Communication and bed reservation: Decreasing the length of stay for emergency department trauma patients

Difficult Intravenous Access Requiring Ultrasound in the Emergency Department: Associations With Delays in Care and Areas for Quality Improvement

Background Patients with difficult intravenous access (DIVA) requiring ultrasound-guided intravenous (USGIV) access have been associated with delays in treatment, imaging, and disposition in academic emergency department (ED) patient populations. Our objective in this study was to characterize differences in time to intravenous access, imaging, and disposition between patients with DIVA versus those without DIVA requiring USGIV access in a community ED while also assessing for DIVA-associated comorbidities. Methods A cross-sectional, observational analysis was performed on admitted ED patients evaluated from September 2 to September 31, 2022, at a community ED. Patients with DIVA were defined as patients with two failed attempts at traditional intravenous placement. These patients require USGIV placement per institutional protocol. Patients younger than 18 years of age, trauma admissions, repeated visits from the same patient, patients with missing data, and direct hospital admissions were excluded. Continuous variables were recorded with medians and included ED throughput measures of time to vascular access, contrast CT imaging, and disposition. Differences in median times between DIVA patients versus non-DIVA patients were assessed with the Mann-Whitney U-test. Categorical data involving comorbidities were reported as percentages, and differences in proportions between DIVA versus non-DIVA patients were assessed via chi-square tests. Multivariate logistic regression analysis evaluated for correlations between DIVA and times to access, contrast CT imaging, disposition, and significant covariates while adjusting for demographic information. Results A total of 1250 patients were included in this investigation (5.8% associated with DIVA requiring USGIV access). The median age of all subjects was 69 (interquartile range = 58, 79) with no significant difference between the DIVA and non-DIVA groups. Patients with DIVA were more likely to be female in comparison to patients without DIVA (65.3% and 51.2%, respectively, p < 0.05). Patients with a history of end-stage renal disease (ESRD) (p < 0.001), intravenous drug use (IVDU) (p < 0.001), and venous thromboembolism (p < 0.05) had statistically significant associations with DIVA. On regression analysis, patients with DIVA were more likely to have a history of ESRD with an odds ratio (OR) of 3.56 (95% confidence interval (CI): 1.62-7.81) and a history of IVDU with an OR of 14.29 (95% CI: 5.17-39.54). Patients with DIVA were associated with statistically significant greater median times to vascular access, contrast CT imaging, and disposition (p < 0.001 for time to access and disposition and p < 0.01 for time to contrast CT imaging). Conclusion In this study, DIVA cases requiring USGIV access were positively associated with significantly longer times to access, contrast CT imaging, and disposition compared to patients without DIVA at our community ED. Comorbidities such as IVDU and ESRD had statistically significant associations with DIVA requiring USGIV access.

Prolonged length of stay and its associated factors at adult emergency department in amhara region comprehensive specialized hospitals, northwest Ethiopia

Background

Prolonged length of stay at the emergency department interferes with the main goal of emergency care and results in adverse patient outcomes like nosocomial infection, dissatisfaction, morbidity, and mortality. Despite this, little is known about the length of stay and the factors that influence it in Ethiopia’s emergency department.

Methods

An institution-based cross-sectional study was conducted on 495 patients admitted at Amhara region comprehensive specialized hospitals emergency department from May 14 to June 15/2022. A systematic random sampling was employed to select study participants. A pretested structured interview-based questionnaire was used to collect data by using Kobo toolbox software. SPSS version 25 was used for data analysis. Bi-variable logistic regression analysis was carried out to select variables with P-value < 0.25. The significance of association was interpreted using an Adjusted Odds Ratio with a 95% confidence interval. Variables with P-value < 0.05 in the multivariable logistic regression analysis were inferred to be significantly associated with length of stay.

Result

Out of 512 enrolled participants, 495 were participated with a response rate of 96.7%. The prevalence of prolonged length of stay in the adult emergency department was 46.5% (95%CI: 42.1, 51.1). Lack of insurance (AOR: 2.11; 95% CI: 1.22, 3.65), non-communicative presentation (AOR: 1.98; 95% CI: 1.07, 3.68), delayed consultation (AOR: 9.5; 95% CI: 5.00, 18.03), overcrowding (AOR: 4.98; 95% CI: 2.13, 11.68), and shift change experience (AOR: 3.67; 95% CI: 1.30, 10.37) were significantly associated with prolonged length of stay.

Conclusion

The result of this study is found to be high based on Ethiopian target emergency department patient length of stay. Lack of insurance, presentation without communication, delayed consultation, overcrowding, and shift change experience were significant factors for prolonged emergency department length of stay. Therefore, interventions like expansion of organizational setup are needed to decrease the length of stay to an acceptable level.

Realist analysis of streaming interventions in emergency departments

Background

Several of the many emergency department (ED) interventions intended to address the complex problem of (over)crowding are based on the principle of streaming: directing different groups of patients to different processes of care. Although the theoretical basis of streaming is robust, evidence on the effectiveness of these interventions remains inconclusive.

