By Amina Niasse
NEW YORK, Sept 24 (Reuters) - AI tools are raising health spending for insurers by nearly $1 billion over two years, as providers bill for more severe patient care, according to a Blue Cross Blue Shield Association study released Thursday.
Between 2024 and 2025, providers more frequently billed for secondary conditions, or those stemming from a separate illness from the one they were treating, driving costs up by $653 million for BCBS companies during that period. Overall, more intense
care contributed $942 million in costs to BCBS firms over the two-year period, when compared to 2023, the study added.
BCBSA said providers used AI technology to identify secondary conditions by scanning existing patient records or using ambient scribes, which passively listen to conversations with patients and draft medical notes.
Patient visits where more complex medical care is documented command higher payments by insurers. In hospital settings, secondary or coexisting conditions can be categorized as more complex.
“If patients are truly sicker, we'd expect to see more treatment,” said Luke Chalker, senior vice president of product and data science at BCBSA.
Blue Cross Blue Shield Association has a network of 31 independent health insurance companies, covering over 100 million people, a representative said. BCBSA's study analyzed billing from inpatient settings where patients were admitted to medical facilities or hospitals.
For people undergoing major bowel surgeries, secondary conditions like partial blockages in the intestines and an overload of acid in the body increased 55% and 33%, respectively, the survey found between the first quarter of 2023 and the fourth quarter of 2025.
Health insurers such as Centene have said use of AI tools by health systems has led to aggressive or inappropriate reimbursement payments.
Dr. Razia Hashmi, vice president of clinical affairs at BCBSA, said more complex health cases did not correspond with higher rates of treatment for people with bowel disease surgeries. When patients were diagnosed with anemia, for example, Hashmi said blood transfusions, a common treatment for patients with a deficit in healthy red blood cells, did not increase.
"The disconnect between diagnoses and treatment suggests that AI is identifying more billable conditions, not sicker patients," said Chalker.
(Reporting by Amina Niasse; Editing by Aurora Ellis)
