Predictive AI Helps Providers Plan Patient Care
At West Tennessee Healthcare, executives say they’ve saved more than $5 million over the past year by using an AI platform from Xsolis to review patient data, enabling them to predict when a patient will be discharged and communicate with payers on authorizations and any denials.
Are Healthcare Leaders Getting Their AI Priorities Straight?
Schwamm says the healthcare industry has become “accustomed” and “complacent” in healthcare IT, and Ai is presenting healthcare leaders with issues they haven’t encountered before. The AI evolution, he pointed out, is similar to the development of the software-as-a-service (SaaS) model, but health systems and hospitals haven’t developed the governance to regulate these tools before they’re used.
The Future of AI In Healthcare Is Not a Zero-Sum Game
The idea of “an AI arms race” between payers and providers toward a more efficient future is troubling in its own right. It adds to the perception of the future of artificial intelligence in healthcare as a zero-sum game, with health insurance companies on one side and clinicians on the other.
New Research Uses AI to Guide Radiation Treatment Protocols
In a study published in JACC: CardioOncology, a team from Brigham and Woman’s Hospital used an AI tool to better understand the risk of cardiac arrhythmia for patients undergoing radiation treatment for lung cancer. The results not only could lead to better treatment plans but also improve care for the estimated 1 in 6 patients who experience severe side effects, including death.
Ambient AI is Fast Becoming the Clinician’s Favorite Tool
The technology acts as a medical scribe, listening to the doctor-patient encounter and transcribing the interaction for the medical record. The finished product is available shortly after the encounter, enabling clinicians to quickly review and edit the information before it’s populated in the EHR.
Using AI to Address Nursing’s Biggest Pain Points
AI is the topic du jour in the healthcare space these days, and while a lot of the talk has centered on using the technology to improve back-office functions and give doctors more time in front of their patients, nursing leaders are eager to claim some of that spotlight.
Patients Are Finding Errors in Their Medical Records, and Want AI to Fix Them
The survey of more than 1,000 consumers, conducted by Propeller Insights for healthcare tech company Carta Healthcare earlier this month, finds an American public intrigued by the potential of AI, but also wary of its effects. For while 60% feel that the technology can improve the accuracy of medical records, more than half have concerns about security and more than 40% worry about accuracy.
There’s Value to Generative AI in Healthcare—if Leaders Understand Its Limits
While large language models like ChatGPT are poised to make substantial contributions to patient care, their immediate value likely won’t be derived in the ways clinicians and healthcare leaders think.
Improved Care Coordination with AI and Automation
Providers will increasingly look to AI and automation to drive operational efficiencies, improve care coordination and patient flow, relieve workers’ stress, enable staff to work at the top of their licenses, and enhance patient engagement.
Adopting AI the Right Way in Healthcare
Much of the power of AI analysis depends on data integrity, but the industry has already seen that patient-matching errors alone threaten the accuracy of AI outputs. In fact, 57% of healthcare leaders surveyed believe patient-matching errors will reach a crisis level in the next five to 10 years.