Abstract TP278: Decade-Long Trends in Recanalization Therapy at a Large Regional Comprehensive Stroke Center in Texas

Introduction: Recanalization therapy (RT) is the cornerstone of acute ischemic stroke (AIS) management. We present 10-year trend in RT at our center, and explore effects of increasing telemedicine (TM) access and a Mobile Stroke Unit (MSU).

Methods: We identified suspected AIS patients between 01/01/2007-12/31/2016 from our prospectively managed registry. Patients presented directly (DP), were transferred-in (TP) from a regional referring hospital with or without TM consultation, or via the MSU. Pre-established TM/MSU period was from 01/01/2007-12/31/2011. We used logistic regression to explore temporal trends among patient groups, report odds ratios (OR) with 95% confidence intervals, and quantile regression to determine the difference in median (DIM) treatment times.

Results: We reviewed 9,464 suspected AIS cases. 44.8% were in pre-TM/MSU and 55.2% TM/MSU period. Over 10 years, the proportion of DP has significantly reduced [OR 0.84 (0.83-0.86)], whereas non-TM TP has increased [OR 1.05 (1.03-1.06)]. In TM/MSU period, the proportion of TM patients has significantly increased each year [OR 2.00 (1.85-2.16)]. Fig. 1 shows the proportional distribution. 29.3% of patients were treated with tPA; significantly higher during the TM/MSU period compared to pre-TM/MSU [(31.5% vs 21.5%, OR 1.21 (1.11 - 1.33)]. Median onset to needle time was significantly shorter for the TM/MSU period [140(99-193) vs 157(119-198), DIM -17(-10.7,-23.2)], as was the proportion of symptomatic intracranial hemorrhage (sICH) [(1.7% vs 4.2%), OR 0.40(0.25-0.64)]. With each increasing year, a significantly greater proportion of patients were discharged home after controlling for age and NIHSS [OR 1.12 (1.10-1.14)].

Conclusion: Over a decade, we saw a steady increase in proportion of tPA treated cases. With the introduction of TM and the MSU at our institution, more AIS patients received RT, with faster onset to treatment, fewer sICH complications, and improved discharge disposition.

Abstract NS5: It Takes a Village: And Other Lessons Learned from a Large Volume Comprehensive Stroke Center

Introduction: The Joint Commission (TJC) certification as a Comprehensive Stroke Center (CSC) entails coordination across multiple units of clinical / academic institutions, and the demands on resources are daunting. Certification standards lack resource allocation recommendations. We present data on workload quantum and resource requirements based on experiences from a TJC certified, high-volume CSC.

Methods: We conducted a desk audit of frequency-based CSC staff activities. An outside team member conducted interviews, followed by collective adjudication for precise categorization. Redundant and overlapping tasks were removed iteratively, and activities were cross-linked with other sources (meeting minutes, individual calendars, on-call schedules). Person-time per task is a product of number of hours and team members. Person-Hours/Day (PHD) were determined by factoring task frequency. PHDs were used to calculate Full Time Employee (FTE) requirements. Volumes were obtained from our CSC registries.

Results: Our CSC received 2,840 patients between 4/1/2016 and 3/31/2017. Among ischemic stroke patients, 30.5% received IV tPA and 119 underwent intra-arterial thrombectomy. Overall, 60 independent activities were divided into 7 mutually exclusive categories (Table 1). Daily, weekly, and monthly activities collectively constituted 83.3% of all the activities. A total of 67.43 PHDs were computed of which data processes are the most resource consumptive (32.07 PHD) followed by core measures tracking (13.8 PHD) (Figure 1). Collectively, the top two activities account for 68% of all PHD and approximate a requirement of six FTEs. Details of activities will be presented.

Conclusion: Adequate planning and continual assessment of resources is imperative to optimal CSC operations and patients’ quality of care. Resources are significantly volume driven. Integrative nature of data processes are central to CSC functioning and necessitate resource evaluation.