Characterization of non-cardiac arrest PulsePoint activations in public and private settings.

BACKGROUND: Geospatial smartphone application alert systems are used in some communities to crowdsource community response for out-of-hospital cardiac arrest (OHCA). Although the clinical focus of this strategy is OHCA, dispatch identification of OHCA is imperfect so that activation may occur for the non-arrest patient. The frequency and clinical profile of such non-arrest patients has not been well-investigated. METHODS: We undertook a prospective 3-year cohort investigation of patients for whom a smartphone geospatial application was activated for suspected OHCA in four United States communities (total population ~1 million). The current investigation evaluates those patients with an activation for suspected OHCA who did not experience cardiac arrest. The volunteer response cohort included off-duty, volunteer public safety personnel (verified responders) notified regardless of location (public or private) and laypersons notified to public locations. The study linked the smartphone application information with the EMS records to report the frequency, condition type, and EMS treatment for these non-arrest patients. RESULTS: Of 1779 calls where volunteers were activated, 756 had suffered OHCA, resulting in 1023 non-arrest patients for study evaluation. The most common EMS assessments were syncope (15.9%, n=163), altered mental status (15.5%, n=159), seizure (14.3%, n=146), overdose (13.0%, n=133), and choking (10.5%, n=107). The assessment distribution was similar for private and public locations. Overall, the most common EMS interventions included placement of an intravenous line (43.1%, n=441), 12-Lead ECG(27.9%, n=285), naloxone treatment (9.8%, n=100), airway or ventilation assistance (8.7%, n=89), and oxygen administration (6.6%, n=68). CONCLUSIONS: More than half of patients activated for suspected OHCA had conditions other than cardiac arrest. A subset of these conditions may benefit from earlier care that could be provided by both layperson and public safety volunteers if they were appropriately trained and equipped.

Improving response to out-of-hospital cardiac arrest: The verified responder program pilot.

BACKGROUND: Survival following out-of-hospital cardiac arrest (OHCA) decreases as the interval from collapse to CPR and defibrillation increases. Innovative approaches are needed to reduce response intervals, especially for private locations. METHODS: We undertook the Verified Responder Program in 5 United States communities during 2018, whereby off-duty EMS professionals volunteered and were equipped with automated external defibrillators (AEDs). Volunteers were alerted using a geospatial smartphone application (PulsePoint) and could respond to nearby private and public suspected OHCA. The study evaluated the frequency of Verified Responder notification, response, scene arrival, and initial care prior to EMS arrival. OHCA surveillance used the CARES registry. RESULTS: Of the 651 OHCA events (475 private, 176 public), Verified Responders were notified in 7.4% (n = 49). Among the 475 in a private location, volunteers were alerted in 8% (n = 38), responded in 2.7% (n = 13), arrived on scene in 2.3% (n = 11), and provided initial care in 1.7% (n = 8). Among the 176 in a public location, volunteers were alerted in 6.3% (n = 11), responded in 2.3% (n = 4), arrived on-scene in 2.3% (n = 4), and provided initial care in 2.3% (n = 4). Over 96% surveyed had positive impression of the program and intended to continue participation. No responder reported any adverse event. CONCLUSIONS: In this initial US-based experience of a smartphone program for suspected OHCA in private and public locations, Verified Responders reported a positive experience, though were only involved in a small fraction of OHCA. Studies should determine how this type of program could be enhanced to involve more OHCA events.

Strategy to Address Private Location Cardiac Arrest: A Public Safety Survey.

OBJECTIVE: Most cardiac arrests occur in the private setting where response is often delayed and outcomes are poor. We surveyed public safety personnel to determine if they would volunteer to respond into private locations and/or be equipped with a personal automated external defibrillator (AED) as part of a vetted responder program that would use smart geospatial technology. METHODS: We conducted an anonymized survey among personnel from fire-based emergency medical services (EMS) and search and rescue organizations from Washington State. The goal of the survey was to evaluate whether there was interest among cardiopulmonary resuscitation (CPR)-trained, public safety personnel to respond with or without an AED to private-residence cardiac arrest outside of working hours using a smartphone platform. We used a 5-point Likert scale to assess responses. RESULTS: Overall the response rate was 73.7% (527/715). Two-thirds of respondents were between the ages of 30-59 with a similar proportion certified as a firefighter-emergency medical technician (EMT). Most were male (80%). As a vetted volunteer responder, the majority would "almost always" or "often" respond to private (79.7%) or public locations (85.2%) outside of work hours. The majority (54.1%) would store the AED in their vehicle while 38% would plan to keep the AED on their person. A total of 83% were "definitely' or "probably interested" in participating in the program. CONCLUSION: The results of this survey indicate that public safety personnel are willing to respond to suspected cardiac arrest during off-hours using geospatial smart technology to private locations with or without an AED.

Evaluation of Physiologic Alterations during Prehospital Paramedic-Performed Rapid Sequence Intubation.

OBJECTIVE: Physiologic alterations during rapid sequence intubation (RSI) have been studied in several emergency airway management settings, but few data exist to describe physiologic alterations during prehospital RSI performed by ground-based paramedics. To address this evidence gap and provide guidance for future quality improvement initiatives in our EMS system, we collected electronic monitoring data to evaluate peri-intubation vital signs changes occurring during prehospital RSI. METHODS: Electronic patient monitor data files from cases in which paramedic RSI was attempted were prospectively collected over a 15-month study period to supplement the standard EMS patient care documentation. Cases were analyzed to identify peri-intubation changes in oxygen saturation, heart rate, and blood pressure. RESULTS: Data from 134 RSI cases were available for analysis. Paramedic-assigned prehospital diagnostic impression categories included neurologic (42%), respiratory (26%), toxicologic (22%), trauma (9%), and cardiac (1%). The overall intubation success rate (95%) and first-attempt success rate (82%) did not differ across diagnostic impression categories. Peri-intubation desaturation (SpO2 decrease to below 90%) occurred in 43% of cases, and 70% of desaturation episodes occurred on first-attempt success. The incidence of desaturation varied among patient categories, with a respiratory diagnostic impression associated with more frequent, more severe, and more prolonged desaturations, as well as a higher incidence of accompanying cardiovascular instability. Bradycardia (HR decrease to below 60 bpm) occurred in 13% of cases, and 60% of bradycardia episodes occurred on first-attempt success. Hypotension (systolic blood pressure decrease to below 90 mmHg) occurred in 7% of cases, and 63% of hypotension episodes occurred on first-attempt success. Peri-intubation cardiac arrest occurred in 2 cases, one of which was on first-attempt success. Only 11% of desaturations and no instances of bradycardia were reflected in the standard EMS patient care documentation. CONCLUSIONS: In this study, the majority of peri-intubation physiologic alterations occurred on first-attempt success, highlighting that first-attempt success is an incomplete and potentially deceptive measure of intubation quality. Supplementing the standard patient care documentation with electronic monitoring data can identify unrecognized physiologic instability during prehospital RSI and provide valuable guidance for quality improvement interventions.