Abstract P651: Should I Stay or Go: Seeking Stroke Care During Covid-19

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Kathyrn J Libby ◽  
Linda Couts ◽  
Paige Schoenheit-Scott ◽  
Lindsay L Olson-Mack ◽  
Amelia Kenner Brininger ◽  
...  
Keyword(s):  
San Diego ◽  
Arrival Time ◽  
Stroke Care ◽  
Time Frame ◽  
San Diego County ◽  
Stroke Patients ◽  
Discharge Data ◽  
Hospital Arrival ◽  
The Impact ◽  
At Home

Introduction: On March 16, 2020 San Diego County implemented a stay at home order in response to COVID-19 pandemic; followed by the state of California instituting a shelter in place order. Locally, San Diego County’s stroke receiving centers (SRC) determined a 30% drop in stroke code activations between March-April 2020 compared to the same time in 2019 indicating a possible delay in seeking care. Utilizing discharge data, we sought to understand the impact of the stay at home order on the timeliness of seeking care. Hypothesis: We hypothesized an increase in last known normal (LKN) to hospital arrival time and a decrease in alteplase (tPA) and endovascular therapy (EVT) treatment rates between March 16-June 30 2020 compared to March 16-June 30 2019. Methods: AIS patients presenting to one of 16 SRC in San Diego County between March 16-June 30 in 2019 and 2020, discharged from the hospital or treated in the ED and transferred to another facility were included. Patients arriving as transfers from another facility were excluded. Results: In 2019, of 1,342 AIS cases LKN time was recorded for 85.6% of cases; of 1,092 cases in 2020 86.4% of cases had a LKN. Average LKN to arrival was 20.5 hours in 2019 and 32.4 hours in 2020 (p = .001, 95% CI [4.79, 18.93]). In 2019, 209 (15.6%) received tPA and 91 (6.8%) had EVT. In 2020, 144 (13.2%) received tPA and 75 (6.9%) had EVT. Odds that a case in 2019 received tPA was 1.21 times that of cases in 2020 (p=.09). Odds that a case in 2019 had EVT was .99 times that of cases in 2020 (p=.93). Conclusion: Ischemic stroke patients arriving between March 16-June 30, 2020 had a longer LKN to arrival time compared to the same time frame in 2019. The longer time to arrival may have been due to patients waiting longer to seek care, as anecdotal information from patients eluded to. The odds of receiving tPA or EVT treatment in 2020 compared to 2019 were not statistically significant. This may be due to patients experiencing acute symptoms accessing healthcare at the same rate in 2020 as 2019. Analysis of percent of patients arriving within 4 hours of LKN and average NIHSS are important next steps to determine this. Regardless, during a time of community crisis, it is important to broadcast community messaging focusing on the importance of seeking emergency care for stroke-like symptoms.

Abstract P268: Community Wide Real-Time Stroke Code Capture to Better Identify Changes in Health Care Utilization During Covid-19

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Amelia Kenner Brininger ◽  
Lindsay L Olson-Mack ◽  
Lorraine Chmielowski ◽  
Kristi L Koenig ◽  
Mary A Kalafut ◽  
...  
Keyword(s):  
Acute Stroke ◽  
Real Time ◽  
Healthcare Utilization ◽  
San Diego ◽  
San Diego County ◽  
Discharge Data ◽  
Stroke Incidence ◽  
Number Of Patients ◽  
Stroke Center ◽  
The Impact

