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Grant: Planning and Dissemination Grant - Institute Community Support

Ottawa Hospital Research Institute

$19,200.00

Innovative Use of Machine-Learning Algorithm Assistance to Rapidly Recognize the Presence of Sudden Cardiac Arrest and Initiate Life-Saving CPR Instructions During Conversations Between 9-1-1 Callers and Telecommunicators.

FY 2023-24

Summary
Each year, there are 20,000 treatable out-of-hospital sudden cardiac arrests (SCA) in Canada. Bystander cardiopulmonary resuscitation (CPR) can nearly quadruple SCA survival but needs to be started within minutes. In most communities, less than 40% of victims receive CPR before the ambulance arrives. Currently, less than 15% of SCA victims will leave the hospital alive. 9-1-1 telecommunicator-assisted CPR instructions to 9-1-1 callers (previously trained in CPR or not) can greatly improve bystander CPR and survival rates for out-of-hospital SCA. Unfortunately, about 25% of SCA victims gasp for air in the first few minutes. This can fool the 9-1-1 callers and telecommunicators into thinking the victim is still alive, and results in delayed or no CPR instructions to callers. We received pilot funding to demonstrate proof-of-concept for a novel application of the existing IBM-Watson's machine learning artificial intelligence. When developed and refined, IBM-Watson will listen to 9-1-1 conversations and help improve the ability and speed with which 9-1-1 telecommunicators can recognize SCA, initiate timely CPR instructions, and improve survival for out-of-hospital SCA victims. When implemented across Canada, this could save 1,000 lives each year. This promising technology, if working for SCA, could possibly have broader 9-1-1 applications. This proposal is to help identify and engage with a diversified/representative cohort of relevant stakeholders, disseminate findings from foundational projects leading to the proof-of-concept, and seek input from cardiac arrest survivors, 9-1-1 telecommunicators, policy-makers, privacy-ethics-contract officers, and members of the industry. As we develop the proposed artificial intelligence solution, we need to explore all facilitators and potential barriers to its successful implementation, and develop a business plan in partnership with the industry. Ultimately, this will lay the foundations for a strong CIHR operating grant.
Program
Planning and Dissemination Grant - Institute Community Support
Location
Ontario, Canada
Recipient Type
Other
Type
Grant
Source
CIHR Funding Decisions Database

As published

Id
487794
Name
Vaillancourt Christian
Region
Ontario
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Health Services and Policy Research
Theme2
Health systems / services
Prcname2
Planning and Dissemination Grants
Projecttitle
Innovative Use of Machine-Learning Algorithm Assistance to Rapidly Recognize the Presence of Sudden Cardiac Arrest and Initiate Life-Saving CPR Instructions During Conversations Between 9-1-1 Callers and Telecommunicators.
Programtype2
Miscellaneous Programs
Orgnameinp2
Ottawa Hospital Research Institute
Cihramount2
$19,200
Cihrequipment2
$0
Programname2
Planning and Dissemination Grant - Institute Community Support
Keyworddelim
9-1-1 Telecommunicators; Agonal Breathing; Artificial Intelligence; Commercial Planning And Viability; Community Integration In Primary Cardiac Arrest Care; Equitable Access To Health Care Systems; Innovative Digital Solution; Knowledge Exchange; Stakeholder Consultation; Sudden Cardiac Arrest
Abstract
Each year, there are 20,000 treatable out-of-hospital sudden cardiac arrests (SCA) in Canada. Bystander cardiopulmonary resuscitation (CPR) can nearly quadruple SCA survival but needs to be started within minutes. In most communities, less than 40% of victims receive CPR before the ambulance arrives. Currently, less than 15% of SCA victims will leave the hospital alive. 9-1-1 telecommunicator-assisted CPR instructions to 9-1-1 callers (previously trained in CPR or not) can greatly improve bystander CPR and survival rates for out-of-hospital SCA. Unfortunately, about 25% of SCA victims gasp for air in the first few minutes. This can fool the 9-1-1 callers and telecommunicators into thinking the victim is still alive, and results in delayed or no CPR instructions to callers. We received pilot funding to demonstrate proof-of-concept for a novel application of the existing IBM-Watson's machine learning artificial intelligence. When developed and refined, IBM-Watson will listen to 9-1-1 conversations and help improve the ability and speed with which 9-1-1 telecommunicators can recognize SCA, initiate timely CPR instructions, and improve survival for out-of-hospital SCA victims. When implemented across Canada, this could save 1,000 lives each year. This promising technology, if working for SCA, could possibly have broader 9-1-1 applications. This proposal is to help identify and engage with a diversified/representative cohort of relevant stakeholders, disseminate findings from foundational projects leading to the proof-of-concept, and seek input from cardiac arrest survivors, 9-1-1 telecommunicators, policy-makers, privacy-ethics-contract officers, and members of the industry. As we develop the proposed artificial intelligence solution, we need to explore all facilitators and potential barriers to its successful implementation, and develop a business plan in partnership with the industry. Ultimately, this will lay the foundations for a strong CIHR operating grant.
Competitiondate
202307
Approvedterm2
1 yr 0 mth
Pinamesdelim
Vaillancourt, Christian
Approvedterm
1 an 0 mois
Cihrcontribution2
SPOR~ $19,200~ $0~