Accuracy and advertising may influence women’s willingness to pay for AI mammography, according to research published April 4 in the Journal of the American College of Radiology.
While high AI accuracy and advertisements for AI imaging tools may steer women toward paying for the technology’s use in breast imaging, “good” or “poor” error rates could drive women away, wrote a team led by Grayson Baird, PhD, from Brown University in Providence, RI.
“Radiology practices may wish to consider these findings when presenting patients with an option to pay for AI interpretation,” the Baird team wrote.
While AI’s uses continue to be explored in clinical practice, especially in breast imaging, there is currently no separate billing code for AI in screening mammography. Because of this, some radiology practices ask patients to pay out-of-pocket for AI interpretation of screening mammograms.
The researchers highlighted three potential issues with this approach: unclear pricing, the risk of exacerbating disparities in breast imaging due to added costs, and the creation of an unexplored psychological and ethical dilemma for patients and radiologists.
“Patients must decide what the value-added cost is to have AI also interpret their mammogram, which will be influenced by their experience and perception [whether correct or incorrect] of AI and breast cancer screening,” the researchers wrote.
Baird and colleagues studied how different price points and information conditions influence how women may or may not be willing to pay for AI in their breast cancer screening. Their research included 2,534 women, all above age 40, who were asked if they would pay for supplemental AI interpretations after being randomized to different price points ($50, $200, $500) and information conditions (no AI information, two AI accuracy rates, two AI error rates) versus a no AI condition.
Respondents showed more of a willingness to pay for AI when shown an advertisement (26.5%) or good AI accuracy rates (25.3%). However, they were least likely to pay when shown good (14.2%) or poor (7%) AI error rates (p < 0.0001).
Among price conditions, women showed more willingness to pay for less expensive AI (p < 0.0001). These included the following findings by price points: 24.4% at $50, 17.1% at $200, and 13.4% at $500.
The team also reported no significant differences based on information condition or price point with concerns about breast cancer, the chance of having breast cancer compared to most women by age comparison, or the probability of having breast cancer today for any of the breast cancer concern questions.
Finally, women showed lower trust when AI alone was used but still showed a desire to pay for AI.
“This suggests that participants want access to new technology but do not want to trade out the human component,” the study authors wrote.
The authors also suggested that while showing AI error rates may lead to fewer women choosing AI-assisted reads, this transparency could reduce legal exposure for stakeholders, including doctors, hospitals, and AI software vendors.
“There are unresolved legal and ethical challenges to the use of AI in mammography, but radiologists must take a lead in guiding the narrative moving forward,” they wrote.
Read the full study here.