Introduction: Many healthcare systems reported a decline in stroke admissions in the early months of the COVID-19 pandemic. We used real-time hospital admission data from Stroke Receiving Centers (SRCs) across San Diego County to quantify changes in stroke patients accessing healthcare with the onset of the COVID-19 pandemic. Rather than waiting for months-delayed discharge data, real-time stroke code data was used to understand the impact on healthcare utilization which may better inform mitigation strategies to encourage accessing care for acute stroke. Methods: We analyzed the total number of patients presenting to any of the 18 San Diego County SRCs for which a stroke code was activated between January 1, 2019 and July 31, 2020; and separated the times into: pre-pandemic (PP) as January 2019 thru February 2020, early-pandemic (EP) as March and April 2020, and mid-pandemic (MP) as May-July 2020. Patients arriving via emergency medical services or private transport were included. A public messaging campaign regarding the safety of accessing care for acute stroke started in early May 2020. Results: A total of 14,028 stroke codes were initiated between January 2019 and July 2020. An average of 43.2 stroke codes were activated per stroke center per month (range=39.6 to 46.7 activations per stroke center per month) during PP, 30.6 during EP and 37.7 during MP (p=.019). Overall, 30% fewer stroke code activations occurred during EP compared to the same months in the PP (p=.012). Mid-pandemic, there were 14.6% fewer stroke code activations compared to the same months pre-pandemic (p=.095). Conclusion: Stroke code activations decreased by 30% across San Diego County SRCs in the EP period compared to the previous year. It is unclear if this is primarily due to decreased healthcare utilization at the start of the COVID-19 pandemic or if there were changes in stroke incidence. MP showed stroke code activations increased compared to EP. This may be partially due to the public messaging campaign initiated after an analysis of PP to EP stroke code activations. We will continue to analyze stroke code data to better understand the impact of public messaging campaigns and determine when activations have returned to PP levels.

Abstract TP245: Variance in Ems Run Times by Receiving Hospital for Stroke Patients in San Diego County

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Amelia Kenner-brininger ◽  
Lindsay Olson-Mack ◽  
Lorraine Calzone ◽  
Kristi L Koenig ◽  
Thomas M Hemmen
Keyword(s):  
Response Time ◽  
San Diego ◽  
Life Support ◽  
Prehospital Care ◽  
Advanced Life Support ◽  
San Diego County ◽  
Stroke Patients ◽  
Transport Time ◽  
Stroke Registry ◽  
Few Data

Background: Emergency Medical Services (EMS) play an important role as initial providers after stroke. Few data are available that capture Stroke Receiving System and EMS response and transport data. We used a stroke registry from a community of 3.3 million residents, 18 stroke receiving centers, and 19 ground transporting advanced life support EMS agencies to evaluate EMS response time, scene time, and transport times. Our aim was to inform the stroke community about duration of EMS care and guide future prehospital interventions. Methods: We included all cases from the San Diego County Stroke Registry arriving by EMS with associated computer automated dispatch (CAD) record and base hospital record (BHR) from July 2017 through December 2018. Records were linked on the EMS incident number, reviewed for accuracy. We analyzed EMS response, scene, transport and total run times (enroute to arrival) by receiving hospital. Results: Between July 2017 and December 2018 2,376 EMS patients were transported to 18 hospitals. Volume per hospital ranged from 11 to 483 patients over the study period. Mean (±SD) response time was 7.0 (±3.7) minutes, range: 5.3 to 9.3 minutes between hospitals. Mean (±SD) scene time was 13.1 (±5.2) minutes, range: 10.5 to 15.0 minutes between hospitals. Transport time averaged 13.8 (±7.7) minutes, range: 8.3 to 23.8 minutes between hospitals (IQR=8.5-17.9). The mean (±SD) total EMS run time was 33.8 (±10.8) minutes, range: 26.4 to 44.9 minutes between hospitals (IQR=26.4-39.9). Conclusion: Only minor variations in EMS response and scene times were observed across the Stroke Receiving Centers. However, transport time showed greater variation and contributed to the differences in total EMS run times. Many systems had short transport times, limiting prehospital interventions. Next steps include studying factors contributing to transport time variation to inform prehospital care and triage decisions of possible stroke patients to optimize transport times.

