Outline and validation of a new dispatcher-assisted cardiopulmonary resuscitation educational bundle using the Delphi method.

Aim: Dispatcher-assisted cardiopulmonary resuscitation (DA-CPR) is time-dependent. To date, evidence-based training programmes for dispatchers are lacking. This study aimed to reach expert consensus on an educational bundle content for dispatchers to provide DA-CPR using the Delphi method.

Swedish emergency medical dispatch centres' ability to answer emergency medical calls and dispatch an ambulance in response to out-of-hospital cardiac arrest calls in accordance with the American Heart Association performance goals: An observational study.

Aim: To investigate the ability of Swedish Emergency Medical Dispatch Centres (EMDCs) to answer medical emergency calls and dispatch an ambulance for out-of-hospital cardiac arrest (OHCA) in accordance with the American Heart Association (AHA) performance goals in a 1-step (call connected directly to the EMDC) and a 2-step (call transferred to regional EMDC) procedure over 10 years, and to assess whether delays may be associated with 30-day survival.

Method: Observational data from the Swedish Registry for Cardiopulmonary Resuscitation and EMDC.

Results: A total of 9,174,940 medical calls were answered (1-step).

Swedish dispatchers' compliance with the American Heart Association performance goals for dispatch-assisted cardiopulmonary resuscitation and its association with survival in out-of-hospital cardiac arrest: A retrospective study.

Aim: We aimed 1) to investigate how Swedish dispatchers perform during emergency calls in accordance with the American Heart Association (AHA) goals for dispatcher-assisted cardiopulmonary resuscitation (DA-CPR), 2) calculate the potential impact on 30-day survival.

Methods: This observational study includes a random sample of 1000 out-of-hospital cardiac arrest (OHCA) emergency ambulance calls during 2018 in Sweden. Voice logs were audited to evaluate dispatchers' handling of emergency calls according to the AHA performance goals.

Machine learning can support dispatchers to better and faster recognize out-of-hospital cardiac arrest during emergency calls: A retrospective study.

Aim: Fast recognition of out-of-hospital cardiac arrest (OHCA) by dispatchers might increase survival. The aim of this observational study of emergency calls was to (1) examine whether a machine learning framework (ML) can increase the proportion of calls recognizing OHCA within the first minute compared with dispatchers, (2) present the performance of ML with different false positive rate (FPR) settings, (3) examine call characteristics influencing OHCA recognition.

Methods: ML can be configured with different FPR settings, i.

Adherence to treatment guidelines for patients with chest pain varies in a nurse-led prehospital ambulance system.

Introduction: Studies have shown that adherence to prehospital treatment guidelines, for patients with non-traumatic chest pain is incomplete and that there is a gender difference in treatment provided.

Purpose: The aim of this study was to examine adherence to guidelines in a nurse-led ambulance system in southern Sweden.

Method: Retrospective cohort study, including 862 medical records was reviewed.