Background: It is challenging to quantify the soft elements of care, that often make the most difference in the long-term success of the patients’ recovery such as stroke knowledge, readiness for discharge, family involvement and patient support resources. The interdisciplinary team members document their specialty notes, however they are saved individually and in different sections of the EMR. The stroke team was challenged to create a process that pulls this data together. Hypothesis: We hypothesized that combining interdisciplinary team documentation into a Stroke Care Coordination Note in the EMR, would empower the care team to modify the acute care plan and simultaneously communicate post-hospital needs in order to maximize patients’ transition and outcomes. Methods: Through the engagement of Lean Six Sigma resources, the multidisciplinary team evaluated current processes and documentation to identify gaps. Tools utilized in facilitated meetings include; scope and critical success factors, SIPOC, process mapping, PARMI analysis, and brainstorming. Additionally, sensing sessions and GEMBA observations provided key insights into current state and engaged stakeholders. Results: The team created a Stroke Care Coordination Note in the EMR that consolidates interdisciplinary notes, demonstrates the stroke patients’ individualized plan of care and communicates post hospital needs. Post implementation, additional benefits have been realized such as: ease of use (one touch click), improved nursing communication during transitions of care, and improved communication with ancillary teams such as therapy and discharge planners. Conclusion: A thorough assessment of the current state and gaps, Joint Commission requirements and engagement of interdisciplinary team members, led to the development of a Stroke Care Coordination Note. At any given time, this note can be activated, convey the patients individualized stroke plan of care in the EMR, and be accessed by the interdisciplinary team. The care team stated improved overall patient care and communication during transitions of care. The ease of the use of the note and additional realized benefits support future systemic implementation among additional disease processes and entities.
Background: Patients who alert the Emergency Medical Services (EMS) system arrive to the hospital sooner and receive faster and more appropriate care after stroke. We investigated the regional distribution of EMS alerts in stroke patients throughout San Diego County. Our aim is to document regional difference that may provide opportunities for improvement in community outreach. Methods: We included all patients with principle discharge diagnosis of stroke in the San Diego County Stroke Registry from 01/2015 to 12/2015. We analyzed stroke incidence by ZIP code in cases per 100,000 and use of EMS in percent of all stroke discharges by ZIP code. Each ZIP code was characterized by race/ethnicity, age, use of prescriptions for high blood pressure, diabetes and smoking from ESRI Community Analyst. ZIP codes with fewer than 10 stroke cases were excluded. We used Pearson correlation with significance level of p<0.05. Results: In total we found 5,302 stroke discharges, 4,163 (78.5%) matched to one of 77 ZIP codes in San Diego County. The rate of stroke incidence ranged from 42.9 to 263.9 cases per 100,000 residents. Frequency of EMS use ranged from 26.3% to 83.3%. Rate of stroke was positively correlated with older age, use of prescription drugs for high blood pressure and diabetes. EMS use was higher in ZIP codes with increased smoking (p=0.02). No other variable correlated with EMS use within ZIP codes. Conclusion: The rate of EMS alert after stroke varies considerably across our region. We did not identify a robust predictor for higher EMS use within a ZIP code. Our data suggests that further studies are needed to best understand the variance in EMS use. The regional difference, however, justify a targeted community outreach program to improve EMS utilization after stroke.
Background: Recent studies have focused on improving prehospital stroke assessment tools, but specificity and sensitivity have been insufficient to reliably detect stroke in the prehospital setting. To assess the ability of emergency medical services (EMS) personnel to identify acute stroke in the field, we compared EMS stroke recognition with receiving medical center discharge diagnosis from a large community-based stroke dataset, the San Diego County Stroke Registry. The registry was founded in 2010 after San Diego County established 16 diverse stroke receiving centers. EMS uses the Cincinnati Prehospital Stroke Scale for screening. Methods: We captured all EMS transports in San Diego County from 2013 to 2015. Accuracy of stroke detection by the EMS providers was analyzed by: a) coding of stroke related provider impression (PI) by EMS; b) “stroke” recorded as the reason the transport destination was selected. All patients with diagnosis stroke on hospital discharge were considered confirmed stroke, and separated by: Acute Ischemic Stroke (AIS), Subarachnoid Hemorrhage (SAH), Transient Ischemic Attack (TIA) or Intracranial Hemorrhage (ICH). Results: Between 2013 and 2015, we identified 577,643 EMS transports, 7,425 (1.3%) were diagnosed as stroke by the treating facility (68.2% AIS, 14.4% TIA, 13.6% ICH, and 3.9% SAH). a) Of these 7,418 (99.9%) had a coded PI. Stroke related PI was positive in 53.8% (AIS: 55.9%; SAH: 18.1%; TIA: 60.5%; ICH 46.4%). b) A recorded reason for destination was found in 6,813 (91.8%) of all stroke patients. Stroke was the coded reason in 16.4% (AIS 16.4%; SAH 8.0%, TIA 18.0%, ICH 17.3%). Conclusion: In a large community EMS system, using routine stroke screening, 53.8% of all stroke patients were identified by EMS. Stroke was the coded reason for the selected destination in only 16.4% of EMS transported stroke cases. This emphasizes the need for better prehospital stroke detection to improve triage and direct patient care.
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