Lighten the Load on Mammography Staff with Operational AI for Better Efficiency and Patient Care

The axiom “work smarter, not harder” has never been more relevant for the radiology industry than it is today. There is a clear shortage of radiologists that is only slated to get worse: An Association of American Medical Colleges (AAMC) report estimates a total shortage of between 13,500 and 86,00 U.S. physicians by 2036. Radiology falls into AAMC’s “other specialties” category, which estimates a combined specialty shortage of 19,500 physicians.

The numbers are no better for radiologic technologists. The American Society of Radiologic Technologists (ASRT) revealed the 2023 mammography vacancy rate was 13.6% — the highest it’s been since the survey started in 2003. Not only are there more vacant posts than ever before, but experts are also worried about what will happen as more radiology professionals retire. It’s a valid concern because radiology professionals skew older – the average age of radiologists is 48 and the average technologist is 43.  

Against this backdrop, the demand for imaging, in general, is increasing by 5.1% per year, according to market research firm MarketsandMarkets. Having more work to do but fewer people to do it is a recipe for burnout, which is exactly what’s happening in radiology. A European Journal of Radiology study reports burnout is increasing globally for radiologists with estimates reaching 88% for overall burnout and 62% for high burnout.

The question on everyone’s mind is how to reduce burnout and also streamline the radiology workload so that everyone truly can work smarter and not harder. The answer? Increased efficiency using AI. Operational efficiency with AI means functioning in such a way that radiologists and technologists achieve maximum productivity with minimum wasted effort or expense.

Operational efficiency with AI in the field of mammography can look like the following:

• Providing feedback to technologists in real time, for instance, about how to position the breast.
• Tailoring training recommendations to inform a technologist how, they, specifically, can improve their performance. This could include self-correction, skill enhancement, and consistent performance.
• Automating reporting and data analysis, which are crucial when sharing a radiology center’s performance.
• Supporting regulatory compliance. AI can streamline the accreditation and compliance process for FDA MQSA EQUIP and ACR Readiness, to name two programs. 

Operating more efficiently can support the radiology workforce with burnout by streamlining the workload. It can also alleviate some of the burden of higher imaging demand, but most importantly, efficiency will improve the quality of care for patients. More mammography efficiency means centering patients’ experiences because behind every image is a woman. Perhaps she’s anxious about her breast cancer screening results, or she’s receiving one for the first time. By improving efficiency, the patient gets her results faster and her imaging is done right the first time.

AI can augment human expertise and free up radiology professionals to not only accomplish more with less but also do the things that only humans can do: provide care and support to other humans.  

To learn more about how Operational AI can help improve the efficiency of your mammography screening programs, contact us here.