Implementation of an Evidence-Based Prenotification Process for Patients With Stroke to Improve Neurological Outcomes : Journal of Neuroscience Nursing

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Implementation of an Evidence-Based Prenotification Process for Patients With Stroke to Improve Neurological Outcomes

Gross, Katharine; Gusler, Bobbi; Londy, Karen; Buterakos, Roxanne; Keiser, Megan

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Journal of Neuroscience Nursing 54(6):p 247-252, December 2022. | DOI: 10.1097/JNN.0000000000000679
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Abstract

Background

Strokes are a major health concern because they account for 11.8% of deaths worldwide, are the second leading cause of death globally, and are the fifth leading cause of death in the United States.1,2 Many comprehensive stroke centers have developed in-hospital code stroke protocols, based on the American Heart Association and American Stroke Association (AHA/ASA) 2019 guidelines that bring the appropriate hospital staff to the patient without delay for lifesaving interventions.3 Although there is significant evidence demonstrating this benefit, rates for using early interventions in acute stroke care, such as administering antiplatelet and fibrinolytic therapy, prenotification process, and overall access to stroke care, are suboptimal.4,5 These protocols notify the stroke team as well as anesthesia and radiology departments to be on standby as the patient is evaluated to determine whether they are a thrombectomy candidate.6,7 Once deemed a candidate, rapid transition from one department to another decreases time to treatment to ensure the best outcome and reversal of symptoms of an acute ischemic stroke (AIS). This is especially important for patients who are found to have a large vessel occlusion (LVO) who run a higher risk of poor functional outcomes without rapid treatment.8 Many studies regarding standardized prenotification processes that accelerate triage and create more effective management of AIS patients have shown drastic improvements in time to treatment, which improves the overall survival and patient outcomes.7,9–11

Prehospital notification of acute stroke has been supported to shorten the emergency department (ED) to groin puncture time because it allows rapid patient registration, swift patient triage, priority use of computed tomography (CT) scanner, standard laboratory tests drawn, immediate intravenous access, rapid imaging interpretation by the stroke team, and completion of the National Institutes of Health Stroke Scale (NIHSS).7,12 Implementation of a standardized evidence-based prenotification process for patients with ischemic stroke symptoms has been proven in multiple research studies worldwide to improve patient outcomes by quick assessment and intervention to promote revascularization to the ischemic brain.5,7,13 Triage to thrombectomy-capable comprehensive stroke centers requires mass communication platforms to distribute emergent notification of an incoming patient with LVO.7,14,15

There are protocols in place for prehospital notification that have been developed for patients showing stroke symptoms that minimize delay in assessment and care.5,7 The emergency medical services (EMS) team contacts the receiving hospital to inform them of a potential stroke patient with conversations between EMS and the ED surrounding the patient's last known well time, current condition, and hemodynamic stability.3 This process allows the ED to prepare for prompt assessment of the patient to ensure that airway, breathing, and circulation are intact and to quickly rule out other causes for stroke symptoms. Established protocols within the hospital help to improve the “timeliness” of care.7,16 In patients with acute stroke due to LVO, good outcomes depend on the time interval from symptom onset to reperfusion, and any delay can lead to poor clinical outcomes.5,10

Currently, at a level I trauma and comprehensive stroke center located in a southwestern metropolitan area of Michigan, it was identified that the present time from arrival in the ED to groin puncture in the angiography suite exceeds 90 minutes, which exceeds the benchmark for mechanical thrombectomy (MT) patients and is considered deleterious to improved outcomes based on the AHA and ASA 2019 guidelines.3 Retrospective chart review identified a major issue related to this delay was the failure to meet the benchmark time from arrival in the ED to undergoing a noncontrast head CT scan. This site's protocol started with the patient going to the ED where assessment by the ED provider was performed, then orders were placed for CT scan, and then decisions regarding the patient's need for MT were made based on CT scan results. This process caused a considerable delay in immediately identifying LVO on CT scan as the patient was losing critical time while waiting for ED providers and transport to CT scan. The objective of this quality improvement (QI) research project is to shorten the time between arrivals in the ED to large-vessel recanalization, which is the clinical marker for the pathways to MT. The AHA and ASA recommend that eligible patients undergo MT preferably within 6 hours of symptom onset.2

Methods

This quasi-experimental QI project was completed at a level I trauma and comprehensive stroke center in a southwestern metropolitan area of Michigan. Implementation occurred during the COVID pandemic during which time the hospital was experiencing immense staff turnover, a high volume of contract staff, and restraints related to COVID restrictions. A statistician performed a power analysis and determined that, with the current average door-to-groin puncture time of 110 minutes and a target postintervention average door-to-groin puncture time of 90 minutes (or less), as well as an assumed standard deviation of 25, 25 patients in the preintervention period and 25 patients in the postintervention period would be needed to reach a power of 0.8 with an α of .05. The university institutional review board reviewed the project protocol and determined that the study did not fit the definition of human subjects' research and deemed the QI project not regulated. No funding was received for this QI project.

