Interstitial Lung Disease: Seasonality of Hospitalizations and In-Hospital Mortality 2005-2015.

BACKGROUND: The overall incidence of interstitial lung disease and disease-associated mortality have been found on the rise. Hospitalizations for interstitial lung disease are typically caused by airway infection or the acute exacerbation of the underlying disease. Seasonal variance in ambient air pollution has recently been linked to exacerbation and mortality. We sought to examine the seasonal pattern of hospitalizations in Germany, use of mechanical ventilation, and in-hospital mortality on a year-by-year basis to identify their overall trend and to characterize seasonal patterns. METHODS: The national in-patient database of the federal statistical office of Germany was searched for cases of interstitial lung disease. RESULTS: A total of 130,366 hospitalizations for ILD occurred from 2005 to 2015. Time series data were examined for seasonality using X-11 statistics. The incidence of hospitalizations, mechanical ventilation, and in-hospital mortality show clear seasonal peaks in the cold season. The observed seasonality cannot be attributed to the variance of selected comorbidities. Also, there is a significant overall upward trend regarding hospitalization counts, especially in the use of non-invasive ventilation. CONCLUSION: Time series analysis of in-hospital data shows an ILD-related rise of hospitalizations, in-hospital mortality, and non-invasive ventilation. This emphasizes a growing importance of interstitial lung diseases for health-care systems. Strong seasonality is seen in these variables. Data therefore support previous studies of ILD exacerbation. More research on infectious causes and environmental factors is warranted.

The conserved kinase SRPK regulates karyosome formation and spindle microtubule assembly in Drosophila oocytes.

In Drosophila oocytes, after the completion of recombination, meiotic chromosomes form a compact cluster called the karyosome within the nucleus, and later assemble spindle microtubules without centrosomes. Although these oocyte-specific phenomena are also observed in humans, their molecular basis is not well understood. Here, we report essential roles for the conserved kinase SRPK in both karyosome formation and spindle microtubule assembly in oocytes. We have identified a female-sterile srpk mutant through a cytological screen for karyosome defects. Unlike most karyosome mutants, the karyosome defect is independent of the meiotic recombination checkpoint. Heterochromatin clustering found within the wild-type karyosome is disrupted in the mutant. Strikingly, a loss of SRPK severely prevents microtubule assembly for acentrosomal spindles in mature oocytes. Subsequently, bi-orientation and segregation of meiotic chromosomes are also defective. Therefore, this study demonstrates new roles of this conserved kinase in two independent meiotic steps specific to oocytes.

A before-after study to evaluate the effect of pharmacy workflow redesign to improve pharmacy waiting time and reduce medication near misses in Malaysia.

OBJECTIVES: This study aimed to evaluate the effectiveness of workflow redesign (eaST system) on pharmacy waiting time and near-missed events. We also investigated other factors that may potentially affect these study outcomes. METHODS: A quasi-experimental (before-after) study design was adopted. Pre-intervention data were collected over 7 months (January-July 2017). Subsequently, the workflow redesign (eaST system) was implemented and the effect of the intervention (August 2017-February 2018) was evaluated. Univariate analysis was used to compare the differences between pre-intervention and post-intervention of pharmacy waiting time and near-missed events. Significant factors affecting study outcomes were analysed using linear regression analysis. KEY FINDINGS: A total of 210,530 prescriptions were analysed. The eaST system significantly increases the percentage of prescriptions dispensed within 30 min per day (median = 68 (interquartile range (IQR) = 41) vs. median = 93 (IQR = 33), P < 0.001) and reduced the mean percentage of near-missed events (mean = 50.71 (standard deviation (SD) = 23.95) vs. mean = 27.87 (SD = 12.23), P < 0.001). However, the eaST system's effects on related outcomes were conditional on a three-way interaction effect. The eaST system's effects on pharmacy waiting time were influenced by the number of prescriptions received and the number of PhIS server disruptions. Conversely, the eaST system's effects on near-missed events were influenced by the number of pharmacy personnel and number of controlled medications. CONCLUSIONS: Overall, the eaST system improved the pharmacy waiting time and reduced near-missed events.

Characteristics and outcomes of a cohort hospitalized for pandemic and seasonal influenza in Germany based on nationwide inpatient data.

RATIONALE: From June of 2009 to August of 2010 the influenza subtype H1N1pdm09 caused a worldwide pandemic. The impact on populations and health care systems around the globe evolved differently. Substantial data come from the German national surveillance network in an outpatient and private practice setting, while information on hospitalized patients in Germany is rather limited. METHODS: Data from the Federal Statistics Office comprising health insurance claims of the entire nationwide inpatient sample from 2005 to 2012 were used to identify patients who were hospitalized for laboratory-confirmed influenza and to analyse demographical aspects, comorbidities, hospitalization duration, outcomes and ventilator use during the pandemic and seasonal waves of influenza. MEASUREMENTS AND MAIN RESULTS: A number of 34,493 admissions for laboratory-confirmed influenza occurred during waves between 2005 and 2012. During the pandemic seasonal waves, the number of hospitalizations vastly surpassed the level that was seen in any of the seasonal waves. A major demographic shift was seen with respect to patient age, as younger patients (< 60 years old) were more frequently hospitalized. Mean length of stay was shorter (149 vs. 193 hours), mean time on ventilation tended to be shorter (261 vs. 305 hours) in young children (< 4 years old) and longer (393 vs. 339 hours) in the elderly (> 60 years old). Time to ventilation was shorter in non-fatal cases (328 vs. 349 hours) and longer in fatal cases (419 vs. 358 hours). Logistic regression was used to show the impact of comorbidities and co-diagnoses on mortality and the need for ventilation, as well as differences between pandemic and seasonal influenza. CONCLUSIONS: Inpatient data suggest differences in patient populations during pandemic and seasonal influenza. Younger patients were more frequently hospitalized. Differences with respect to the presence of certain comorbidities and co-diagnoses, length of stay, time to ventilation and ventilation time could be identified.

