US-based healthcare company RXNT has launched Ambient IQ as a standalone, AI ambient listening and documentation platform, extending access to physicians nationwide after an earlier rollout to its electronic health record (EHR) customers.

Ambient IQ operates independently of specialty and system type, with straightforward integration into any EHR system or with RXNT's clinical software.

In contrast to third-party tools that integrate with EHR systems but offer limited functionality, Ambient IQ has been developed with native integration into RXNT's platform.

This allows the ambient scribe to accurately identify and record essential details during patient encounters, significantly reducing documentation time by as much as 70%.

Ambient IQ enhances the capture of clinical details, ensuring they are recorded more consistently and accurately, thereby minimising errors and omissions that could affect subsequent decision-making.

Additionally, RXNT's AI-powered Encounter Insights feature provides concise summaries of clinical encounters, allowing healthcare providers to swiftly identify and rectify any discrepancies in charting.

RXNT founder, president and CEO Randy Boldyga said: “When a patient shares health concerns during a 20-minute appointment, it’s nearly impossible for a physician to simultaneously listen, recall the patient’s full medical history, identify subtle connections, and document everything accurately.

“Ambient IQ acts as an intelligent note-taking assistant, capturing the conversation with a deep understanding of medical language and context to generate full, precise clinical notes.”

With Ambient IQ, providers can start a session compliant with the Health Insurance Portability and Accountability Act (HIPAA) from a mobile device, generating full notes using templates tailored to specialities, including psychiatry and behavioural health.

RXNT emphasises its native build within its clinical system and use of millions of data points and historical insights to interpret medical language and context, aiming to structure documentation with less errors.