Retrospective chart reviews occurred between September 2020 and April 2021 for the preintervention group establishing the population of LVO stroke subjects. Data abstraction occurred between the months of August of 2021 and January of 2022. The inclusion criteria for QI project subjects were as follows: ED patients 18 years or older with AIS symptoms and NIHSS greater than 5 who arrive with EMS prenotification, an Alberta Stroke Program Early CT Score greater than 6, and confirmed LVO on CT angiogram.

The steps identified that must occur before the patient being transported for MT include an acute stroke call down (ASCD) notification sent to the pager and phone of the pertinent members of the ASCD team, arrival of the stroke team, noncontrast head CT scan, CT scan read, decision for MT, patient arrival in the interventional neuroangiography suite (NAS), neurointerventionalist arrival, and groin puncture. The target for this QI project was reducing the “door-to-groin puncture time” to 90 minutes or less within 3 months after the educational intervention with the goal of improving neurological outcomes. All attempted thrombectomies performed have outcome measures of NIHSS on discharge and 75-day postdischarge modified Rankin scores (mRs).

Revisions were made to the site's neurologic deficit protocol algorithm to expedite CT imaging times. Changes to the protocol included adjusting the sequence of CT imaging for hemodynamically stable patients who met the following criteria: Spo2 is 92% or greater, Glasgow Coma Scale score of 10 or higher, blood glucose is 70 or greater, and systolic blood pressure is 90 or greater. If criteria were met, then patients were transported directly to CT scan from ED arrival. A revised algorithm was implemented to improve functional outcomes for patients by streamlining their movement from one department to the next. To meet these deadlines for treatment, an efficient process must be in place to transition from each step in the algorithm for care.2,17,18 Ultimately, delays in treatment for MT in AIS patients are detrimental to the patient's survival and quality of life.2

A neurological deficit algorithm revision (Fig 1) was implemented, and staff were educated on its proper use. The educational implementation occurred in July 2021, which included emails detailing the Joint Commission's national stroke quality measures, data from the previous 6 months regarding the organization's adherence to meeting those measures, the specific revisions made to the neurologic deficit protocol, and an appointment for a mock run-through of the new algorithm. The mock run-through was an opportunity to begin the ASCD process at the entrance of the ambulance bay of the ED and practice the systemization of transporting stable patients directly to CT. Healthcare staff who participated in the education consisted of ED physicians (8), ED physician assistants (3), ED nurse practitioners (5), ED registered nurses (25), neurointensivist nurse practitioners (6), interventional radiology staff (40), EMS personnel (30), and registration (10).

F1
FIGURE 1:
Revised neurological deficit algorithm.

Additional training included a mock run-through of the neurological deficit algorithm for the prehospital notification in the ED. The postintervention sample only included patients who were identified as patients who triggered the prehospital notification criteria. Postintervention data were collected by chart reviews between August 2021 and January 2022. Post 75-day discharge mRs results were collected by the stroke navigator at the site. Improved functional outcomes for patients were measured by an improved mRs scale of greater than 0 but less than 2 at the poststroke follow-up call in 75 days.

Results

Data were collected on a total of 50 stroke patients: 25 were from preintervention and 25 were from postintervention. The researchers were assisted in the data analysis by an experienced statistician at the University of Michigan-Flint. Data were analyzed using SPSS v27.0 for Windows (IBM Corp). Values are expressed as mean (SD) or frequency (%) unless otherwise noted. The significance value of P .05 was set a priori. Descriptive statistics were calculated for demographic variables. The mean age was 69.3 (range, 32–89) years for the preintervention group and 61.5 (range, 29–85) years for the postintervention group. In terms of ethnicity, in the preintervention group, 22 patients were White (88%) and 3 were Hispanic (12%); in the postintervention group, 23 patients were White (92%), one was Hispanic (4%), and one was Black (4%). In the preintervention group, there were 14 men (56%) and 11 women (44%); in the postintervention group, there were 11 men (44%) and 14 women (56%). Twenty patients (83.3%) in the preintervention group presented with cardiovascular risk factors compared with 22 patients (88%) in the postintervention group.

