HIMSS24

Talkdesk can integrate AI with EHRs so patients don't have to repeat information and agents can express empathy in their calls, explains Patty Hayward, the company's healthcare and life sciences GM.

Forming collaborative healthcare ecosystems between health systems, insurers and IT developers helps supports the goal of delivering cost-effective preventive care, says Adam Chee, associate professor, National University of Singapore.

Many healthcare organizations underestimate the expense of on-premises cybersecurity and may miss early signs of an attack if teams don’t know what to look for, says Max Rogers, senior director of the security operations center at Huntress.  

Hours a day in different workflows on multiple systems leads to burnout. Nicole Rogas, president of symplr, explains how the company consolidates systems and uses AI to automate workflows - leading to more time for patients.

Cybersecurity and artificial intelligence are the chief concerns in the region, followed by cloud adoption and use of machine learning in medical imaging, says Sam Amory, managing director for the Middle East and Africa at Dedalus.

Symplr uses AI and predictive analytics to perform mundane tasks such as time card management for nurse managers. This allows them to spend more of their time on direct patient care, says Tony DiGiorgio, the company's chief architect.

Now that participation among multiple QHINs is allowed under TEFCA, The Sequoia Project addresses how cybersecurity requirements apply to all entities exchanging protected health data.

As the first organization in the world to reach Stage 7 of the new INFRAM24, the health system has seen valuable improvements in cybersecurity, sustainability and care delivery, says Dr. Farukh Usmani, its medical director of digital technology services.

They may need help from AI tools or peer support groups to make knowledgeable decisions based on data from their medical records, says Grace Cordovano, cofounder of Unblock Health and a 2024 Changemaker Award recipient.  

There are limitations to current large language models for coding and identifying clinical quality measures, says Dr. Jay Anders, CMO at Medicomp Systems, who discusses the need for further model training and clinical vigilance to avoid errors.