Methods

This qualitative research, grounded in the population-capacity-process model, sought to determine how, why and under what conditions streaming interventions may be effective. Data came from a broader study exploring patient flow strategies across Western Canada through in-depth interviews with managers at all levels. We undertook realist analysis of interview data from the 98 participants who discussed relevant interventions (fast-track/minor treatment areas, rapid assessment zones, diverse short-stay units), focusing on their explanations of initiatives’ perceived outcomes.

Results

Essential features of streaming interventions included separation of designated populations (population), provision of dedicated space and resources (capacity) and rapid cycle time (process). These features supported key mechanisms of impact: patients wait only for services they need; patient variability is reduced; lag time between steps is eliminated; and provider attitude change promotes prompt discharge. Conversely, reported failures usually involved neglect of one of these dimensions during intervention design and/or implementation. Participants also identified important contextual barriers to success, notably lack of outflow sites and demand outstripping capacity. Nonetheless, failure was more commonly attributed to intervention flaws than to context factors.

Conclusions

While streaming interventions have the potential to reduce crowding, a theory-based intervention relies on its implementers’ adherence to the theory. Streaming interventions cannot be expected to yield the desired results if operationalised in a manner incongruent with the theory on which they are supposedly based.

Prolonged hospital length of stay in pediatric trauma: a model for targeted interventions

BACKGROUND

In this study, trauma-specific risk factors of prolonged length of stay (LOS) in pediatric trauma were examined. Statistical and machine learning models were used to proffer ways to improve the quality of care of patients at risk of prolonged length of stay and reduce cost.

METHODS

Data from 27 hospitals were retrieved on 81,929 hospitalizations of pediatric patients with a primary diagnosis of trauma, and for which the LOS was >24 h. Nested mixed effects model was used for simplified statistical inference, while a stochastic gradient boosting model, considering high-order statistical interactions, was built for prediction.

RESULTS

Over 18.7% of the encounters had LOS >1 week. Burns and corrosion and suspected and confirmed child abuse are the strongest drivers of prolonged LOS. Several other trauma-specific and general pediatric clinical variables were also predictors of prolonged LOS. The stochastic gradient model obtained an area under the receiver operator characteristic curve of 0.912 (0.907, 0.917).

CONCLUSIONS

The high performance of the machine learning model coupled with statistical inference from the mixed effects model provide an opportunity for targeted interventions to improve quality of care of trauma patients likely to require long length of stay.

IMPACT

Targeted interventions on high-risk patients would improve the quality of care of pediatric trauma patients and reduce the length of stay. This comprehensive study includes data from multiple hospitals analyzed with advanced statistical and machine learning models. The statistical and machine learning models provide opportunities for targeted interventions and reduction in prolonged length of stay reducing the burden of hospitalization on families.

Emergency Department Boarding of Non-Trauma Patients Adversely Affects Trauma Patient Length of Stay

Introduction Emergency Department (ED) boarding delays initiation of time-sensitive protocols for trauma patients and makes them susceptible to increased mortality and morbidity. In this study, we compared the ED boarding times of non-trauma patients and ED length of stay (LOS) of trauma patients. Methods This was a single-center retrospective cohort study in a Level 1 trauma center. The median boarding time among non-trauma patients and ED LOS among trauma patients was determined by month between the period of April 2018 to March 2019. Linear regression and Pearson correlation coefficient were used to express the magnitude and direction of the relationship between these two variables. Results During the study period, the mean number of non-trauma patients admitted in our ED per month was 1,154 and trauma patients was 89. The mean of the median boarding time per month for non-trauma patients was 76 minutes, and the mean of the median ED LOS per month for trauma patients was 198 minutes. There was a significant positive correlation between boarding time for non-trauma patients and ED LOS for trauma patients (Pearson correlation coefficient: 0.73; p = 0.007). Conclusion The long boarding times for non-trauma patients is associated with ED LOS for trauma patients, indicating that the total patient volume in the hospital contributes to the trauma patient's stay in the ED. Thus, ED LOS of trauma patients can be minimized by improving overall ED and hospital flow, including non-trauma patients.

Methodological Approaches to Support Process Improvement in Emergency Departments: A Systematic Review

The most commonly used techniques for addressing each Emergency Department (ED) problem (overcrowding, prolonged waiting time, extended length of stay, excessive patient flow time, and high left-without-being-seen (LWBS) rates) were specified to provide healthcare managers and researchers with a useful framework for effectively solving these operational deficiencies. Finally, we identified the existing research tendencies and highlighted opportunities for future work. We implemented the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to undertake a review including scholarly articles published between April 1993 and October 2019. The selected papers were categorized considering the leading ED problems and publication year. Two hundred and three (203) papers distributed in 120 journals were found to meet the inclusion criteria. Furthermore, computer simulation and lean manufacturing were concluded to be the most prominent approaches for addressing the leading operational problems in EDs. In future interventions, ED administrators and researchers are widely advised to combine Operations Research (OR) methods, quality-based techniques, and data-driven approaches for upgrading the performance of EDs. On a different tack, more interventions are required for tackling overcrowding and high left-without-being-seen rates.