A Time-Motion Study of Emergency and Hospitalist Physicians in a Community Hospital Setting

Introduction: Research has shown that low physician work satisfaction correlates with burnout. Having sufficient time at the patient’s bedside is one element that contributes to work satisfaction. Interruptions, on the other hand, have been implicated as a potential cause of both worker dissatisfaction and clinical error. Better understanding how direct patient care and interruptions affect physician satisfaction may aid in developing future interventions to reduce burnout and improve patient safety. Methods: We conducted an observational, time-motion study to assess how physicians spend their time and correlated these findings to physician satisfaction. This study was conducted in July 2020 (7/1/20 - 7/15/20) at a 591-bed community hospital. A total of 114 emergency medicine (EM) physicians and hospitalists were eligible for participation. Participants were recruited by email. Two trained medical students categorized and recorded the activities of 13 EM and 8 hospitalist physicians and documented the number of interruptions they experienced. An anonymous survey was also employed to investigate participants’ perceptions about interruptions and how they spend their time. We compared the responses from the subjective survey to the objective data to identify activities that may positively or negatively impact participant satisfaction. Results: 18.4% of all eligible physicians participated in the study. In summary, our study showed that EM and hospitalist physicians dedicate roughly double the amount of time to indirect patient care (56.3%) compared to direct patient care (25.8%). EM physicians had more than twice the number of interruptions as hospitalists (every 4.4 minutes vs. every 11.3 minutes). From our survey results, we found no statistically significant difference between the perceived and observed proportion of time spent on direct and indirect patient care for EM physicians (p = 0.62 direct; 0.21 indirect) or hospitalists (p = 0.82 direct; 0.69 indirect). However, there was a statistically significant difference between perceived (overestimated) and observed number of interruptions reported by EM physicians (p = 0.02). Conclusion: The observational data along with the survey results indicate a desire to reduce indirect patient care and increase time at the bedside — suggesting that interventions that target this discrepancy may increase physician work satisfaction and therefore decrease burnout. Additionally, we found that EM physicians far overestimate the actual number of interruptions they experience —however, EM does still engender more than double the interruptions as hospitalists encounter, despite experiencing similar percentages of direct and indirect patient care

Extracellular microRNAs in blood differentiate between ischaemic and haemorrhagic stroke subtypes.

Rapid identification of patients suffering from cerebral ischaemia, while excluding intracerebral haemorrhage, can assist with patient triage and expand patient access to chemical and mechanical revascularization. We sought to identify blood-based, extracellular microRNAs 15 (ex-miRNAs) derived from extracellular vesicles associated with major stroke subtypes using clinical samples from subjects with spontaneous intraparenchymal haemorrhage (IPH), aneurysmal subarachnoid haemorrhage (SAH) and ischaemic stroke due to cerebral vessel occlusion. We collected blood from patients presenting with IPH (n = 19), SAH (n = 17) and ischaemic stroke (n = 21). We isolated extracellular vesicles from plasma, extracted RNA cargo, 20 sequenced the small RNAs and performed bioinformatic analyses to identify ex-miRNA biomarkers predictive of the stroke subtypes. Sixty-seven miRNAs were significantly variant across the stroke subtypes. A subset of exmiRNAs differed between haemorrhagic and ischaemic strokes, and LASSO analysis could distinguish SAH from the other subtypes with an accuracy of 0.972 ± 0.002. Further analyses predicted 25 miRNA classifiers that stratify IPH from ischaemic stroke with an accuracy of 0.811 ± 0.004 and distinguish haemorrhagic from ischaemic stroke with an accuracy of 0.813 ± 0.003. Blood-based, ex-miRNAs have predictive value, and could be capable of distinguishing between major stroke subtypes with refinement and validation. Such a biomarker could one day aid in the triage of patients to expand the pool eligible for effective treatment

Extracellular microRNAs in blood differentiate between ischaemic and haemorrhagic stroke subtypes

