Re-thinking Medical Device Management: Driving Digital Innovation, Analytics & Supply Chain Efficiencies

May 13th, 2021 | 10.00 AM – 11.00 AM ET

COVID19 disruptions have accelerated the need for medical device organizations to digitize their supply chain and transform device management. Medical device organizations can leverage advanced analytics to optimize inventory of device parts thereby ensuring there is neither high capital tie-up due to stockpiling of devices nor stock out of devices at provider facilities and hospitals.

Join the panel discussion
Login with LinkedIn or Google for a seamless experience
OR
Enter your information

About the Speakers

 

Panelist
Joe Dudas
Division Chair, Supply Chain Management,
Mayo Clinic

Panelist
KT Pickard
Director New Product Development, Enterprise Diagnostic Informatics,
Philips Healthcare

   

 

Panelist
Patricia Morrison
Board of Director, Baxter
Former Exec. Vice President, 
Cardinal Health

 

Moderator
Dr. William Winkenwerder Jr.

Chairman at CitiusTech,

Formerly, CEO of Highmark,
Asst. Secretary of Defense for Health Affairs

 

Besides digitizing the medical device supply chain, organizations must aim to transform device management and maintenance. Traditionally, medical device organizations have followed a reactive approach for device maintenance leading to unplanned downtime and unnecessary service visits by field engineers for device maintenance. Through the adoption of an AI-based proactive approach, organizations can reduce field visits by over 20%, intelligently monitor devices, alert service teams in real-time and reduce the overall cost of maintenance.

In this panel discussion industry luminaries will share insights on steps device organizations can take to digitize the overall supply chain and drive proactive maintenance of devices.

Key Learnings

  • Prioritizing digital technologies for improving supply chain efficiency
  • Optimizing medical device inventory costs
  • Adopting an integrated technology framework to drive predictive and remote maintenance of devices
  • Operationalizing AI models to drive intelligent and adaptive monitoring of devices