Smart EHR UI Market Map: When native workflows just won’t cut it
This is part of Elion’s weekly market map series where we break down critical vendor categories and the key players in them. For more, become a member and sign up for our email here.
Epic has said it is developing 100-plus AI products across their portfolio—among them a chatbot demoed at UGM that followed up with a post-wrist-surgery patient using video analysis to assess the wrist’s condition. Given that, it’s hard to imagine a world where Epic doesn’t end up dominating the market for AI clinician assistants—or even healthcare AI in general. However, catering to such a broad range of users has its drawbacks.
Not only does it take a long time to bring fully-featured products to market (we can expect at least 3-5 years for the video analysis demo to become a reality), but products designed for everyone often lack the streamlined efficiency of those built for specific purposes. Products in the Smart EHR UI category are taking the gamble that a customized EHR UI that incorporates AI can ultimately outperform more feature-rich EHRs in specific workflows.
Smart EHR UI products sit on top of the EHR and other data sources, surfacing and summarizing workflow-specific, relevant information to clinicians, and also write back to the EHR in useful ways. They use AI and machine learning, in addition to natural language processing and advanced search capabilities, to deliver a more useful interface for specific workflows than the more fully-featured EHR beneath it.
Evolution of the Smart EHR UI
In many cases, these applications started off as EHR sidecars, existing before the GenAI hype cycle, and they have workflow- and specialty-specific UIs that give clinicians a more customized, streamlined workflow for their most common and high-priority tasks.
In practice, this means better visualizations for workflows like chronic condition management or discharge planning, as well as summarization of patient records for pre-charting, team handoffs, or HCC (hierarchical condition category) capture. However, they’ve added on key AI capabilities for record summarization, diagnosis, and documentation, making them contenders in the race to become the AI operating system.
Use cases across care sites
For health system workflows—including inpatient care and outpatient primary care—some examples include:
Wellsheet, which has taken a workflow-focused approach with pre-charting, care team collaboration, and discharge planning.
Google Care Studio, which focuses on smart search and chronic condition management.
Other hospital-focused EHR sidecars like CareAlign are more focused on care collaboration and record summarization.
In the home health setting, we’re seeing a similar trend with products like Apricot Health and io Health—both of which sit on top of EHRs and use a combination of genAI and workflow-focused UI design to improve the OASIS documentation workflow for nurses.
AI is just a tool
At the end of the day, we think the dominant players here will not be the vendors with the best AI capabilities, but the vendors who can wield AI technologies and build the best tools to accomplish all of the clinician workflows. It’s unclear if that will be monolithic EHRs, workflow-tailored sidecar EHR applications, or native AI platforms that integrate into the EHR. For now, the debate rages on.