Abstract 1122‐000242: Effect of Covid‐19 on Stroke Treatment in Australia and New Zealand

2021 ◽  
Vol 1 (S1) ◽  
Author(s):  
Ela Machiroutu
Keyword(s):  
New Zealand ◽  
Stroke Care ◽  
Small Subset ◽  
Stroke Patients ◽  
Secondary Research ◽  
Stroke Treatment ◽  
Survey Tool ◽  
Early Adoption ◽  
Survey Responses ◽  
The Impact

Introduction : In general, compared to the rest of the world, the impact of Covid‐19 in the Australia and New Zealand regions has been minimal and this may be attributed to their early adoption of social distancing, stable governments, national wealth and geographic isolation. However, this research was designed to validate this perception amongst the stakeholders. Methods : This research included: primary and secondary research. First, secondary research about Covid‐19 and stroke treatment and Australia and New Zealand in particular was conducted and compiled in a Google spreadsheet. Research sources include Stroke Foundation, Brain Foundation, and World Meters. Data collected included the number of stroke and Covid‐19 cases in Australia and New Zealand as well as a list of stakeholders with their contact information. The stakeholders included neurosurgeons, hospitals, neurologists, interventionists, and vascular surgeons. A survey tool and an interview questions were prepared next. The survey request was emailed to stakeholders, requesting the stakeholders for an interview and survey response. Over the following weeks, survey results came in and interviews were conducted. Since only a small subset of stakeholders responded to the survey (6 survey responses and 4 interviews), this study must be considered to be primarily qualitative in nature. The interviews were conducted online using Zoom. After the interviews, I replayed the interviews and took notes of important details. Results : The survey showed that 83% of the doctors worked in a hospital that had a separate stroke unit and that they perform mechanical thrombectomies most often as a treatment for stroke. Most of the doctors suggested that the stroke numbers have not changed significantly since Covid‐19. Yet, 50% of the doctors said that there had been delays in admitting stroke patients. One third believed Covid‐19 may have made an impact on mortality of stroke patients. One of the interviewees revealed that the main barriers to access to stroke care are the time it takes to treat the patient, fewer locations that treat strokes or perform mechanical thrombectomy, and patients’ reluctance to go to the hospital during the pandemic. Another confirmed that she did think there had been delays due to Covid‐19. Conclusions : Counter to widespread perception, Covid‐19 pandemic DID worsen many barriers for stroke treatment in Australia and New Zealand. These regions have insufficient stroke centers and these are not spread out widely enough for accessibility. Stroke deaths have increased during the Covid‐19 pandemic. Barriers such as time, accessibility, and the patient’s fear of hospitals have affected stroke treatment during the pandemic. Several measures can alleviate the impact: stroke awareness is critical. Every hospital needs to have the ability to assess and treat stroke. Hospitals must run simulations to practice and prepare for different scenarios that they could encounter when dealing with stroke patients. In conclusion, stroke treatment has been affected by the Covid‐19 pandemic and it is critical to minimize and overcome these barriers as stroke is one of the leading causes of death in Australia and New Zealand.

Abstract P293: Disparate Outcomes for Stroke Patients With Documented Substance Use Compared to Those Without Substance Use

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Leslie Corless ◽  
Tamela L Stuchiner ◽  
Cameron Garvin ◽  
Alexandra C Lesko ◽  
Elizabeth Baraban
Keyword(s):  
Substance Use ◽  
Patient Characteristics ◽  
Stroke Care ◽  
Stroke Patients ◽  
Chi Square ◽  
Stroke Treatment ◽  
Discharge Disposition ◽  
Healthcare Settings ◽  
Medical Histories ◽  
The Impact

