The CDO Healthcare Exchange presents valuable sponsorship opportunities to connect your brand with leading data executives. You’ll have the chance to engage in up to 15 personalised one-to-one meetings with pre-qualified delegates, giving you direct access to decision-makers who align with your offerings.

Additionally, you’ll gain exclusive insights into their challenges and priorities, allowing you to tailor your approach for maximum impact. Beyond direct engagement, your brand will benefit from prominent visibility at the event and across its digital platforms.

This includes branding at the physical venue, on the event website, and in all marketing materials. Sponsors can also establish thought leadership through a dedicated 30-minute presentation and participation in panels or workshops, as well as enhance networking by hosting exclusive events or sponsoring breakout sessions. Download the Sponsorship Prospectus for more details.

Download the 2024 post event report for exclusive insights on attendee investment priorities, audience breakdown, key themes discussed at the event, and much more!

The HIMSS Analytics Maturity Assessment Model (AMAM) determines where healthcare organizations are on the data and analytics maturity curve. Only a handful of organizations worldwide have reached the highest level, indicating population-level predictive modeling. The CDO Healthcare Exchange was lucky enough to sit down with Ryan Sousa, a data and analytics leader who has led organizations through the journey to HIMSS AMAM Stage 7. In this interview, Ryan shares valuable insight on:

• The roadmap to reach HIMSS AMAM Stage 7 
• The kind of cultural change needed to reach HIMSS AMAM Stage 7
• The impact that advanced analytics can have on patient care and employee experience
  

Generative AI is poised and ready to revolutionize modern healthcare - do organizations have proactive strategies & risk mitigation in place?

What role does Amazon Pharma Play in the disruption of US healthcare system?

Insight into how Kerri Webster, Chief Analytics Officer at Children's Hospital Colorado, led a data team to predict patient numbers to within a 98% accuracy, 72 hours ahead of time.