Geographic Modeling to Quantify the Impact of Primary and Comprehensive Stroke Center Destination Policies.

BACKGROUND AND PURPOSE: We evaluated the impact of a primary stroke center (PSC) destination policy in a major metropolitan city and used geographic modeling to evaluate expected changes for a comprehensive stroke center policy. METHODS: We identified suspected stroke emergency medical services encounters from 1/1/2004 to 12/31/2013 in Philadelphia, PA. Transport times were compared before and after initiation of a PSC destination policy on 10/3/2011. Geographic modeling estimated the impact of bypassing the closest hospital for the closest PSC and for the closest comprehensive stroke center. RESULTS: There were 2 326 943 emergency medical services runs during the study period, of which 15 099 had a provider diagnosis of stroke. Bypassing the closest hospital for a PSC was common before the official policy and increased steadily over time. Geographic modeling suggested that bypassing the closest hospital in favor of the closest PSC adds a median of 3.1 minutes to transport time. Bypassing to the closest comprehensive stroke center would add a median of 8.3 minutes. CONCLUSIONS: Within a large metropolitan area, the time cost of routing patients preferentially to PSCs and comprehensive stroke centers is low.

Accuracy of Emergency Medical Services Dispatcher and Crew Diagnosis of Stroke in Clinical Practice.

BACKGROUND: Accurate recognition of stroke symptoms by Emergency Medical Services (EMS) is necessary for timely care of acute stroke patients. We assessed the accuracy of stroke diagnosis by EMS in clinical practice in a major US city. METHODS AND RESULTS: Philadelphia Fire Department data were merged with data from a single comprehensive stroke center to identify patients diagnosed with stroke or TIA from 9/2009 to 10/2012. Sensitivity and positive predictive value (PPV) were calculated. Multivariable logistic regression identified variables associated with correct EMS diagnosis. There were 709 total cases, with 400 having a discharge diagnosis of stroke or TIA. EMS crew sensitivity was 57.5% and PPV was 69.1%. EMS crew identified 80.2% of strokes with National Institutes of Health Stroke Scale (NIHSS) ≥5 and symptom duration <6 h. In a multivariable model, correct EMS crew diagnosis was positively associated with NIHSS (NIHSS 5-9, OR 2.62, 95% CI 1.41-4.89; NIHSS ≥10, OR 4.56, 95% CI 2.29-9.09) and weakness (OR 2.28, 95% CI 1.35-3.85), and negatively associated with symptom duration >270 min (OR 0.41, 95% CI 0.25-0.68). EMS dispatchers identified 90 stroke cases that the EMS crew missed. EMS dispatcher or crew identified stroke with sensitivity of 80% and PPV of 50.9%, and EMS dispatcher or crew identified 90.5% of patients with NIHSS ≥5 and symptom duration <6 h. CONCLUSION: Prehospital diagnosis of stroke has limited sensitivity, resulting in a high proportion of missed stroke cases. Dispatchers identified many strokes that EMS crews did not. Incorporating EMS dispatcher impression into regional protocols may maximize the effectiveness of hospital destination selection and pre-notification.

Recognition of Stroke by EMS is Associated with Improvement in Emergency Department Quality Measures.

OBJECTIVE: Hospital arrival via Emergency Medical Services (EMS) and EMS prenotification are associated with faster evaluation and treatment of stroke. We sought to determine the impact of diagnostic accuracy by prehospital providers on emergency department quality measures. METHODS: A retrospective study was performed of patients presenting via EMS between September 2009 and December 2012 with a discharge diagnosis of transient ischemic attack (TIA), ischemic stroke (IS), or intracerebral hemorrhage (ICH). Hospital and EMS databases were used to determine EMS impression, prehospital and in-hospital time intervals, EMS prenotification, NIH stroke scale (NIHSS), symptom duration, and thrombolysis rate. RESULTS: 399 cases were identified: 14.5% TIA, 67.2% IS, and 18.3% ICH. EMS providers correctly recognized 57.6% of cases. Compared to cases missed by EMS, correctly recognized cases had longer median on-scene time (17 vs. 15 min, p = 0.01) but shorter transport times (12 vs. 15 min, p = 0.001). Cases correctly recognized by EMS were associated with shorter door-to-physician time (4 vs. 11 min, p < 0.001) and shorter door-to-CT time (23 vs. 48 min, p < 0.001). These findings were independent of age, NIHSS, symptom duration, and EMS prenotification. Patients with ischemic stroke correctly recognized by EMS were more likely to receive thrombolytic therapy, independent of age, NIHSS, symptom duration both with and without prenotification. CONCLUSION: Recognition of stroke by EMS providers was independently associated with faster door-to-physician time, faster door-to-CT time, and greater odds of receiving thrombolysis. Quality initiatives to improve EMS recognition of stroke have the potential to improve hospital-based quality of stroke care.

A call for formal telemedicine training during stroke fellowship.

During the 20 years since US Food and Drug Administration approval of IV tissue plasminogen activator for acute ischemic stroke, vascular neurology consultation via telemedicine has contributed to an increased frequency of IV tissue plasminogen activator administration and broadened geographic access to the drug. Nevertheless, a growing demand for acute stroke coverage persists, with the greatest disparity found in rural communities underserved by neurologists. To provide efficient and consistent acute care, formal training in telemedicine during neurovascular fellowship is warranted. Herein, we describe our experiences incorporating telestroke into the vascular neurology fellowship curriculum and propose recommendations on integrating formal telemedicine training into the Accreditation Council for Graduate Medical Education vascular neurology fellowship.