Salesforce has announced a new library of AI-powered capabilities for industries that offer healthcare-specific tools, enabling organizations to automate time-consuming tasks.
According to Salesforce, the new generative AI capabilities are available on Health Cloud and can be integrated with physician workflows to improve the quality and efficiency of patient care.
WHY IT IS IMPORTANT
As part of a larger effort to address operational pain points across 15 industries, the new AI capabilities are integrated into each of Salesforce’s 15 industry clouds.
Einstein Copilot enables healthcare organizations to collect patient data summaries in natural language, using a suite 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 said. Healthcare IT News Tuesday.
According to the Salesforce website, AI-driven patient services are enabled via Einstein prompts while working in member accounts within HealthCloud.
The copilot already uses conversational AI to send referrals and book appointments, which can help minimize the time and effort required to perform administrative tasks. In terms of data privacy and security, the company said Einstein Data Masking and Zero Data Retention Layer Protect patient data when sending prompts to large language models.
Other healthcare AI capabilities available from the new use case library support business operations, including validating insurance coverage and determining copays 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 noted that the new Industry AI capabilities are priced based on specific implementations.
THE BIGGER TREND
In March, Salesforce has launched the Einstein AI Copilot in the Einstein 1 platform to leverage a healthcare institution’s unique data and metadata in its Health Data Cloud.
The spokesperson said that verification of patient services and benefits are new capabilities that will reduce the need to switch between platforms, allowing for faster approvals and better support for physicians in their work on patient records prior to a visit.
Most organizations don’t have the time, expertise, or funding to build and train their own AI models. According to Salesforce, developing a training model alone can cost more than $100 million.
Many digital health leaders agreed last week at the HIMSS AI in Healthcare Forum in Boston about the rising costs of technology.
But managing ever-expanding technology footprints was just one of the challenges of AI adoption. In a market saturated with point-source solutions, decision makers must design change management processes within their organizations and address the labor implications of introducing new technologies into workflows, they said.
“The easiest things to pursue from a transformation perspective are operational workflows or back-office things, because those don’t touch patients,” Lee Schwamm, Chief Digital Health Officer at Yale New Haven Health System, advised during the forum Friday when asked what he sees as the biggest opportunity for AI transformation in the next three to five years.
“They are very low risk and relatively unregulated.”
ON THE RECORD
“Organizations of all sizes and budgets can now easily get started with practical AI tools specifically designed to solve their unique challenges,” said Jeff Amann, executive vice president and general manager of Salesforce Industries, in a statement.
Andrea Fox is Editor-in-Chief of Healthcare IT News.
Email address: afox@himss.org
Healthcare IT News is a publication of HIMSS Media.