Salesforce has announced a new library of artificial intelligence-enabled capabilities for industries that offer healthcare-specific tools. Organizations can deploy them to automate time-consuming tasks.
Available on Health Cloud, the new generative AI features integrate with clinician workflows and could help improve the quality and efficiency of patient care, Salesforce says.
WHY IT MATTERS
As part of a larger effort to address operational pain points across 15 Industries, the new AI capabilities are embedded in each of Salesforce’s 15 industry clouds.
Using the Einstein Copilot, healthcare organizations will be able to gather patient information summaries in natural language using a set of new patient data management features.
“For example, care coordinators can get comprehensive summaries of a patient or member including care plans, prescriptions, clinical encounters, prior authorizations, preferences and more” before an appointment, a Salesforce spokesperson told Healthcare IT News Tuesday.
According to the Salesforce website, AI-driven patient services are enabled through Einstein prompts while working in member accounts held within HealthCloud.
The copilot already leverages conversational AI to send referrals and book appointments, which can help minimize the time and effort needed to complete administrative tasks. As far as data privacy and security, the company said Einstein’s data masking and zero data retention layer protect patient information when prompts are sent to large language models.
Other healthcare AI features that will be available from the new use case library support business operations, including validating insurance coverage and determining out-of-pocket costs and eligibility.
These out-of-the-box AI features will be generally available in Salesforce in October, the spokesperson said. Meanwhile, the company’s website indicated that the new Industry AI capabilities are priced based on specific implementations.
THE LARGER TREND
In March, Salesforce launched the Einstein AI Copilot in the Einstein 1 Platform to leverage a healthcare organization’s unique data and metadata in its Health Data Cloud.
However, patient services and benefits verification are new capabilities that the company said will reduce switching between platforms, enabling faster approvals and better support for clinicians’ work in patient records ahead of visits, the spokesperson noted.
Most organizations lack time, expertise and funding to build and train their own AI models. Developing a training model alone could cost upwards of $100 million, according to Salesforce.
Escalating technology costs was a sentiment echoed by many digital health leaders last week at HIMSS AI in Healthcare Forum in Boston.
Managing ever-growing technology footprints, however, was just one of the challenges in procuring AI. In a market filled with point source solutions, decision-makers must architect change management processes within their organizations and address the labor implications of new technologies they introduce into workflows, they said.
“The simplest things to go after from a transformational perspective are operational workflows or back-office stuff because they don’t touch patients,” Lee Schwamm, chief digital health officer at Yale New Haven Health System, advised at the forum on Friday, when he was asked what he sees as the greatest opportunity for AI transformation over the next three to five years.
“They’re very low risk, and they’re relatively unregulated.”
ON THE RECORD
“Organizations of every size and budget can now easily get started with practical AI tools that were purposefully designed to solve their unique challenges,” Jeff Amann, executive vice president and general manager of Salesforce Industries, said in a statement.
Andrea Fox is senior editor of Healthcare IT News.
Email: [email protected]
Healthcare IT News is a HIMSS Media publication.
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