Impact of value added services on patient waiting time at the ambulatory pharmacy Queen Elizabeth Hospital.

BACKGROUND: Value added services (VAS) are an innovative dispensing system created to provide an alternative means of collecting partial drug supply from our hospital. This in turn was projected to reduce the necessity for patient to visit pharmacy counter and thus reduce the burden of prescription handling. OBJECTIVE: To evaluate the impact of increased VAS uptake following promotional campaign towards patient waiting time and to explore factors that may affect patient waiting time at the Ambulatory Pharmacy, Queen Elizabeth Hospital. METHODS: A quasi experimental study design was conducted from September 2014 till June 2015 at the Ambulatory Pharmacy. During pre-intervention phase, baseline parameters were collected retrospectively. Then, VAS promotional campaign was carried out for six months and whilst this was done, the primary outcome of patient waiting time was measured by percentage of prescription served less than 30 minutes. A linear regression analysis was used to determine the impact of increased VAS uptake towards patient waiting time. RESULTS: An increased in percentage of VAS registration (20.9% vs 35.7%, p<0.001) was observed after the promotional campaign. The mean percentage of prescription served less than 30 minutes increased from 83.2% SD=15.9 to 90.3% SD=11.5, p=0.001. After controlling for covariates, it was found that patient waiting time was affected by number of pharmacy technicians (b=-0.0349, 95%CI-0.0548 : -0.0150, p=0.001), number of pharmacy counters (b=0.1125, 95%CI 0.0631 : 0.1620, p<0.001), number of prescriptions (b=0.0008, 95%CI 0.0004 : 0.0011, p<0.001), and number of refill prescriptions (b=0.0004, 95%CI 0.0002 : 0.0007, p<0.001). The increased in percentage of VAS registration was associated with reduction in number of refill prescription (b=-2.9838, 95%CI -4.2289 : -1.7388, p<0.001). CONCLUSIONS: Patient waiting time at the Ambulatory Pharmacy improved with the increased in VAS registration. The impact of increased VAS uptake on patient waiting time resulted from reduction in refill prescriptions. Patient waiting time is influenced by number of pharmacy technicians, number of pharmacy counters, number of prescriptions and number of refill prescriptions.

Impact of value added services on patient waiting time at the ambulatory pharmacy Queen Elizabeth Hospital

Background: Value added services (VAS) are an innovative dispensing system created to provide an alternative means of collecting partial drug supply from our hospital. This in turn was projected to reduce the necessity for patient to visit pharmacy counter and thus reduce the burden of prescription handling. Objective: To evaluate the impact of increased VAS uptake following promotional campaign towards patient waiting time and to explore factors that may affect patient waiting time at the Ambulatory Pharmacy, Queen Elizabeth Hospital. Methods: A quasi experimental study design was conducted from September 2014 till June 2015 at the Ambulatory Pharmacy. During pre-intervention phase, baseline parameters were collected retrospectively. Then, VAS promotional campaign was carried out for six months and whilst this was done, the primary outcome of patient waiting time was measured by percentage of prescription served less than 30 minutes. A linear regression analysis was used to determine the impact of increased VAS uptake towards patient waiting time. Results: An increased in percentage of VAS registration (20.9% vs 35.7%, p<0.001) was observed after the promotional campaign. The mean percentage of prescription served less than 30 minutes increased from 83.2% SD=15.9 to 90.3% SD=11.5, p=0.001. After controlling for covariates, it was found that patient waiting time was affected by number of pharmacy technicians (b=-0.0349, 95%CI-0.0548 : -0.0150, p=0.001), number of pharmacy counters (b=0.1125, 95%CI 0.0631 : 0.1620, p<0.001), number of prescriptions (b=0.0008, 95%CI 0.0004 : 0.0011, p<0.001), and number of refill prescriptions (b=0.0004, 95%CI 0.0002 : 0.0007, p<0.001). The increased in percentage of VAS registration was associated with reduction in number of refill prescription (b=-2.9838, 95%CI -4.2289 : -1.7388, p<0.001). Conclusions: Patient waiting time at the Ambulatory Pharmacy improved with the increased in VAS registration. The impact of increased VAS uptake on patient waiting time resulted from reduction in refill prescriptions. Patient waiting time is influenced by number of pharmacy technicians, number of pharmacy counters, number of prescriptions and number of refill prescriptions (AU)

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