The mean response time to ASCD in the preintervention group was 6.92 (7.99) minutes, and that in the postintervention group was 2.56 (1.87) minutes, which was a statistically significant decrease (P = .013). The mean response time for the arrival of the ASCD neurology team in the preintervention group was 5.92 (9.26) minutes, and that in the postintervention group was 0.68 (1.52) minutes, which was also a statistically significant decrease (P = .01). The mean NIHSS on arrival for the preintervention group was 15.92 (5.59), and that for the postintervention group was 15 (5.93). The mean NIHSS on discharge for the preintervention group was 11.92 (8.72), and that for the postintervention group was 6.05 (5.92) (P = .01). The door-to-CT in minutes was 14.42 (8.85) for the preintervention group and 5.25 (3.19) for the postintervention group (P < .001). The mean time for the NAS interventional radiology team activation was 45.70 (16.72) minutes for the preintervention group and 28.69 (23.82) minutes for the postintervention group (P = .022). The mean door-to-NAS time was 76.1 (22.55) minutes for the preintervention group and 79.12 (44.99) minutes for the postintervention group (P = .77). The mean door-to-groin puncture time was 106.12 (49.32) minutes for the preintervention group and 97.52 (47.77) minutes for the postintervention group (P = .534). The mean for the reperfusion time in minutes for the preintervention group was 150.47 (56.54), and that for the postintervention group was 115.67 (67.20) minutes (P = .07). The mean for the 75-day follow-up mRs was 3.68 (2.48) in the preintervention group and 3.16 (2.36) in the postintervention group (P = .451) (Table 1).

TABLE 1 - Mean Time and Scores for Variables in Neurologic Deficit Algorithm
Variables in Neurologic Deficit Algorithm Mean (SD) Preintervention Time in Minutes Mean (SD) Postintervention Time in Minutes P
Door to CT 14.42 (8.85) 5.25 (3.19) <.001
Response time to ASCD 6.92 (7.99) 2.56 (1.87) .013
Response time for arrival of the ASCD neurology team 5.92 (9.26) 0.68 (1.52) .010
NAS interventional radiology team activation 45.70 (16.72) 28.69 (23.82) .022
Door to arrival in NAS 76.10 (22.55) 79.12 (44.99) .770
Door to groin puncture 106.12 (49.32) 97.52 (47.77) .534
Reperfusion time 150.47 (56.54) 115.67 (67.20) .070
Variables in Neurologic Deficit Algorithm Mean Score Preintervention Mean Score Postintervention P
NIHSS on discharge 11.92 (8.72) 6.05 (5.92) .010
75-d follow-up mRs 3.68 (2.48) 3.16 (2.36) .451
Abbreviations: ASCD, acute stroke call down; CT, computed tomography; mRs, modified Rankin score; NAS, neuroangiography suite; NIHSS, National Institutes of Health Stroke Scale.

Discussion

This QI research project identified many areas of needed improvement for decreasing door-to-groin puncture time at the project site. After implementation of the revised algorithm, significant improvements were observed in the times of the patient arrival to the ED and transport to CT scan. Despite these improved times, there were still delays in the patient's transport from the ED to the angiography suite, which adversely impacted the groin puncture and reperfusion times. Delays in transportation to the angiography suite included securing the patient's airway before intervention and awaiting the interventional radiology staff to transport the patient to the NAS, and during night shift ASCD, there was a delay related to the arrival of the interventional radiology staff to the hospital. Identifying these areas where delays occurred will be the starting point to adjust protocols in the future and thus further improve patient outcomes.

Ultimately, improvements in functional outcomes were not observed. However, in the preintervention group, 12 died, 10 of which had an NIHSS of 15 or higher on arrival. In the postintervention group, 5 died, 4 of which had NIHSS of 15 or higher on arrival. The increase in mortality for ASCD patients could have been attributed to the severity of their stroke symptoms on arrival. The decrease in mortality between the 2 groups could be attributed to the difference in age between the 2 groups, not because of improved times.

As a result of this QI project, the implementation of the revised evidence-based algorithm made for this project showed improvement in response time to ASCD, response time for arrival of the ASCD neurology team, NIHSS on discharge, door-to-CT time, and NAS interventional radiology team activation time. The results of this project did not translate to reduction in door-to-NAS arrival or door-to-groin puncture times. Modified Rankin scores were improved at discharge; however, they were not found to be statistically significant at 75 days post discharge. Limitations of this study included small sample size, lack of diversity of the patient population, the postintervention sample that only included prehospital notification patients, inconsistent provider groups due to the necessity of locums, hospital constraints due to the COVID pandemic, and periodic diversion of regional transfer of stroke patients.

Conclusion

Reduction in benchmark times for AIS patients has the potential to reduce neurological morbidity and mortality for MT patients. Although this QI project did not achieve a goal of door-to-groin puncture time of less than 90 minutes, we found that there were single variable improvements in several benchmarks, and this is a starting point for future QI projects. Reduction in time from patient arrival to CT scan allowed the imaging to be interpreted and results to be processed more efficiently. However, reducing benchmark times is a multivariable problem that requires further evaluation and altering to improve patient outcomes. To achieve these benchmarks and possibly improve patient outcomes, revisions need to be made to the hospital's algorithms according to AHA/ASA evidence-based standards.

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Keywords:

ischemic stroke; mechanical thrombectomy; neurologic outcomes; stroke; stroke benchmarks

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