Background: Few studies have shown the impact of substance use (SU) on treatment and outcomes of stroke patients. Research suggests stigma related to SU impacts patient experience in healthcare settings. In this study we assessed whether there were differences in patient characteristics and outcomes for stroke patients with SU compared to those with no substance use (NSU). Methods: Retrospective data from two Oregon hospitals included patients admitted with stroke diagnosis, 18 years or older, who discharged between October 2017 and May 2019. Patients with documented SU and specific SU type were compared to patients with NSU with regard to demographics, medical history, stroke subtypes, treatment, discharge disposition and length of stay (LOS). SU was defined as any documented abuse of alcohol (ETOH), methamphetamine (MA), cannabis, opiates, cocaine, benzodiazepines, and Methyl-enedioxy-methamphetamine (MDMA). Non parametric median tests and Pearson’s chi square tests were used. Results: Among 2,030 patients included in the analysis, 13.8% (n=280) were SU and 86.2% (n=1,750) were NSU. Patients with SU were significantly younger, median age (61 vs. 73, p <.001) and less were female (35.4% vs. 53.6%, p <0.001). Those with SU had lower prevalence of dyslipidemia (43.6% vs. 59.5%, p <0.001), AFIB (12.5% vs. 22.2%, p <0.001), and previous TIA (6.1% vs 10.8%, p=0.02), and more smoked (54.3% vs 13.3% p <0.001). More patients with SU arrived via transfer (38.4% vs 27.4%, p=.001). Fewer patients with SU expired or were discharged to hospice (8.9% vs 13.7%) and a greater percent left against medical advice (AMA) (3.2% vs 0.6%) (p<.001). When comparing specific SU types to NSU, all SU groups were younger, had similar medical histories and a greater proportion left AMA. Only MA users had differentiating stroke diagnoses with a higher percent of SAH (14.5% vs 5.6%) (p=.003) in addition to longer LOS (6 vs 4 days, p=.006). No differences were found in acute stroke treatment rates. Conclusion: Patients with SU were demographically different from the NSU population and did differentiate on some stroke care outcomes and processes, potentially indicating opportunities to address stigma around substance use to meet the needs of patients with both stroke and substance use.

Abstract WP247: Paramedic Perspectives on Prehospital Stroke Care: A Qualitative Analysis

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
J A Oostema ◽  
Maria Tecos ◽  
Deborah Sleight ◽  
Brian Mavis
Keyword(s):  
Qualitative Analysis ◽  
Focus Groups ◽  
Stroke Care ◽  
Final Diagnosis ◽  
Structured Interview ◽  
Time Frame ◽  
System Level ◽  
Stroke Patients ◽  
Interview Format ◽  
The Right

Introduction: Ischemic stroke patients who arrive by emergency medical service (EMS) receive faster emergency department evaluations and improved rates of thrombolytic treatment. However, EMS stroke recognition and compliance with prehospital stroke quality measures are inconsistent. We hypothesized that EMS stroke care is influenced by a complex interaction of knowledge, beliefs, and system-level variables that influence behavior. Methods: Focus groups of paramedics from a single urban/suburban county were assembled to discuss their experiences identifying and transporting stroke patients. Focus groups were conducted using a semi-structured interview format and audio recorded. Transcripts of focus groups were qualitatively analyzed to identify themes, subthemes, and patterns of paramedic responses. The Clinical Practice Guidelines Framework provided the initial coding scheme, which was modified during the coding process by three coders using grounded theory methods, who came to consensus on which codes to apply. Results: Three focus groups (n=13) were conducted to reach theme saturation. Overall, paramedics reported high confidence in clinical gestalt for assessing stroke patients and a strong desire to “do the right thing,” but were unfamiliar with published guidelines. Paramedics identified variability in the clinical presentations of stroke, inadequate or inconsistent hospital guidance, and lack of feedback regarding care as principle barriers to ideal prehospital stroke care. Participants reported conflicting hospital guidance regarding the appropriate time frame for a high priority transport and hospital prenotification. Feedback regarding final diagnosis was viewed as critical for developing improved clinical acumen. Direct to CT protocols were cited as an effective way to integrate EMS into hospital stroke response. Conclusion: In this qualitative analysis, paramedics expressed a desire for clear, hospital-directed guidance and consistent feedback regarding outcomes for suspected stroke patients.

Abstract WP281: Pharmacists Improve Door to Needle Times in the Emergency Department

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Kevin Phan ◽  
Megan Degener
Keyword(s):  
Emergency Department ◽  
Cerebral Perfusion ◽  
Stroke Care ◽  
Time Frame ◽  
Safe Delivery ◽  
Team Meetings ◽  
Stroke Team ◽  
Comprehensive Stroke Center ◽  
Stroke Center ◽  
The Impact

