Emergency Department access and flow: Complex systems need complex approaches

The work of patient flow management: A grounded theory study of emergency nurses

INTRODUCTION

The current crisis of emergency department overcrowding demands novel approaches. Despite a growing body of patient flow literature, there is little understanding of the work of emergency nurses. This study explored how emergency nurses perform patient flow management.

METHODS

Constructivist grounded theory and situational analysis methodologies were used to examine the work of emergency nurses. Twenty-nine focus groups and interviews of 27 participants and 64 hours of participant observation across four emergency departments were conducted between August 2022 and February 2023. Data were analyzed using coding, constant comparative analysis, and memo-writing to identify emergent themes and develop a substantive theory.

FINDINGS

Patient flow management is the work of balancing department resources and patient care to promote collective patient safety. Patient safety arises when care is ethical, efficient, and appropriately weighs care timeliness and comprehensiveness. Emergency nurses use numerous patient flow management strategies that can be organized into five tasks: information gathering, continuous triage, resource management, throughput management, and care oversight.

CONCLUSION

Patient flow management is complex, cognitively demanding work. The central contribution of this paper is a theoretical model that reflects emergency nurses'conceptualizations, discourse, and priorities. This model lays the foundation for knowledge sharing, training, and practice improvement.

Inter hospital external validation of interpretable machine learning based triage score for the emergency department using common data model

Emergency departments (ED) are complex, triage is a main task in the ED to prioritize patient with limited medical resources who need them most. Machine learning (ML) based ED triage tool, Score for Emergency Risk Prediction (SERP), was previously developed using an interpretable ML framework with single center. We aimed to develop SERP with 3 Korean multicenter cohorts based on common data model (CDM) without data sharing and compare performance with inter-hospital validation design. This retrospective cohort study included all adult emergency visit patients of 3 hospitals in Korea from 2016 to 2017. We adopted CDM for the standardized multicenter research. The outcome of interest was 2-day mortality after the patients' ED visit. We developed each hospital SERP using interpretable ML framework and validated inter-hospital wisely. We accessed the performance of each hospital's score based on some metrics considering data imbalance strategy. The study population for each hospital included 87,670, 83,363 and 54,423 ED visits from 2016 to 2017. The 2-day mortality rate were 0.51%, 0.56% and 0.65%. Validation results showed accurate for inter hospital validation which has at least AUROC of 0.899 (0.858-0.940). We developed multicenter based Interpretable ML model using CDM for 2-day mortality prediction and executed Inter-hospital external validation which showed enough high accuracy.

Non-clinical intuitions and adaptive heuristics in emergency care: A scoping review

BACKGROUND

Across a range of fields, including healthcare, heuristics are typically conceived as a source of bias and systematic error. However, research across the psychological and management sciences shows that intuition and heuristics are also vital sources of adaptive decision strategies, especially in complex, uncertain environments. The complexity of the emergency care environment marks this environment as one in which non-clinical intuitions and heuristics are likely to emerge and function as adaptive decision strategies. The aim of this study was to map and contextualize what is known about leadership and non-clinical intuitions and heuristics in emergency care.

METHODS

Based on a systematic search of the Pubmed, Scopus, Web of Science, MEDLINE and CINAHL electronic databases, we conducted a scoping review to map what is known about leadership and non-clinical intuitions and adaptive heuristics in emergency care.

RESULTS

Of the 1219 articles retrieved, 9 met the inclusion criteria. Our review revealed four key findings. First, intuitions are used to make judgments about patients, caring for patients, and coordinating with colleagues. Second, although non-clinical intuitions are documented, non-clinical heuristics are rarely studied. Third, the literature is focused on nurses and silent on the use of non-clinical intuition and heuristics among medical doctors. Finally, professional cultures influence clinicians' use of intuitive sense- and decision-making.

CONCLUSION

This review highlights the dearth of research into non-clinical intuitions and heuristics in emergency care. Understood in the context of insights from the psychological and management sciences about intuitions and 'smart' heuristics as adaptive decision strategies, our findings point to new frontiers of research into leadership in emergency care.

How an emergency department is organized to provide opioid-specific harm reduction and facilitators and barriers to harm reduction implementation: a systems perspective

BACKGROUND

The intersection of dual public health emergencies-the COVID-19 pandemic and the drug toxicity crisis-has led to an urgent need for acute care based harm reduction for unregulated opioid use. Emergency Departments (EDs) as Complex Adaptive Systems (CASs) with multiple, interdependent, and interacting elements are suited to deliver such interventions. This paper examines how the ED is organized to provide harm reduction and identifies facilitators and barriers to implementation in light of interactions between system elements.

METHODS

Using a case study design, we conducted interviews with Emergency Physicians (n = 5), Emergency Nurses (n = 10), and clinical leaders (n = 5). Nine organizational policy documents were also collected. Interview data were analysed using a Reflexive Thematic Analysis approach. Policy documents were analysed using a predetermined coding structure pertaining to staffing roles and responsibilities and the interrelationships therein for the delivery of opioid-specific harm reduction in the ED. The theory of CAS informed data analysis.

RESULTS

An array of system agents, including substance use specialist providers and non-specialist providers, interacted in ways that enable the provision of harm reduction interventions in the ED, including opioid agonist treatment, supervised consumption, and withdrawal management. However, limited access to specialist providers, when coupled with specialist control, non-specialist reliance, and concerns related to safety, created tensions in the system that hinder harm reduction provision with resulting implications for the delivery of care.

CONCLUSIONS

To advance harm reduction implementation, there is a need for substance use specialist services that are congruent with the 24 h a day service delivery model of the ED, and for organizational policies that are attentive to discourses of specialized practice, hierarchical relations of power, and the dynamic regulatory landscape. Implementation efforts that take into consideration these perspectives have the potential to reduce harms experienced by people who use unregulated opioids, not only through overdose prevention and improving access to safer opioid alternatives, but also through supporting people to complete their unique care journeys.