheduled return within 24 hours were significantly lower for physician-led team triage, 1.0%, compared with 2.1%, and 2.5% for nurse/emergency physician, and nurse/junior physician, respectively (p < 0.001). The mortality rate within 7 days was 0.8% for physician-led team triage and 1.0% for the two other triage models (p < 0.001).</p> <p>Conclusions</p> <p>Physician-led team triage seemed advantageous, both expressed as efficiency and quality indicators, compared with the two other models.</p