
doi: 10.1111/ane.13343
pmid: 32882056
Clinical outcomes of acute ischaemic stroke patients have significantly improved with the advent of reperfusion therapy. However, time continues to be a critical factor. Reducing treatment delays by improving workflows can improve the efficacy of acute reperfusion therapy. Systems-based approaches have improved in-hospital temporal parameters, maximizing the utility of reperfusion therapies and improving clinical benefit to patients. However, studies aimed at optimizing and hence reducing treatment delays in emergency department (ED) settings are limited. The aim of this article is to discuss existing systems-based approaches to optimize ED acute stroke workflows and its value in reducing treatment delays and identify gaps in existing workflows that need optimization. Identifying gaps in acute stroke workflow, variations in processes and challenges in implementation, in the in-hospital settings, is essential for systems-based interventions to be effective in delivering improved outcomes for patients with acute ischaemic stroke.
Stroke, Reperfusion, Humans, Emergency Service, Hospital, Brain Ischemia, Quality of Health Care, Workflow
Stroke, Reperfusion, Humans, Emergency Service, Hospital, Brain Ischemia, Quality of Health Care, Workflow
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 40 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
