Contemporary prehospital care systems for cardiovascular emergencies rely on complex communication technologies for daily operation. The rapid care of acutely ill cardiovascular patients depends on effective information transfer among stakeholders across the chain of care. These include the 911 caller, dispatch, first responders, emergency medical services (EMS), and hospital workers. However, the antiquated technologies many systems use to manage medical care in the field are insufficient and surpassed by the technological prowess of ride share services, social media applications, and even national pizza chains. 1 These deficiencies result in inefficient communication in the prehospital-to-hospital chain of care and lead to knowledge compartmentalization among stakeholders who should be seamlessly integrated.Fortunately, technological limitations at the source of these problems are being disrupted, through a process akin to uberization, a business trend by which the development of highly networked systems stimulates new services and fosters more efficient provision of existing services. While these changes hold promise for systemic improvements in emergency care, cardiovascular specialists need to actively plan for their arrival to fully realize their potential.

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Introduction: For out-of-hospital cardiac arrests (OHCAs) unwitnessed by emergency responders, contact with the 911 system provides the earliest point for consistent data collection. Building upon previous tools, we developed a 911 call data abstraction instrument and tested it to see if it reliably tracked key metrics from 911 calls for dispatch assisted CPR in order to guide quality initiatives for OHCA. Methods: Data abstractors applied this tool to a random sample of 23 emergency medical services (EMS)-confirmed, second-party, non-traumatic, non-overdose adult OHCAs occurring prior to first responder arrival from November 2017 to November 2019 in Washtenaw County, Michigan. For each call, data elements were collected by 2 independent reviewers. We focused on key variables: 1) whether the arrest was recognized by dispatch in eligible cases (n=23), 2) whether instructed compressions were provided in eligible cases (n=23), and 3) the 911-time-to-first-instructed-compression (n=11). To evaluate interrater reliability, we calculated kappa statistics for categorical variables and intraclass correlation coefficients (ICC) for continuous variables. Results: We included 23 calls with an average patient age of 64.2 (SD: 10.9) lasting an average of ~5 mins. Overall, 16 patients were men and 7 were women. Thirteen calls originated from private residences, 9 from a public place, and 1 could not be identified. We found that OHCA was recognized by dispatch in 18 of the 23 calls (78%). Reviewers reported instructed compressions occurred in 14 of 23 calls (61%). The median 911-time-to-first-instructed-compression of calls where consistent measurement was possible (n=11) was 197.5 seconds (IQR: 2:30.0-4:44.0). Among calls, kappa statistics for recognition of cardiac arrest and provision of instruction compressions was 1.00 (n=23) and 0.91 (n=23), respectively, while the ICC for time-to-first instructed compression was >0.99 (n=11). Conclusions: Reviewing 911 calls with this tool was capable of collecting reliable information from independent reviewers on key events including critically important times. Collection of these data is a critical first step for evaluating system performance to improve survival from OHCA.

Introduction: Dispatch processes for prehospital management of out-of-hospital cardiac arrest (OHCA) vary greatly by region, and so do the barriers and facilitators of rapid time-to-first-treatment within those systems. In order to optimize local OHCA response, we sought to identify improvement targets by tracking time intervals during OHCA 911 calls and evaluating associated barriers and facilitators to timely OHCA prehospital care delivery. Methods: We developed a data abstraction tool to collect quantitative and qualitative data regarding key events in a random sample of 23 of emergency medical services (EMS)-confirmed, second-party, non-traumatic, non-overdose, non-facility adult OHCAs occurring prior to first responder arrival from November 2017 to November 2019 in Washtenaw County, Michigan. Trained abstractors double reviewed calls. We calculated descriptive statistics of key event times to summarize a timeline of care and evaluated qualitative data using thematic analysis to assess event intervals. Results: Based on quantitative and qualitative analyses, we created a timeline with summary data of dispatcher OHCA response based on an aggregate of 23 calls to 911 dispatch (see Figure 1). Data abstractors identified two intervals-of-interest as containing barriers to optimizing time-to-first treatment: 1) time between the first report of abnormal breathing and call taker statement of CPR need (Interval 1), and 2) time from patient positioning to the first compression instruction (Interval 2). Qualitative data suggested that these interval delays were a result of extensive efforts on the part of the call taker to reconfirm breathing status in particular. Additional barriers, such as the callers misunderstanding instruction, and on-scene physical limitations, were also identified. Conclusions: We identified two primary time intervals to target for improvement as well as barriers present in our local 911 system. These data may serve as a foundation to develop targeted interventions to optimize local systems of care for 911 dispatch workflows. Figure 1