Enhancing Hospital-Wide Patient Flow to Reduce Emergency Department Crowding and Boarding.

INTRODUCTION: ED overcrowding and boarding is a global phenomenon that negatively affects patients, hospital staff, and hospital-wide operations. Poor patient flow has been identified as a major contributing factor to ED overcrowding and boarding, which is directly linked to negative patient outcomes. This project implemented a multidisciplinary rounding team that addressed barriers to patient flow in real time. By reducing the inpatient length of stay bed capacity will improve, which in turn will help alleviate ED boarding and overcrowding. METHODS: This before-and-after process improvement project took place on a 30-bed, inpatient medicine floor of a level-I trauma, tertiary, regional transfer center. Multidisciplinary rounding was used to improve care team communication and collaboration. Concepts from a Real-Time Demand Capacity model were used in this project to help develop a plan for capacity issues regarding bed supply and demand. Outcome variables included inpatient length of stay and ED boarding hours. RESULTS: Implementation of multidisciplinary rounding resulted in a statistically significant reduction of 0.83 days in the length of stay for patients on this floor. By increasing inpatient bed capacity, ED boarding hours for patients targeted to the 3000-medicine floor was reduced by an average of 8.83 hours per month, a reduction > 50% from baseline. DISCUSSION: Increasing inpatient bed capacity helps decrease ED access block, and contributes to reducing ED overcrowding. Implementing a daily multidisciplinary rounding structure on the inpatient floor helped hospital throughput by expediting discharges, which in turn created inpatient bed capacity.

Prehospital end-tidal carbon dioxide is predictive of death and massive transfusion in injured patients: An Eastern Association for Surgery of Trauma multicenter trial.

BACKGROUND: Prehospital identification of the injured patient likely to require emergent care remains a challenge. End-tidal carbon dioxide (ETCO2) has been used in the prehospital setting to monitor respiratory physiology and confirmation of endotracheal tube placement. Low levels of ETCO2 have been demonstrated to correlate with injury severity and mortality in a number of in-hospital studies. We hypothesized that prehospital ETCO2 values would be predictive of mortality and need for massive transfusion (MT) in intubated patients. METHODS: This was a retrospective multicenter trial with 24 participating centers. Prehospital, emergency department, and hospital values were collected. Receiver operating characteristic curves were created and compared. Massive transfusion defined as >10 U of blood in 6 hours or death in 6 hours with at least 1 U of blood transfused. RESULTS: A total of 1,324 patients were enrolled. ETCO2 (area under the receiver operating characteristic curve [AUROC], 0.67; confidence interval [CI], 0.63-0.71) was better in predicting mortality than shock index (SI) (AUROC, 0.55; CI, 0.50-0.60) and systolic blood pressure (SBP) (AUROC, 0.58; CI, 0.53-0.62) (p < 0.0005). Prehospital lowest ETCO2 (AUROC, 0.69; CI, 0.64-0.75), SBP (AUROC, 0.75; CI, 0.70-0.81), and SI (AUROC, 0.74; CI, 0.68-0.79) were all predictive of MT. Analysis of patients with normotension demonstrated lowest prehospital ETCO2 (AUROC, 0.66; CI, 0.61-0.71), which was more predictive of mortality than SBP (AUROC, 0.52; CI, 0.47-0.58) or SI (AUROC, 0.56; CI, 0.50-0.62) (p < 0.001). Lowest prehospital ETCO2 (AUROC, 0.75; CI, 0.65-0.84), SBP (AUROC, 0.63; CI, 0.54-0.74), and SI (AUROC, 0.64; CI, 0.54-0.75) were predictive of MT in normotensive patients. ETCO2 cutoff for MT was 26 mm Hg. The positive predictive value was 16.1%, and negative predictive value was high at 98.1%. CONCLUSION: Prehospital ETCO2 is predictive of mortality and MT. ETCO2 outperformed traditional measures such as SBP and SI in the prediction of mortality. ETCO2 may outperform traditional measures in predicting need for transfusion in occult shock. LEVEL OF EVIDENCE: Diagnostic test, level III.

Prevalence of IgG antibodies against the severe acute respiratory syndrome coronavirus-2 among healthcare workers in Tennessee during May and June, 2020.

SARS-CoV-2 seroprevalence was low (<1%) in this large population of healthcare workers (HCWs) across the state of Tennessee (n=11,787) in May-June 2020. Among those with PCR results, 81.5% of PCR and antibody test results were concordant. SARS-CoV-2 seroprevalence was higher among HCWs working in high-community-transmission regions and among younger workers. IMPORTANCE: These results may be seen as a baseline assessment of SARS-CoV-2 seroprevalence among HCWs in the American South during a period of growth, but not yet saturation, of infections among susceptible populations. In fact, this period of May-June 2020 was marked by the extension of renewed and sustained community-wide transmission after mandatory quarantine periods expired in several more populous regions of Tennessee. Where community transmission remains low, HCWs may still be able to effectively mitigate SARS-CoV-2 transmission, preserving resources for populations at high risk of severe disease, and these sorts of data help highlight such strategies.

Risk stratification in chest pain patients undergoing nuclear stress testing: the Erlanger Stress Score.

BACKGROUND: Studies have individually reported the relationship of age, cardiac risk factors, and history of preexisting coronary artery disease (CAD) for predicting acute coronary syndromes in chest pain patients undergoing cardiac stress testing. In this study, we investigate the interplay of all these factors on the incidence of acute coronary syndromes to develop a tool that may assist physicians in the selection of appropriate chest pain patients for stress testing. METHODS: Retrospective analysis of a prospectively acquired database of consecutive chest pain patients undergoing nuclear stress testing. Backward stepwise logistic regression was used to develop a model for predicting risk of 30-day acute coronary events (ACE) using information obtained from age, sex, cardiac risk factors, and history of preexisting CAD. RESULTS: A total of 800 chest pain patients underwent nuclear stress testing. ACE occurred in 74 patients (9.3%). Logistic regression analysis found only 6 factors predictive of ACE: age, male sex, preexisting CAD, diabetes, and hyperlipidemia. Area under the receiver operator characteristic curve of this model for predicting ACE was 0.767 (95% confidence interval, 0.719-0.815). There were no cases of ACE in the 173 patients with predicted probability estimates ≤2.5% (95% confidence interval, 0%-2.1%). CONCLUSIONS: A regression model using age, sex, preexisting CAD, diabetes, and hyperlipidemia is predictive of 30-day ACE in chest pain patients undergoing nuclear stress testing. Prospective studies need to be performed to determine whether this model can assist physicians in the selection of appropriate low-to-intermediate risk chest pain patients for nuclear stress testing.