Lost in Translation: A Standardized, Interdepartmental Approach to Improve the Safety of Inpatient Transitions of Care

AIM: During the 2016-2017 academic year physician perception of favorability regarding inpatient interunit handoffs will meet the national HSOPS benchmark without negatively impacting patient bed flow. All ACGME training programs at Thomas Jefferson University Hospital will expose their new trainees to standardized handoff training during orientation in June 2017 as well as adapt a framework for monitoring trainee compliance and proficiency.https://jdc.jefferson.edu/patientsafetyposters/1028/thumbnail.jp

Understanding Differences in Medical Versus Surgical Patients Alerted by the Modified Early Warning Score (MEWS) at Jefferson Hospital

An Early Warning Score (EWS) is a risk-management tool to identify patients experiencing clinical deterioration early, therefore allowing timely treatment to occur. Although EWS scores are recommended for all in-patients, more data is available for patients under general medical services compared to surgical services. This study aims to understand differences between medical versus surgical in-patients who receive a red alert from the Modified Early Warning Score (MEWS) at Jefferson hospital. Patients who received a red MEWS alert during admission and discharged between June 2017 to March 2018 (N=812) were categorized as medical or surgical patients. Patient characteristics were compared using an independent samples t-test (age, alert count) or chi-square test (sex, race, admission source, insurance). Patient outcomes were compared using a binary logistic regression (in-hospital mortality, RRT, sepsis diagnosis, ICU transfer, intubation, discharge to hospice) or a Cox regression model (length of stay), controlling for age, sex, and race. Compared to medical patients, surgical patients were younger by 2.7 years (p=0.026) and more likely to have a Commercial and/or Medicare category of insurance (OR=1.568, p=0.005). Surgical patients were more likely to have ICU transfer (OR=1.487, p=0.013) and intubation post-alert (OR=2.470, p=0.006), while less likely to be discharged early (HR=0.675,

To Fib or Not to Fib: Misdiagnosis of Atrial Fibrillation on Telemetry Case Presentation and Root Cause Analysis

Case presentation, current practices of telemetry management, root cause analysis, goals for improvement, proposed intervention and next steps

Taking the e out of Night MARe Rotation: Uncloaking Ghost Admissions via Teletracking and Reducing Paper Fatigue

Goal: To improve communication at admission for patients admitted from non-ED locations so that patient care delays are minimized and provider frustration decreases.https://jdc.jefferson.edu/patientsafetyposters/1015/thumbnail.jp

Easy Identification of Missed DVT Prophylaxis-A Chance for Intervention

Goal: To minimize the number of missed or refused medications for inpatients so that adverse patient events such as PE or DVT are prevented SMART AIM: Within 3 months of initiating an EMR based electronic identification system for refused and missed medications, we will decrease the rate at which DVT prophylaxis was ordered however not eventually administered by 50%.https://jdc.jefferson.edu/patientsafetyposters/1014/thumbnail.jp

At the Leading Edge of Change: Creation of the Housestaff Quality and Safety Leadership Council

Background: The ACGME Clinical Learning Environment Review (CLER) is driving a national re-evaluation of the engagement and alignment of housestaff in institutional Quality and Safety. In 2008, the concept of a housestaff quality and safety committee was born, as a means of driving practice change Our CLER data suggested that we need a similar councilhttps://jdc.jefferson.edu/patientsafetyposters/1004/thumbnail.jp

Getting Engaged: Efforts to Increase Housestaff Event Reporting

Background: Residents traditionally are under-engaged in event reporting through institutional channels. The ACGME Clinical Learning Environment Review prioritizes this issue, and is establishing national benchmarks. In 2015 the Housestaff Quality and Safety Leadership Council selected Increasing Error Reporting as their clinical quality initiative.https://jdc.jefferson.edu/patientsafetyposters/1010/thumbnail.jp

Standardizing Postoperative Handoffs Using the Evidence-Based IPASS Framework Improves Handoff Communication for Postoperative Neurosurgical Patients in the Neuro-Intensive Care Unit

Aims for Improvement Within one year of initiation of the process improvement plan, we wanted to improve: Direct communication of airway and hemodynamic concerns Direct communication of operative events, complications, and perioperative management goals. Attendance at postoperative handoffs Confirmation of information by receiving teams Staff perceptions of handoff efficacy and teamwork

Characterization of the Fecal Microbiome from Non-Human Wild Primates Reveals Species Specific Microbial Communities

BACKGROUND: Host-associated microbes comprise an integral part of animal digestive systems and these interactions have a long evolutionary history. It has been hypothesized that the gastrointestinal microbiome of humans and other non-human primates may have played significant roles in host evolution by facilitating a range of dietary adaptations. We have undertaken a comparative sequencing survey of the gastrointestinal microbiomes of several non-human primate species, with the goal of better understanding how these microbiomes relate to the evolution of non-human primate diversity. Here we present a comparative analysis of gastrointestinal microbial communities from three different species of Old World wild monkeys. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed fecal samples from three different wild non-human primate species (black-and-white colobus [Colubus guereza], red colobus [Piliocolobus tephrosceles], and red-tailed guenon [Cercopithecus ascanius]). Three samples from each species were subjected to small subunit rRNA tag pyrosequencing. Firmicutes comprised the vast majority of the phyla in each sample. Other phyla represented were Bacterioidetes, Proteobacteria, Spirochaetes, Actinobacteria, Verrucomicrobia, Lentisphaerae, Tenericutes, Planctomycetes, Fibrobacateres, and TM7. Bray-Curtis similarity analysis of these microbiomes indicated that microbial community composition within the same primate species are more similar to each other than to those of different primate species. Comparison of fecal microbiota from non-human primates with microbiota of human stool samples obtained in previous studies revealed that the gut microbiota of these primates are distinct and reflect host phylogeny. CONCLUSION/SIGNIFICANCE: Our analysis provides evidence that the fecal microbiomes of wild primates co-vary with their hosts, and that this is manifested in higher intraspecies similarity among wild primate species, perhaps reflecting species specificity of the microbiome in addition to dietary influences. These results contribute to the limited body of primate microbiome studies and provide a framework for comparative microbiome analysis between human and non-human primates as well as a comparative evolutionary understanding of the human microbiome