Background Patients with acute stroke at non‐ or primary stroke centers (PSCs) are transferred to comprehensive stroke centers for advanced treatments that reduce disability but experience significant delays in treatment and increased adjusted mortality. This study reports the results of a proactive, systematic, risk assessment of the door‐in‐door‐out process and its application to solution design. Methods and Results A learning collaborative (clinicians, patients, and caregivers) at 2 PSCs and 3 comprehensive stroke centers in Chicago, Illinois participated in a failure modes, effects, and criticality analysis to identify steps in the process; failures of each step, underlying causes; and to characterize each failure’s frequency, impact, and safeguards using standardized scores to calculate risk priority and criticality numbers for ranking. Targets for solution design were selected among the highest‐ranked failures. The failure modes, effects, and criticality analysis process map and risk table were completed during in‐person and virtual sessions. Failure to detect severe stroke/large‐vessel occlusion on arrival at the PSC is the highest‐ranked failure and can lead to a 45‐minute door‐in‐door‐out delay caused by failure to obtain a head computed tomography and computed tomography angiogram together. Lower risk failures include communication problems and delays within the PSC team and across the PSC comprehensive stroke center and paramedic teams. Seven solution prototypes were iteratively designed and address 4 of the 10 highest‐ranked failures. Conclusions The failure modes, effects, and criticality analysis identified and characterized previously unrecognized failures of the door‐in‐door‐out process. Use of a risk‐informed approach for solution design is novel for stroke and should mitigate or eliminate the failures.
Introduction: Acute stroke (AS) is a highly time sensitive treatment condition affecting approximately 800,000 people/year in the US. Most AS patients receive care at a primary stroke center (PSC), but some require more advanced treatments, and rely on a timely transfer to a comprehensive stroke center (CSC) where such treatments can be given. Stroke teams at 2 Chicago area PSCs and 4 CSCs, collectively, developed solutions (Graph) targeting both reported and perceived failures/delays/weakness in the current PSC door-in-door-out (DIDO) process for transferring patients to a CSC. The study simulates the potential impact of the solutions on DIDO. Methods: Current state (baseline) times were calculated from time stamps in the electronic health record (EHR) (e.g., door to CT), estimated by the stroke teams (e.g., hand-off time) or retrieved (e.g., DIDO, door to stroke activation) from a prospectively maintained REDCap data registry (2/2018-1/2020). Proportions (e.g., % with ischemic stroke, % transferred) were estimated from hospital data. Changes in times after implementation of a solution were obtained from peer reviewed literature, when available, or by consensus expert opinion. Simio (version 11.197.19514) was used to simulate the current and future states with implementation of the solutions, with 500 replications, to estimate changes in DIDO. Results: Implementation of all solutions would achieve a decrease in DIDO of 33 minutes (19%) from current state. The largest driver of this change was direct to CT/CTA protocol implementation (21 minutes) followed by using a handoff tool for paramedics prior to transfer (13 minutes). Conclusion: The proposed solutions can achieve nearly a 20% reduction in DIDO times. The “Direct to CT/CTA Protocol” solution is the major driver of the improvement. Data simulation is helpful by assessing the potential impact of many solutions and the relative impact of each solution to inform implementation decisions.
