No Evidence of the “Weekend Effect” in the Northern New South Wales Telestroke Network

Abstract

Background: Admission outside normal business hours has been associated with prolonged door-to-treatment times and poorer patient outcomes, the so called "weekend effect. " This is the first examination of the weekend effect in a telestroke service that uses multi-modal computed tomography. Aims: To examine differences in workflow and triage between in-hours and out-of-hours calls to a telestroke service. Methods: All patients assessed using the Northern New South Wales (N-NSW) telestroke service from April 2013 to January 2019 were eligible for inclusion (674 in total; 539 with complete data). The primary outcomes measured were differences between in-hours and out-of-hours in door-to-call-to-decision-to-needle times, differences in the proportion of patients confirmed to have strokes or of patients selected for reperfusion therapies or patients with a modified Rankin Score (mRS ≤ 2) at 90 days. Results: There were no significant differences between in-hours and out-of-hours in any of the measured times, nor in the proportions of patients confirmed to have strokes (67.6 and 69.6%, respectively, p = 0.93); selected for reperfusion therapies (22.7 and 22.6%, respectively, p = 0.56); or independent at 3 months (34.8 and 33.6%, respectively, p = 0.770). There were significant differences in times between individual hospitals, and patient presentation more than 4.5 h after symptom onset was associated with slower times (21 minute delay in door-to-call, p = 0.002 and 22 min delay in door-to-image, p = 0.001). Conclusions: The weekend effect is not evident in the Northern NSW telestroke network experience, though this study did identify some opportunities for improvement in the delivery of acute stroke therapies.

Virtual Care Initiatives for Older Adults in Australia: Scoping Review

“…Only 1 study reported on interactions between health care providers, which was asynchronous [ 74 ]. Seven videoconference initiatives required patients to attend a local health care facility to use videoconference equipment [ 18 , 19 , 21 - 27 , 29 , 32 ].…”

Real-time video analysis allows the identification of large vessel occlusion in patients with suspected stroke: feasibility trial of a “telestroke” pathway in Northwestern Switzerland

“…In that trial, all patients were clinically assessed by a neurologist using NIHSS. Comparing different telestroke protocols from Europe ( 18 ), Australia ( 19 ), and the US ( 20 ), we learned that the local conditions define certain characteristics. While older publications consider any telemedical approach to stroke medicine, newer publications, such as the ESO 2019 guidelines, refer to any real-time video–audio connection as telestroke.…”

The Need for Structured Strategies to Improve Stroke Care in a Rural Telestroke Network in Northern New South Wales, Australia: An Observational Study

“…Time metrics were also assessed using a regression model. To examine the effect of telestroke experience, we set treatment timings as a dependent variable and set the time elapsed since January 2017, NIHSS, ED arrival within 4.5 h from the onset, and reperfusion therapy as independent variables, since our previous research showed symptom severity, fast ED arrival and reperfusion therapy related to faster treatment timings (15). Partial missing data from the database are random and the proportion of cases missing data was relatively small, thus we used the case deletion method.…”

“…Of the 109 patients who received reperfusion therapy, the median age was 73 [64-80] years and 66 were male (60.6%), and most of them (98.2%) were independent at baseline. The baseline NIHSS was 9 [6][7][8][9][10][11][12][13][14][15], and 84 (77.1%) had a large vessel occlusion. The baseline characteristics between phase 1 and 2 for these patients were similar, but there was a higher proportion of male sex in phase 1 (69.1% in phase 1 vs. 46.3% in phase 2, p = 0.02) and a higher proportion of large vessel occlusion strokes in phase 2 (70.6 vs. 87.8%, p = 0.04).…”