Predictors of failed attendances in a multi-specialty outpatient centre using electronic databases.

BACKGROUND: Failure to keep outpatient medical appointments results in inefficiencies and costs. The objective of this study is to show the factors in an existing electronic database that affect failed appointments and to develop a predictive probability model to increase the effectiveness of interventions. METHODS: A retrospective study was conducted on outpatient clinic attendances at Tan Tock Seng Hospital, Singapore from 2000 to 2004. 22864 patients were randomly sampled for analysis. The outcome measure was failed outpatient appointments according to each patient's latest appointment. RESULTS: Failures comprised of 21% of all appointments and 39% when using the patients' latest appointment. Using odds ratios from the mutliple logistic regression analysis, age group (0.75 to 0.84 for groups above 40 years compared to below 20 years), race (1.48 for Malays, 1.61 for Indians compared to Chinese), days from scheduling to appointment (2.38 for more than 21 days compared to less than 7 days), previous failed appointments (1.79 for more than 60% failures and 4.38 for no previous appointments, compared with less than 20% failures), provision of cell phone number (0.10 for providing numbers compared to otherwise) and distance from hospital (1.14 for more than 14 km compared to less than 6 km) were significantly associated with failed appointments. The predicted probability model's diagnostic accuracy to predict failures is more than 80%. CONCLUSION: A few key variables have shown to adequately account for and predict failed appointments using existing electronic databases. These can be used to develop integrative technological solutions in the outpatient clinic

Understanding organisational development, sustainability, and diffusion of innovations within hospitals participating in a multilevel quality collaborative

<p>Abstract</p> <p>Background</p> <p>Between 2004 and 2008, 24 Dutch hospitals participated in a two-year multilevel quality collaborative (MQC) comprised of (a) a leadership programme for hospital executives, (b) six quality-improvement collaboratives (QICs) for healthcare professionals and other staff, and (c) an internal programme organisation to help senior management monitor and coordinate team progress. The MQC aimed to stimulate the development of quality-management systems and the spread of methods to improve patient safety and logistics. The objective of this study is to describe how the first group of eight MQC hospitals sustained and disseminated improvements made and the quality methods used.</p> <p>Methods</p> <p>The approach followed by the hospitals was described using interview and questionnaire data gathered from eight programme coordinators.</p> <p>Results</p> <p>MQC hospitals followed a systematic strategy of diffusion and sustainability. Hospital quality-management systems are further developed according to a model linking plan-do-study-act cycles at the unit and hospital level. The model involves quality norms based on realised successes, performance agreements with unit heads, organisational support, monitoring, and quarterly accountability reports.</p> <p>Conclusions</p> <p>It is concluded from this study that the MQC contributed to organisational development and dissemination within participating hospitals. Organisational learning effects were demonstrated. System changes affect the context factors in the theory of organisational readiness: organisational culture, policies and procedures, past experience, organisational resources, and organisational structure. Programme coordinator responses indicate that these factors are utilised to manage spread and sustainability. Further research is needed to assess long-term effects.</p

Artemisinin Attenuates Lipopolysaccharide-Stimulated Proinflammatory Responses by Inhibiting NF-κB Pathway in Microglia Cells

Microglial activation plays an important role in neuroinflammation, which contributes to neuronal damage, and inhibition of microglial activation may have therapeutic benefits that could alleviate the progression of neurodegeneration. Recent studies have indicated that the antimalarial agent artemisinin has the ability to inhibit NF-κB activation. In this study, the inhibitory effects of artemisinin on the production of proinflammatory mediators were investigated in lipopolysaccharide (LPS)-stimulated primary microglia. Our results show that artemisinin significantly inhibited LPS-induced production of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), monocyte chemotactic protein-1 (MCP-1) and nitric oxide (NO). Artemisinin significantly decreased both the mRNA and the protein levels of these pro-inflammatory cytokines and inducible nitric oxide synthase (iNOS) and increased the protein levels of IκB-α, which forms a cytoplasmic inactive complex with the p65-p50 heterodimeric complex. Artemisinin treatment significantly inhibited basal and LPS-induced migration of BV-2 microglia. Electrophoretic mobility shift assays revealed increased NF-κB binding activity in LPS-stimulated primary microglia, and this increase could be prevented by artemisinin. The inhibitory effects of artemisinin on LPS-stimulated microglia were blocked after IκB-α was silenced with IκB-α siRNA. Our results suggest that artemisinin is able to inhibit neuroinflammation by interfering with NF-κB signaling. The data provide direct evidence of the potential application of artemisinin for the treatment of neuroinflammatory diseases

