Typically, software placed on the market will undergo changes and updates after its initial release. In the case of healthcare AI, changes can occur, often unexpectedly, even when the developers have not updated the model.
In the latest episode of the Debunked podcast, MedCity News Editor-in-Chief Arundhati Parmar and Samir Batra, Managing Partner of Health Innovation Pitch, talked about a new report by Bessemer Venture Partners assessing AI ROI, their insights on the CVS Health restructure, FTC warning letters sent to healthcare organizations, and more.
Healthcare decision-makers, especially at pharmaceutical companies, must prioritize patient input. Data collected from social media listening is a significant step in the right direction.
Documentation tools have value. They solve a visible pain point well. But solving a visible pain point is not the same as solving the right one.
If we choose the quick fix, let us be honest about the consequences: when an unexamined algorithm leads to a fatal diagnostic error, the blame will not lie with the black box. It will lie with us, because we were too reckless to teach the fundamentals when we still had the chance.
Acute kidney injury is a common and sometimes serious surgical complication. Researchers at New York’s Mount Sinai health system are building AI models to better predict who's most at risk, so that healthcare providers can offer individualized, preventive care.
Flagship Pioneering unveiled Etcelera, a new startup formed by combining three of the firm’s portfolio companies. Etcelera's approach to drug R&D focuses on “causal intelligence,” which Flagship defines as predicting and understanding cause and effect in biology.
Veradigm examines key clinical trends, comorbidity profiles, and treatment trends across adolescence, reproductive years, and peri-/post-menopause. Download it today!
The U.S. Department of Health and Human Services (HHS) is rolling back several health IT certification requirements that could reduce certification costs for technology developers. But they may leave hospitals and health systems holding more responsibility for evaluating the safety and performance of the AI tools they purchase.
The federal government is testing whether artificial intelligence can help Medicare identify unnecessary medical care, speed up the prior authorization process, and reduce healthcare spending. But a new report based on evidence recovered from a lawsuit raises concerns about the AI experiment.
Companies aren't slowing down to ask if AI is ready for mental health; they're racing to build it in. Encoding the same unexamined standards into these tools means repeating the systemic issues marginalized groups have lived with for far too long.
The cost of waiting is not evenly distributed. Rural and critical access hospitals report under 50 percent adoption of even basic predictive tools, compared with 86 percent among top-tier system-affiliated hospitals. Every year without a bridge widens that gap, and it widens it fastest for the hospitals with the least room to absorb it.
Healthcare payments are no longer about transactions. It’s about controlling the revenue cycle. And increasingly, that control is not sitting with ISOs.
As generative AI moves toward performing increasingly consequential clinical functions, the American Medical Association (AMA) is urging the U.S. Food and Drug Administration to address a foundational question: Who is responsible for ensuring that these tools remain safe once they enter clinical practice?
A patient's automated risk score was reassuringly green. Pulling from a sparse medical record and infrequent acute visits, the model flagged him as low risk and routed him to the default, low-touch outpatient pathway — so why was the patient actively deteriorating?
Rick Abramson, a radiologist by training and the director of FDA's Digital Health Center of Excellence said, "We ended up putting out this idea that maybe these devices are starting to behave a little bit more like me as a physician than a heart valve or a defibrillator."
Some of the thorniest problems in medicine that AI can improve have nothing to do with diagnosis. They have to do with triage.
UPMC Enterprises is making a strategic investment in VeloSource with plans to further develop its AI-enabled staffing management platform.