AI at the Point of Care Team
AI Working Teams > AI @ POC
Goal
The AI at the Point of Care Team (AI@POC) is designed for physicians, healthcare system members, and innovators seeking to leverage Artificial Intelligence (AI) to improve patient care, clinical workflow, system operations, and also reduce unnecessary costs.
01
Establish a reliable digital framework for sharing knowledge and insights between both clinical and technical experts through collaboration and active use case discussions.
02
Develop successful practices and recommendations, addressing concerns related to the development, implementation, and usage of AI tools.
03
Create a reliable mechanism to assess the trustworthiness of potential AI products, establishing a well-informed adoption across the healthcare environment. (Note: Trustworthiness is a measure of the products’ integrity, transparency, explicability, ethicality, etc.)
04
Foster communication across an open-access network of Providers, Implementors, and Innovators to encourage responsible AI adoption at the Point of Care.
Problem Statement
AI has the potential to forever alter the operating paradigm of high performing healthcare systems at all levels and across all domains. The safe and effective development, implementation, and ongoing use of AI tools and resources requires participation of all key stakeholders to:
Improve system operations
Improve patient safety and care
Increase effectiveness of clinical workflow and healthcare services
Reduce unnecessary costs
TheAI@POC Team will develop outcomes to address the above challenges. Emphasis will be placed on creating deliverables that provide maximum ROI. (Note: ROI is defined as Relationships, Outcomes, and Improvements.)
Deliverables
The first year (September 2021 – October 2022) goal for the AI@POC Team is:
Establish a reliable digital framework for sharing knowledge and insights between both clinical and technical experts through collaboration and active use case discussions.
Deliverables will include:
Adoption Matrix Model by Use case, easing the Adoption curve
Implementation Matrix Model by Use case, leading to an Implementation Playbook
Levels of Engagement
Core Members
Committed to maintaining goals and the active stewardship of deliverables
Subgroups
Contributors and developers of deliverables; based on areas of interest
General Group
Knowledgeable/informed; provide input for subgroup deliverables
Joining the Team
You have an opportunity to work with your peers to improve patient care, clinical workflow, and system operations by leveraging the possibilities of Augmented Intelligence.
The AI@POC Team operates virtually from September to August annually, led by a structured leadership team to achieve predefined goals.
Team leaders present the work outcome at the annual AI Summit. You’ll be acknowledged for your contributions at the Summit and in team publications.
Meeting frequency and duration are determined by the needs to support progress. Team members volunteer based on expertise.
If you are interested in joining the AI@POC Working Team, please note:
It is expected that you participate in the standing meetings (schedule is determined by each team).
Plan on a time commitment of 5 hours per month, but this may vary.
Explore how you can use AI in your organization starting today and how far it can be taken into the future.
The membership fee for 2022 will be WAIVED for everyone as we transition to management of our ai work team programs under AFDO/RAPS. Any member who previously paid a 2022 membership fee, will receive a free membership for 2023.
Team Leaders
Steve Frigon
Sr. Clinical Systems Analyst, The Christ Hospital Health Network
Steve Frigon is a Senior Clinical Systems Analyst at The Christ Hospital in Cincinnati, Ohio. He has specialized in Application Development, Data Integration, and Data Management solutions in the Pharmaceutical and Healthcare industries for the past 21 years. In this position, Frigon develops various technology strategies and adaptation techniques in the areas of interoperability, web services, and Digital Health. His focus in the AI framework is on explicability, validation, and adoption, which stimulates the development of trust in patients and physicians alike.
Prior to joining The Christ Hospital, Frigon was a Data Integration Consultant with HC Tech, Inc. and a Data Integration Manager at Mercy Health.
Marc Paradis
Vice President of Data Strategy, Northwell Holdings
Patrick Pavlick
Senior Digital Diagnostics Director, US Medical, Rare Diseases, Sanofi
Pat has been part of the US Rare Medical Diagnostic team at Sanofi for over 5 years. This team is responsible for shortening the diagnostic odyssey associated with rare lysosomal storage disorders. Pat spearheads Project Searchlight, an AI/ML initiative designed to mine aggregated electronic health records to assess patients and identify those needing confirmatory testing for diagnosis. Before joining Sanofi, Pat had over 20 years in pharma and biopharma with roles in sales, marketing, and leadership.