Introduction: Many patients with acute stroke require inter-facility transfer from primary stroke centers (PSC) to comprehensive stroke centers. Given the time-sensitive benefits of endovascular treatments, door-in-door-out (DIDO) time at the PSC is a target for quality improvement. Methods: As part of a funded ongoing study of redesigning the acute stroke DIDO process, we collected data on consecutive patients with acute stroke between February 2018 and February 2019 who required inter-facility transfer from 5 PSCs to one of 3 CSCs in the Chicago region. The stroke coordinators at each site abstracted data on mode of transport (critical care vs. advanced life support [ALS]), medical events and treatments (intubation, intravenous medications including tPA), times from arrival to: triage, telestroke activation and start, CT and CTA start, initial transfer center contact, ambulance request, and ambulance arrival and departure times. We evaluated predictors of DIDO time using linear regression. Results: Among 107 patients who met study criteria, 67.6% arrived by EMS, 83.2% had telestroke evaluation, 34.6% had tPA treatment, and 43.9% underwent CTA at the PSC. The median DIDO time was 146 (IQR 99-220) minutes. The largest contributors to DIDO time (Figure) were CT to CTA time (45 [18-86] minutes), ambulance scene time (26 [21-35] minutes), and telestroke to transfer center contact (median 23 [0-61] minutes). Independent predictors of DIDO time were obtaining CTA (+64.1 [29.4-98.5] minutes), use of ALS ambulance (+52.5 minutes [17.5-87.5] minutes), and use of intravenous medications besides tPA (+59.9 [15.7-104.1] minutes). Conclusions: We identified major opportunities for reducing DIDO times for inter-facility acute stroke transfers. Reducing the need for or time to CTA, earlier, streamlined transfer center contact, and using critical care ambulances are likely important strategies to decrease DIDO times.
BackgroundThe majority of Mobile Stoke Units (MSUs) operate in European and United States urban cities. Questions remain on the cost-effectiveness, setting (urban, suburban, or rural), infrastructure and support, and reimbursement of these units. We present our experiences of a single-center MSU in a suburban setting, with treatment times, challenges, and possible future directions of alternative methods of care.MethodsRetrospective analysis of prospectively collected data from Mobile Stroke Unit calls for service and Get With The Guidelines-Stroke data from two primary stroke centers from December 2017 through February 2020 comparing patients receiving intravenous thrombolysis and treatment times.ResultsThere were no differences in age, sex, medical history, or stroke severity between MSU transport when compared to standard transport. There were differences in patient racial and ethnic demographics between groups, with higher white race and Hispanic ethnicity. Door-to-needle time was 48.9 minutes for patients seen on the Rush MSU versus 67.2 minutes for patients seen via traditional EMS transport (p=0.04).ConclusionsThe Rush MSU demonstrated significant reduction of acute ischemic stroke treatment time with intravenous thrombolysis, but did not demonstrate the patient volume necessary to justify continued operation. Suburban and rural regions do benefit from pre-hospital stroke evaluation, however the ideal method for a cost-effective strategy is still unknown.
Introduction: Given the time-critical nature of acute stroke, reducing door-in-door-out (DIDO) times at primary stroke centers (PSC) prior to transfer to comprehensive stroke centers (CSC) is a priority. We applied Failure Modes Effects and Criticality Analysis (FMECA) to the DIDO process at a PSC, an engineering methodology widely used in other industries, to understand the most critical areas negatively impacting DIDO time. Methods: We collected data during 2 in-person and 5 virtual Learning Collaborative (LC) meetings, enhanced by electronic surveys. The LC team consisted of 18 clinicians affiliated with 6 different healthcare systems including 3 PSCs and 3 CSCs, 2 participants from EMS agencies, and 5 patients and caregivers. The LC team created a DIDO process map with individual steps. For each step, we asked LC members to identify ways in which the process could be performed incorrectly, incompletely, skipped or delayed (failures) along with the clinical impact, their causes, frequency and existing safeguards. Each clinical impact, frequency and safeguard was scored from 1-10 (lowest to highest). Frequency, severity, and safeguards scores were multiplied to calculate a criticality score to rank the top DIDO process failures. Results: Among 61 DIDO process steps, the top 12 steps with the highest criticality score represented 40.4% of the sum of criticalities (Figure). Among these, the highest criticality scores were for: 1) Delay in the decision to obtain CTA; 2) Delay in stroke recognition by the EMS team; 3) Delay in stroke identification at triage. Conclusion: We identified opportunities to re-design the DIDO process for acute stroke. Existing safeguards for the identified “high” criticality failures rely on human factors (e.g., multiple visual inspections, provider’s experience). There is a need to develop better stroke identification tools and automatic triggers within the DIDO process to increase timely stroke transfers from PSC to CSCs.
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