Survey data underscore need for tailored AI strategies in different healthcare settings
New survey data underscore the potential need for tailored artificial intelligence strategies in different healthcare settings.
Radiology providers are increasingly implementing AI to aid in breast cancer screening, with some charging extra for the option. However, information is limited on patient perceptions about the technology.
Researchers with UT Southwestern Medical Center, Dallas, recently dove further into this topic, surveying over 900 women about how they view AI’s deployment for screening. They found significant differences in patient perceptions among those treated by safety-net hospitals versus others imaged at academic medical centers, according to research published in Breast Cancer Research and Treatment.
“This is the first study to measure patient perspectives on AI in mammography in different hospital settings,” corresponding author Basak Dogan, MD, a professor of radiology at UT Southwestern, said in a statement from the school shared Tuesday. “It reveals how demographic and socioeconomic factors shape acceptance, trust and concerns about AI integration in breast cancer screening.”
Dogan and colleagues administered the 29-question survey across multiple breast imaging clinics between 2023 and 2024. They received a total of 924 responses, including about 400 from the safety-net setting and another 500 from academic medical center patients. Those imaged in the academic setting generally were older, mostly white, had higher incomes and education, and greater self-reported knowledge of AI compared to those treated in safety-net centers.
Higher education and self-reported AI knowledge were associated with greater acceptance of AI. Non-Hispanic black race was associated with lower acceptance of the technology, when controlling for other factors. Use of AI alone or as a second reader was accepted by about 74% of respondents, with lower chances among safety-net settings. About 72% said they supported deployment of AI in mammogram interpretation but only 7% would accept AI as the sole reader.
Nearly 60% would prefer to wait hours or even days for a radiologist interpretation, rather than relying on immediate AI results. This, UT Southwestern experts assert, reinforces the “importance patients place on human oversight and provider-patient interaction.” Across all settings, 84% wanted a rad to review an AI-identified abnormality, and only 44% wanted AI to review a rad-detected concern.
“As AI is increasingly used in breast imaging interpretation, attention should be paid to educate patients about the role of AI, obtain consent for its use, and provide safeguards to protect data privacy,” study leader Emily Knippa, MD, an associate professor of radiology, said in the announcement.
The study comes after German researchers published results from a similar AI survey in the journal Insights into Imaging on Jan. 5.
Marty Stempniak has covered healthcare since 2012, with his byline appearing in the American Hospital Association's member magazine, Modern Healthcare and McKnight's. Prior to that, he wrote about village government and local business for his hometown newspaper in Oak Park, Illinois. He won a Peter Lisagor and Gold EXCEL awards in 2017 for his coverage of the opioid epidemic.