One of the many offers at HIMSS21 is The Future of Healthcare, a continuation of the data-driven virtual event State of Healthcare, which HIMSS held in June. In this special episode of HIMSSCast, we welcome all four HIMSS Trust partners and moderators to give a sneak peek of the August event.

Moderator Jonah Comstock and MobiHealthNews Managing Editor Laura Lovett speak with Tom Kiesau, Director and Digital Health Leader at Chartis Group; Lauren Goodman, Director of Market Intelligence at HIMSS; Shreesh Tiwari, a director at ZS; and Dr. Darryl Gibbings-Isaac, Senior Manager in Accenture’s Health Strategy Practice.

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Conversation topics:

  • Health takeaways
  • Tension between learning the technology class and getting back to normal
  • Patient attitudes towards machine learning and artificial intelligence
  • Vendors Still Looking For A Value Proposition For AI, Barriers To Digital Health Adoption
  • How payers accept technological innovations
  • The future of digital health investments
  • Uncertainties: What Will Big Tech Companies Do? What will providers prioritize?
  • More uncertainties: value-based care acceptance, interoperability and access to patient data
  • Generational differences in patient attitudes
  • New competitive threats to health systems and payers
  • Keeping health equity and patient focus in mind as we shape the future of healthcare
  • The importance of trust in healthcare
  • The potential of technology to humanize healthcare
  • How COVID-19 has and has not changed healthcare

More about this episode:

Register for HIMSS21

The state of health, ICYMI

The future of healthcare

HIMSSCast: Healthcare State Summary and Preview of the Future of Healthcare

68% of health system executives are planning deeper investments in AI to meet strategic goals

Atrium Health’s rapid turnaround enabled digital innovations during the pandemic

Patients want to return to stationary retail after the pandemic

Oscar Health CEO on Insurance Company Transformation During COVID-19

Payers focus on artificial intelligence and machine learning



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