Abstract
Mortality from sudden cardiac arrest remains high despite increased awareness and advancements in emergency resuscitation efforts. Various gaps exist in bystander resuscitation, automated external defibrillators, and access. Significant racial, gender, and geographic disparities have also been found. A myriad of recent innovations in sudden cardiac arrest uses new machine learning algorithms with high levels of performance. These have been applied to a broad range of efforts to identify individuals at high risk, recognize emergencies, and diagnose high-risk cardiac arrhythmias. Such technological advancements must be coupled to novel public health approaches to best implement these innovations in an equitable way. The authors propose a data-driven, technology-enabled system of care within a public health system of care to ultimately improve sudden cardiac arrest outcomes.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.