Partner Perspective: Health Systems Should Give Software Training a Closer Look; Role-specific, Just-in-Time Approach More Effective Way to Go

Health system IT leaders face a growing challenge: clinicians struggle to keep pace with rapid changes in EHRs and other digital tools. Bobby Zarr, Vice President of Healthcare at uPerform, believes AI can transform how health systems deliver training, improving adoption and satisfaction while reducing disruption.

“The pace of change is accelerating, and users feel disconnected from it,” Zarr said. “Instead of broad training sessions that may not be relevant, we need personalized learning in the moment of need.”

Traditionally, health systems deliver training through pre-scheduled sessions, often weeks before an upgrade goes live. However, Zarr said research shows that learners forget up to 72% of material within 48 hours. That creates a gap between training and execution, leading to frustration when users encounter changes they don’t remember learning about. Zarr sees AI as a way to tailor training, ensuring clinicians receive only the information relevant to them at the right time.

“What may seem like a minor change to IT could be a significant disruption to a clinician,” he explained. “When a button moves or a workflow shifts, users should be able to ask, ‘What changed for me?’ and get an immediate answer.”

The Importance of Personalized Training

One challenge is that not all users experience change the same way. Some clinicians quickly adapt to new systems and workflows, while others struggle when even minor adjustments are made. Zarr compared this to how people react to consumer technology. “Some users felt like the internet was ending when AOL went away,” he said. “There are always going to be those who find change overwhelming.”

This variability in learning and adaptation means that IT teams should not rely on a one-size-fits-all approach to training. Historically, training programs required all users to sit through large amounts of content, much of which was irrelevant to their specific role or workflow. With AI, health systems can now pinpoint individual learning gaps and deliver only the information each user needs.

Zarr emphasized the importance of delivering training within the clinician’s workflow. “These are critical workflows,” Zarr said. “If users can’t quickly learn new systems, patient care suffers, revenue is delayed, and IT trust erodes.”

One Size Doesn’t Fit All

Health systems frequently rely on vendor guidance to assess the significance of changes introduced in upgrades. However, Zarr pointed out that significance varies by user. “A vendor might provide general guidance on an upgrade’s impact, but it’s up to IT leadership to determine what that means for different roles,” he said. That process involves filtering information and ensuring the right users receive the right level of training. Yet many organizations struggle with the sheer volume of changes, leading to training that fails to address individual needs.

One persistent challenge is misalignment between IT and training teams. Many organizations place training under human resources rather than informatics, which creates a disconnect. “Training is often far removed from the teams making the changes,” Zarr said. “The most successful organizations align training with IT and informatics to ensure seamless communication.”

That misalignment contributes to a common complaint among clinicians: a lack of communication about IT-driven changes. Zarr explained that users often feel blindsided when workflows shift without adequate notice. When changes happen too quickly or without targeted communication, the result is a breakdown in trust.

Proactive communication is another key factor. IT teams often notify users about upcoming upgrades, but delays or last-minute changes can create confusion. “If a planned upgrade doesn’t happen as scheduled, users need to know,” Zarr said. “Otherwise, they lose trust in IT and feel left in the dark.”

Communication is Key