Publications by authors named "L Holmqvist"
Article Synopsis
- This study examines out-of-hospital cardiac arrests (OHCA) in young adults (ages 16-49) in Sweden from 1990 to 2020, focusing on survival rates and causes of cardiac arrests.
- Over the 30-year period, there was a notable annual increase of 5.9% in 30-day survival rates without decline in neurological function, despite rising cases related to overdoses and suicides.
- By 2020, an impressive 88% of OHCA cases received bystander CPR, while EMS response times increased from 6 to 10 minutes, indicating both improvement in immediate care and challenges in emergency response.
The impact of the three-level collaboration exercise on collaboration and leadership during scenario-based hospital evacuation exercises using flexible surge capacity concept: a mixed method cross-sectional study.
BMC Health Serv Res
August 2023
Background: Hospitals play a crucial role in responding to disasters and public health emergencies. However, they are also vulnerable to threats such as fire or flooding and can fail to respond or evacuate adequately due to unpreparedness and lack of evacuation measures. The United Nations Office for Disaster Risk Reduction has emphasised the importance of partnerships and capacity building in disaster response.
View Article and Find Full Text PDFBackground: Most Swedish emergency departments (ED) use the triage system Rapid Emergency Triage and Treatment System (RETTS©), which over time has proven to prioritize patients to higher triage levels. When many patients are prioritized to high triage levels, challenges with identifying true high-risk patients and increased waiting time for these patients has emerged. In order to achieve a more balanced triage in relation to actual medical risk, the triage system WEst coast System for Triage (WEST) was developed, based on the South African Triage Scale (SATS).
View Article and Find Full Text PDFPediatric Priority Process (PEPP) is a triage system derived from the South African Triage Scale. It was developed by healthcare professionals at the Queen Silvia Children's hospital in Gothenburg. PEPP is a four-level triage system with two parts: vital parameters and warning symptoms.
View Article and Find Full Text PDFBackground: Machine learning (ML) is an emerging tool for predicting need of end-of-life discussion and palliative care, by using mortality as a proxy. But deaths, unforeseen by emergency physicians at time of the emergency department (ED) visit, might have a weaker association with the ED visit.
Objectives: To develop an ML algorithm that predicts unsurprising deaths within 30 days after ED discharge.