One Fungus = One Name: DNA and fungal nomenclature twenty years after PCR

Some fungi with pleomorphic life-cycles still bear two names despite more than 20 years of molecular phylogenetics that have shown how to merge the two systems of classification, the asexual “Deuteromycota” and the sexual “Eumycota”. Mycologists have begun to flout nomenclatorial regulations and use just one name for one fungus. The International Code of Botanical Nomenclature (ICBN) must change to accommodate current practice or become irrelevant. The fundamental difference in the size of fungi and plants had a role in the origin of dual nomenclature and continues to hinder the development of an ICBN that fully accommodates microscopic fungi. A nomenclatorial crisis also looms due to environmental sequencing, which suggests that most fungi will have to be named without a physical specimen. Mycology may need to break from the ICBN and create a MycoCode to account for fungi known only from environmental nucleic acid sequence (i.e. ENAS fungi)

The chemical signatures underlying host plant discrimination by aphids

The diversity of phytophagous insects is largely attributable to speciation involving shifts between host plants. These shifts are mediated by the close interaction between insects and plant metabolites. However, there has been limited progress in understanding the chemical signatures that underlie host preferences. We use the pea aphid (Acyrthosiphon pisum) to address this problem. Host-associated races of pea aphid discriminate between plant species in race-specific ways. We combined metabolomic profiling of multiple plant species with behavioural tests on two A. pisum races, to identify metabolites that explain variation in either acceptance or discrimination. Candidate compounds were identified using tandem mass spectrometry. Our results reveal a small number of compounds that explain a large proportion of variation in the differential acceptability of plants to A. pisum races. Two of these were identified as L-phenylalanine and L-tyrosine but it may be that metabolically-related compounds directly influence insect behaviour. The compounds implicated in differential acceptability were not related to the set correlated with general acceptability of plants to aphids, regardless of host race. Small changes in response to common metabolites may underlie host shifts. This study opens new opportunities for understanding the mechanistic basis of host discrimination and host shifts in insects

Modeling screening, prevention, and delaying of Alzheimer's disease: an early-stage decision analytic model

<p>Abstract</p> <p>Background</p> <p>Alzheimer's Disease (AD) affects a growing proportion of the population each year. Novel therapies on the horizon may slow the progress of AD symptoms and avoid cases altogether. Initiating treatment for the underlying pathology of AD would ideally be based on biomarker screening tools identifying pre-symptomatic individuals. Early-stage modeling provides estimates of potential outcomes and informs policy development.</p> <p>Methods</p> <p>A time-to-event (TTE) simulation provided estimates of screening asymptomatic patients in the general population age ≥55 and treatment impact on the number of patients reaching AD. Patients were followed from AD screen until all-cause death. Baseline sensitivity and specificity were 0.87 and 0.78, with treatment on positive screen. Treatment slowed progression by 50%. Events were scheduled using literature-based age-dependent incidences of AD and death.</p> <p>Results</p> <p>The base case results indicated increased AD free years (AD-FYs) through delays in onset and a reduction of 20 AD cases per 1000 screened individuals. Patients completely avoiding AD accounted for 61% of the incremental AD-FYs gained. Total years of treatment per 1000 screened patients was 2,611. The number-needed-to-screen was 51 and the number-needed-to-treat was 12 to avoid one case of AD. One-way sensitivity analysis indicated that duration of screening sensitivity and rescreen interval impact AD-FYs the most. A two-way sensitivity analysis found that for a test with an extended duration of sensitivity (15 years) the number of AD cases avoided was 6,000-7,000 cases for a test with higher sensitivity and specificity (0.90,0.90).</p> <p>Conclusions</p> <p>This study yielded valuable parameter range estimates at an early stage in the study of screening for AD. Analysis identified duration of screening sensitivity as a key variable that may be unavailable from clinical trials.</p

Comparative analysis of bones, mites, soil chemistry, nematodes and soil micro-Eukaryotes from a suspected homicide to estimate the post-mortem interval

Criminal investigations of suspected murder cases require estimating the post-mortem interval (PMI, or time after death) which is challenging for longer periods. Here we present the case of human remains found in a Swiss forest. We have used a multidisciplinary approach involving the analysis of bones, soil chemical characteristics, mites and nematodes (by microscopy) and micro-Eukaryotes (by Illumina high throughput sequencing). We analysed soil samples collected beneath the remains of the head, upper and lower body and “control” samples taken a few meters away. The PMI estimated on hair 14C-data via bomb peak radiocarbon dating gave a time range of 1 to 2 years before the finding of the remains on site. Cluster analyses for chemical constituents, nematodes, mites and micro- Eukaryotes revealed two clusters 1) head and upper body and 2) lower body and controls. From mite evidence, we conclude that the body was likely to have been brought to the site after death. However, chemical analyses, nematode community analyses and the analyses of micro-Eukaryotes indicate that decomposition took place at least partly on site. This study illustrates the usefulness of combining several lines of evidence for the study of homicide cases to better calibrate PMI inference tools