Background: An estimated two million brain cells die every minute cerebral perfusion is impaired. The best outcomes for acute ischemic strokes are achieved by decreasing the time from emergency department (ED) arrival to thrombolytic therapy. Alteplase, a high risk medication, was dosed and prepared in the pharmacy. This contributed to prolonged door to needle (DTN) times. Purpose: To describe the impact of pharmacist interventions on DTN times in the ED. Methods: All patients who received alteplase for acute ischemic stroke from January 2012 to April 2019 were reviewed. In November 2012, the ED pharmacy program began with a dedicated ED pharmacist for 8 hours a day and expanded to 13 hours a day in September 2014. During those hours alteplase was prepared at bedside in the ED. In November 2015, all pharmacists were trained on the ED code stroke process. Monthly case reviews and DTN times were reported to the stroke coordinators starting January 2017. Alteplase preparation and administration in the computed tomography (CT) room started April 2017. Following comprehensive stroke center certification, routine stroke competency exams were administered to pharmacists in 2018. In 2019, pharmacists started reporting DTN times at neuroscience core team meetings. Results: During this time frame, a total of 407 patients received alteplase. Average DTN times decreased from a baseline of 130.9 minutes to 45.3 minutes. Interventions that resulted in the largest decrease in average DTN times were the expanded ED service hours (34.6 minutes) and pharmacist preparation of alteplase in the CT room (21.9 minutes). Conclusions: Pharmacists directly impacted stroke care in the ED by decreasing DTN times. Presence of a pharmacist in the ED enabled fast and safe delivery of alteplase by ensuring accurate dosing and preparation. Pharmacists also performed rapid medication reconciliation and expedited antihypertensive therapies. In conclusion, having pharmacists as part of the stroke team is a model that could be adopted by hospitals to enhance stroke care.

scholarly journals The stroke mothership model survived during COVID-19 era: an observational single-center study in Emilia-Romagna, Italy

2020 ◽  
Vol 41 (12) ◽  
pp. 3395-3399
Author(s):  
Andrea Zini ◽  
Michele Romoli ◽  
Mauro Gentile ◽  
Ludovica Migliaccio ◽  
Cosimo Picoco ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Treatment Time ◽  
Combined Treatment ◽  
Temporal Trends ◽  
Stroke Care ◽  
Minor Stroke ◽  
Care Organization ◽  
Stroke Patients ◽  
Stroke Center ◽  
The Impact

Abstract Introduction A reduction of the hospitalization and reperfusion treatments was reported during COVID-19 pandemic. However, high variability in results emerged, potentially due to logistic paradigms adopted. Here, we analyze stroke code admissions, hospitalizations, and stroke belt performance for ischemic stroke patients in the metropolitan Bologna region, comparing temporal trends between 2019 and 2020 to define the impact of COVID-19 on the stroke network. Methods This retrospective observational study included all people admitted at the Bologna Metropolitan Stroke Center in timeframes 1 March 2019–30 April 2019 (cohort-2019) and 1 March 2020–30 April 2020 (cohort-2020). Diagnosis, treatment strategy, and timing were compared between the two cohorts to define temporal trends. Results Overall, 283 patients were admitted to the Stroke Center, with no differences in demographic factors between cohort-2019 and cohort-2020. In cohort-2020, transient ischemic attack (TIA) was significantly less prevalent than 2019 (6.9% vs 14.4%, p = .04). Among 216 ischemic stroke patients, moderate-to-severe stroke was more represented in cohort-2020 (17.8% vs 6.2%, p = .027). Similar proportions of patients underwent reperfusion (45.9% in 2019 vs 53.4% in 2020), although a slight increase in combined treatment was detected (14.4% vs 25.4%, p = .05). Door-to-scan timing was significantly prolonged in 2020 compared with 2019 (28.4 ± 12.6 vs 36.7 ± 14.6, p = .03), although overall timing from stroke to treatment was preserved. Conclusion During COVID-19 pandemic, TIA and minor stroke consistently reduced compared to the same timeframe in 2019. Longer stroke-to-call and door-to-scan times, attributable to change in citizen behavior and screening at hospital arrival, did not impact on stroke-to-treatment time. Mothership model might have minimized the effects of the pandemic on the stroke care organization.

