From detecting cancer and remote patient monitoring to streamlined documentation and automated prior authorizations, here are 15 proven clinical uses of AI — with results:
- Nearly 2,000 physicians and advanced practice providers at Altamonte Springs, Fla.-based AdventHealth are using Nuance’s DAX Copilot ambient AI scribe.
Since implementing the technology in April 2024, 86% of users report less burnout, 83% report improved work-life balance and job satisfaction, 80% report better patient experience, and 3 in 4 say they are less likely to leave clinical practice. - Yale New Haven (Conn.) Health System researchers employed an AI model called PanEcho to perform echocardiogram interpretation.
The model accurately estimated left ventricular ejection fraction, and detected moderate or worse left ventricular systolic dysfunction, right ventricular systolic dysfunction and severe aortic stenosis with a median normalized mean absolute error of 0.13.
- Charleston, S.C.-based MUSC Health has been leveraging agentic AI for administrative functions. The technology has been associated with a 7.6% reduction in no-show rates and a 30% increased digital intake for Spanish-speaking patients.
The health system has also deployed the AI agents to execute 40% of prior authorizations without human involvement, cutting 30 minutes of manual work to about one minute. - Since integrating Ambience’s generative AI for clinical documentation in 2024, Boise, Idaho-based St. Luke’s Health System has generated an extra $13,049 per clinician.
The health system reported a 41% reduction in active documentation time, a 41% reduction in time to chart closure, a 39% decrease in time spent documenting after hours, a 36% reduction in the number of clinicians reporting near-daily clinician burnout, a 22% increase in patient face time and a 17% decrease in time spent documenting after appointments. - Anthony Law, MD, PhD, an assistant professor in the department of otolaryngology at Atlanta-based Emory University School of Medicine, developed an AI model to detect throat cancer by listening to a patient’s voice.
The model, designed for in-clinic use through an app, has about an 93% success rate for identifying patients who have a mass in their larynx. - The Permanente Medical Group, part of Oakland, Calif.-based Kaiser Permanente, saved nearly 16,000 hours in documentation time over a 15-month period through the use of ambient AI.
- Chicago-based Northwestern Medicine radiologists used a generative AI system — designed by Northwestern engineers — to boost documentation efficiency by 15.5%.
- Cleveland-based MetroHealth improved its medication prior authorization process with an AI tool, cutting submission times from 18 hours to around five minutes and increasing approval rates by 15%.
In one case, AI submitted prior authorization for a hepatitis C patient’s prescription in five minutes, leading the health system to receive insurance approval within three hours and provide the medication within seven.
- Houston-based Texas Children’s Hospital developed an AI model to assess bone age in pediatric patients, reducing the time radiologists spend on image interpretation by 30% to 50%.
- Sacramento, Calif-based UC Davis Health developed an AI model to identify patients who may be at-risk for hospitalization or an ED visit within 12 months. Care teams then conduct proactive outreach to the at-risk patients. The initiative reduced hospitalization rates by 5% to 10% among at-risk patients.
- Somerville, Mass.-based Mass General Brigham employed ambient documentation using generative AI to alleviate administrative burden among its clinicians.
Around 60% of providers reported they were more likely to extend their clinical careers because of the technology, 20% reported reduced burnout symptoms and 80% said they were spending more time looking at their patients. - Kettering (Ohio) Health leveraged an AI-powered risk assessment tool to cut length of stay in half and improve care quality among patients undergoing angioplasty.
Use of the AI tool was associated with a decline in contrast-induced acute kidney injury from 10% to an average of 2.18%.
The tool was also associated with a decrease in bleeding complications from 2.15 events per month to an average of 1.54 events per month, and the average patient length of stay decreased from 3.44 days to 1.79 days.
- Sioux Falls, S.D.-based Sanford Health found the use of an ambient AI documentation tool significantly improved workforce satisfaction and retention.
After using the technology for less than a year, 88% of clinicians reported a reduction in burnout or fatigue, 90% reported higher job satisfaction and an improvement in their work-life balance, and 95% of clinicians stating it has helped reduce mental strain.
Additionally, 76% of clinicians said they were more likely to remain with Sanford Health and 80% reported were more likely to continue practicing in the medical field.
- Aurora, Colo.-based UCHealth uses AI to monitor about 22,000 hospital beds through a virtual care center. With the help of in-room cameras and AI embedded in the Epic EHR, a team of nurses virtually monitors medical-surgical and step-down beds across 14 hospitals for signs of sepsis.
The technology has enabled care teams to identify sepsis two to four hours earlier than if they had not been using AI, reducing mortality risk by 30% or more.
The technology also helps virtual care center teams remotely monitor patients at home, reducing at-home diabetes patients’ hemoglobin A1c levels by about 25%. - The use of ambient AI-scribe technology at Philadelphia-based Penn Medicine reduced clinical note time by about two minutes per appointment and after-hours “pajama time” from 50.6 minutes to 35.4 minutes per workday.
