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Background Traditional simulation-based education prioritizes participation in simulated scenarios. The educational impact of observation in simulation-based education compared with participation remains uncertain. Our objective was to compare the performances of observers and participants in a standardized simulation scenario. Methods We assessed learning differences between simulation-based scenario participation and observation using a convergent, parallel, quasi-experimental, mixed-methods study of 15 participants and 15 observers (N = 30). Fifteen first-year residents from six medical specialties were evaluated during a simulated scenario (cardiac arrest due to critical hyperkalemia). Evaluation included predefined critical actions and performance assessments. In the first exposure to the simulation scenario, participants and observers underwent a shared postevent debriefing with predetermined learning objectives. Three months later, a follow-up assessment using the same case scenario evaluated all 30 learners as participants. Wilcoxon signed rank and Wilcoxon rank sum tests were used to compare participants and observers at 3-month follow-up. In addition, we used case study methodology to explore the nature of learning for participants and observers. Data were triangulated using direct observations, reflective field notes, and a focus group. Results Quantitative data analysis comparing the learners' first and second exposure to the investigation scenario demonstrated participants' time to calcium administration as the only statistically significant difference between participant and observer roles (316 seconds vs. 200 seconds, p = 0.0004). Qualitative analysis revealed that both participation and observation improved learning, debriefing was an important component to learning, and debriefing closed the learning gap between observers and participants. Conclusions Participants and observers had similar performances in simulation-based learning in an isolated scenario of cardiac arrest due to hyperkalemia. Findings support current limited literature that observation should not be underestimated as an important opportunity to enhance simulation-based education. When paired with postevent debriefing, scenario observers and participants may reap similar educational benefits.

Supplemental Digital Content is available in the text., Importance: Risk prediction models for patients with suspected sepsis have been derived on and applied to various outcomes, including readily available outcomes such as hospital mortality and ICU admission as well as longer-term mortality outcomes that may be more important to patients. It is unknown how selecting different outcomes influences model performance in patients at risk for sepsis. Objectives: Evaluate the impact of outcome selection on risk model performance and weighting of individual predictor variables. Design, Setting, and Participants: We retrospectively analyzed adults hospitalized with suspected infection from January 2014 to September 2017 at 12 hospitals. Main Outcomes and Measures: We used routinely collected clinical data to derive logistic regression models for four outcomes: hospital mortality, composite ICU length of stay greater than 72 hours or hospital mortality, 30-day mortality, and 90-day mortality. We compared the performance of the models using area under the receiver operating characteristic curve and calibration plots. Results: Among 52,184 admissions, 2,030 (4%) experienced hospital mortality, 6,659 (13%) experienced the composite of hospital mortality or ICU length of stay greater than 72 hours, 3,417 (7%) experienced 30-day mortality, and 5,655 (11%) experienced 90-day mortality. Area under the receiver operating characteristic curves decreased when hospital-based models were applied to predict 30-day (hospital mortality = 0.88–0.85; –0.03, composite ICU length of stay greater than 72 hours or hospital mortality = 0.90–0.81; –0.09) and 90-day mortality (hospital mortality = 0.88–0.81; –0.07, composite ICU length of stay greater than 72 hours or hospital mortality = 0.90–0.76; –0.14; all p < 0.01). Models were well calibrated for derived (root-mean-square error = 5–15) but not alternate outcomes (root-mean-square error = 8–35). Conclusions and Relevance: Risk models trained to predict readily available hospital-based outcomes in suspected sepsis show poorer discrimination and calibration when applied to 30- and 90-day mortality. Interpretation and application of risk models for patients at risk of sepsis should consider these findings.

s Background Hospital mortality for patients with sepsis has recently declined, but sepsis survivors still suffer from significant long-term mortality and morbidity. There are limited data that support effective strategies to address post-discharge management of patients hospitalized with sepsis. Methods The Improving Morbidity during Post-Acute Care Transitions for Sepsis (IMPACTS) study is a pragmatic, randomized controlled trial at three hospitals within a single healthcare delivery system comparing clinical outcomes between sepsis survivors who receive usual care versus care delivered through the Sepsis Transition and Recovery (STAR) program. The STAR program includes a centrally located nurse navigator using telephone counseling and electronic health record-based support to facilitate best-practice post-sepsis care strategies for patients during hospitalization and the 30 days after hospital discharge, including post-discharge review of medications, evaluation for new impairments or symptoms, monitoring existing comorbidities, and palliative care referral when appropriate. Adults admitted through the Emergency Department with suspected infection (i.e., antibiotics initiated, bacterial cultures drawn) and deemed, by previously developed risk-stratification models, high risk for readmission or death are included. Eligible patients are randomly allocated 1:1 to either Arm 1, usual care or Arm 2, STAR. Planned enrollment is 708 patients during a 6-month period. The primary outcome is the composite of all-cause hospital readmissions and mortality assessed 30 days post discharge. Secondary outcomes include 30- and 90-day hospital readmissions, mortality, emergency department visits, acute care-free days alive, and acute care and total costs. Discussion This pragmatic evaluation provides the most comprehensive assessment to date of a strategy to improve delivery of recommended post-sepsis care. Trial registration ClinicalTrials.gov, NCT03865602. Registered retrospectively on 6 March 2019.

The analysis of data from social media sites can provide useful decision-making information for businesses; however, can small businesses with limited budgets and limited technical expertise compete in this new social media driven market? This study provides a proof of concept for increasing a company’s competitive knowledge through the use of the Strengths, Weaknesses, Opportunities, and Threats (SWOT) framework model by gathering qualitative data about the use of social media from employee interviews. By increasing the competitive knowledge through evaluating the results of the SWOT analysis, this small start-up company will have a strategic plan for increasing their competitive advantage. The authors present the results of the study in the form of practical recommendations for short-term and long-term implementation. Several of the shortterm and long-term recommendations are substantiated through prior research studies. Future research could include a follow-up study of this company using a SWOT framework tool or other methodologies to indicate what social media tools and strategies provide the most beneficial competitive knowledge for a small business, and why. Additionally, comparing the results from this study with a similar study of a different small start-up business could lead to the design of a model for other small businesses trying to increase their competitive knowledge through the effective use of social media.

The approach to interventional airway management must be consistent and disciplined. This chapter will describe one method to assess the airway and potentially predict which ones could be difficult and require additional interventions to secure and protect. In addition, assessments for difficult bag mask ventilation, laryngoscopy, extraglottic devices, and surgical interventions will be discussed.

One of the most stressful events that a provider will encounter in the ICU is the inability to secure an airway. This chapter will focus on the “Plan B”—what techniques and devices could be used if the traditional placement of an endotracheal tube is unsuccessful.