Controlling Juvenile Delinquency: An Evaluation of an Interagency Strategy

1990 ◽  
Vol 36 (2) ◽  
pp. 257-275 ◽  
Author(s):  
Susan Pennell ◽  
Christine Curtis ◽  
Dennis C. Scheck
Keyword(s):  
Early Intervention ◽  
Juvenile Delinquency ◽  
San Diego ◽  
Delinquent Behavior ◽  
Juvenile Crime ◽  
San Diego County ◽  
Graduated Sanctions ◽  
Time Period ◽  
The Impact ◽  
Extended Time Period

This article presents the findings of a two-year assessment of the impact of the San Diego County Interagency Agreement upon delinquent behavior. The goals of this systemwide strategy are to reduce juvenile delinquency through consistent, early intervention and graduated sanctions, based on the nature of the arrest offense and prior offense history, and to hold youth accountable for their acts. The findings suggest that a strategy such as the Interagency Agreement may be successful in reducing juvenile crime if implemented carefully over an extended time period. Based upon the results of this evaluation, recommendations for other jurisdictions are offered.

Social factors influencing hospital arrival time in acute ischemic stroke patients

2011 ◽  
Vol 54 (4) ◽  
pp. 361-367 ◽  
Author(s):  
Christina Iosif ◽  
Mathilda Papathanasiou ◽  
Eleftherios Staboulis ◽  
Athanasios Gouliamos
Keyword(s):  
Ischemic Stroke ◽  
Acute Ischemic Stroke ◽  
Social Factors ◽  
Arrival Time ◽  
Stroke Patients ◽  
Hospital Arrival ◽  
Factors Influencing

scholarly journals Exploring the Collateral Damage of the COVID-19 Pandemic on Stroke Care

Stroke ◽  
2021 ◽  
Author(s):  
Clotilde Balucani ◽  
J. Ricardo Carhuapoma ◽  
Joseph K. Canner ◽  
Roland Faigle ◽  
Brenda Johnson ◽  
...  
Keyword(s):  
Transient Ischemic Attack ◽  
Intravenous Thrombolysis ◽  
Stroke Care ◽  
Unintended Consequences ◽  
Stroke Subtype ◽  
Hospital Arrival ◽  
Time Period ◽  
Ischemic Attack ◽  
The Impact ◽  
Emergency Measures

Background and Purpose: During the coronavirus disease 2019 (COVID-19) pandemic, the various emergency measures implemented to contain the spread of the virus and to overcome the volume of affected patients presenting to hospitals may have had unintended consequences. Several studies reported a decrease in the number of stroke admissions. There are no data on the impact of the COVID-19 pandemic on stroke admissions and stroke care in Maryland. Methods: A retrospective analysis of quality improvement data reported by stroke centers in the State of Maryland. The number of admissions for stroke, overall and by stroke subtype, between March 1 and September 30, 2020 (pandemic) were compared with the same time period in 2019 (prepandemic). Median last known well to hospital arrival time, the number of intravenous thrombolysis and thrombectomy were also compared. Results: During the initial 7 months of the pandemic, there were 6529 total admissions for stroke and transient ischemic attack, monthly mean 938 (95% CI, 837.1–1038.9) versus prepandemic 8003, monthly mean 1156.3 (CI, 1121.3–1191.2), P <0.001. A significant decrease was observed in intravenous thrombolysis treatments, pandemic 617, monthly mean 88.1 (80.7–95.6) versus prepandemic 805, monthly mean 115 (CI, 104.3–125.6), P <0.001; there was no significant decrease for thrombectomies. The pandemic decreased the probability of admissions for stroke and transient ischemic attack by 19%, for acute ischemic stroke by 20%, for the number of intravenous thrombolysis performed by 23%. There was no difference in the number of admissions for subarachnoid hemorrhage, pandemic 199, monthly mean 28.4 (CI, 22.5–34.3) versus prepandemic 217, monthly mean 31 (CI, 23.9–38.1), respectively, P =0.507. Conclusions: Our findings suggest that the COVID-19 pandemic adversely affected the acute care of unrelated cerebrovascular emergencies.

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