Rapid identification of patients suffering from cerebral ischaemia, while excluding intracerebral haemorrhage, can assist with patient triage and expand patient access to chemical and mechanical revascularization. We sought to identify blood-based, extracellular microRNAs 15 (ex-miRNAs) derived from extracellular vesicles associated with major stroke subtypes using clinical samples from subjects with spontaneous intraparenchymal haemorrhage (IPH), aneurysmal subarachnoid haemorrhage (SAH) and ischaemic stroke due to cerebral vessel occlusion. We collected blood from patients presenting with IPH (n = 19), SAH (n = 17) and ischaemic stroke (n = 21). We isolated extracellular vesicles from plasma, extracted RNA cargo, 20 sequenced the small RNAs and performed bioinformatic analyses to identify ex-miRNA biomarkers predictive of the stroke subtypes. Sixty-seven miRNAs were significantly variant across the stroke subtypes. A subset of exmiRNAs differed between haemorrhagic and ischaemic strokes, and LASSO analysis could distinguish SAH from the other subtypes with an accuracy of 0.972 +/- 0.002. Further analyses predicted 25 miRNA classifiers that stratify IPH from ischaemic stroke with an accuracy of 0.811 +/- 0.004 and distinguish haemorrhagic from ischaemic stroke with an accuracy of 0.813 +/- 0.003. Blood-based, ex-miRNAs have predictive value, and could be capable of distinguishing between major stroke subtypes with refinement and validation. Such a biomarker could one day aid in the triage of patients to expand the pool eligible for effective treatment.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial

SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication

BoF: Establishing a AU-NZ bioinformatics software accelerator program

The creation of quality and performant bioinformatics software is a growing need as the field of data-driven omics continues to rapidly grow and expand. A proposed response to this challenge is the creation of a software accelerator program that supports the development, optimisation and sharing of software for bioinformatics, by providing the authors with expertise, best practice guidelines, and access to HPC and cloud facilities. This idea arises from the existing Australian BioCommons Leadership Share (ABLeS) program, by providing environments on peak compute systems to test, scale, debug and enhance bioinformatics software (tools and workflows) in lock step with support and expertise in making software findable, understandable and citable (i.e. FAIR). The ultimate vision is to accelerate the transition towards a culture of best practice bioinformatics at scale on peak infrastructures. In this BoF we will collectively discuss and shape this proposed program, by exploring what the RSE community considers to be critical, and how we might share the outcomes of this effort across infrastructure partners in the region and beyond. These observations are broadly applicable to all domains, and we invite people of diverse domain backgrounds to the BoF. This concept is being actively pursued as a collaborative effort by the Australian BioCommons, Pawsey Supercomputing Centre, New Zealand eScience Infrastructure and the National Computational Infrastructure

Wait Time for Curative Intent Radio Frequency Ablation is Associated with Increased Mortality in Patients with Early Stage Hepatocellular Carcinoma

Introduction: Radiofrequency ablation (RFA) is a recommended curative intent treatment option for patients with early stage hepa-tocellular carcinoma (HCC). We investigated if wait times for RFA were associated with residual tumor, tumor recurrence, need for liver transplantation, or death. Material and methods: We conducted a retrospective study of patients diagnosed with HCC between January 2010 and December 2013 presenting to University Health Network (UHN) in Toronto, Canada. All patients receiving curative intent RFA for HCC were included. Multivariable Cox regression was used to determine if wait times were associated with clinical outcomes. Results: 219 patients were included in the study. 72.6% were male and the median age was 62.7 years (IQR 55.6-71). Median tumor size at diagnosis was 21.5 mm (IQR 17-26); median MELD was 8.7 (IQR 7.2-11.4) and 57.1% were Barcelona stage 0. The cause of liver disease was viral hepatitis in 73.5% (Hepatitis B and C). The median time from HCC diagnosis to RFA treatment was 96 days (IQR 75-139). In multivariate analysis, wait time was not associated with requiring liver transplant or tumor recurrence, however, each incremental 30-day wait time was associated with an increased risk of residual tumor (HR = 1.09; 95% CI 1.01-1.19; p = 0.033) as well as death (HR = 1.23; 95% CI 1.11-1.36; p ≤ 0.001). Conclusion: Incremental 30-day wait times are associated with a 9% increased risk of residual tumor and a 23% increased risk of death. We have identified system gaps where quality improvement measures can be implemented to reduce wait times and allocate resources for future RFA treatment, which may improve both quality and efficiency of HCC care