Time Intervals for Direct Versus Transfer Cases of Thrombectomy for Stroke in a Primarily Rural System of Care

Organizational Factors Determining Access to Reperfusion Therapies in Ischemic Stroke-Systematic Literature Review

BACKGROUND

After onset of acute ischemic stroke (AIS), there is a limited time window for delivering acute reperfusion therapies (ART) aiming to restore normal brain circulation. Despite its unequivocal benefits, the proportion of AIS patients receiving both types of ART, thrombolysis and thrombectomy, remains very low. The organization of a stroke care pathway is one of the main factors that determine timely access to ART. The knowledge on organizational factors influencing access to ART is sparce. Hence, we sought to systematize the existing data on the type and frequency of pre-hospital and in-hospital organizational factors that determine timely access to ART in patients with AIS.

METHODOLOGY

Literature review on the frequency and type of organizational factors that determine access to ART after AIS. Pubmed and Scopus databases were the primary source of data. OpenGrey and Google Scholar were used for searching grey literature. Study quality analysis was based on the Newcastle-Ottawa Scale.

RESULTS

A total of 128 studies were included. The main pre-hospital factors associated with delay or access to ART were medical emergency activation practices, pre-notification routines, ambulance use and existence of local/regional-specific strategies to mitigate the impact of geographic distance between patient locations and Stroke Unit (SU). The most common intra-hospital factors studied were specific location of SU and brain imaging room within the hospital, and the existence and promotion of specific stroke treatment protocols. Most frequent factors associated with increased access ART were periodic public education, promotion of hospital pre-notification and specific pre- and intra-hospital stroke pathways. In specific urban areas, mobile stroke units were found to be valid options to increase timely access to ART.

CONCLUSIONS

Implementation of different organizational factors and strategies can reduce time delays and increase the number of AIS patients receiving ART, with most of them being replicable in any context, and some in only very specific contexts.

Using network analysis to model the effects of the SARS Cov2 pandemic on acute patient care within a healthcare system

Consolidation of healthcare in the US has resulted in integrated organizations, encompassing large geographic areas, with varying services and complex patient flows. Profound changes in patient volumes and behavior have occurred during the SARS Cov2 pandemic, but understanding these across organizations is challenging. Network analysis provides a novel approach to address this. We retrospectively evaluated hospital-based encounters with an index emergency department visit in a healthcare system comprising 18 hospitals, using patient transfer as a marker of unmet clinical need. We developed quantitative models of transfers using network analysis incorporating the level of care provided (ward, progressive care, intensive care) during pre-pandemic (May 25, 2018 to March 16, 2020) and mid-pandemic (March 17, 2020 to March 8, 2021) time periods. 829,455 encounters were evaluated. The system functioned as a non-small-world, non-scale-free, dissociative network. Our models reflected transfer destination diversification and variations in volume between the two time points - results of intentional efforts during the pandemic. Known hub-spoke architecture correlated with quantitative analysis. Applying network analysis in an integrated US healthcare organization demonstrates changing patterns of care and the emergence of bottlenecks in response to the SARS Cov2 pandemic, consistent with clinical experience, providing a degree of face validity. The modelling of multiple influences can identify susceptibility to stress and opportunities to strengthen the system where patient movement is common and voluminous. The technique provides a mechanism to analyze the effects of intentional and contextual changes on system behavior.