AI Model Finds 55% of Commercially Insured Women Unlikely to Get a Mammogram

What You Should Know:

– Cedar Gate Technologies’ advanced AI analytics platform has identified that 55% of commercially insured women are unlikely to get a mammogram. Leveraging this proprietary AI, Cedar Gate evaluated nearly 2.4 million women in its national healthcare benchmark database.

– The model surfaces a probability score for whether or not a woman is likely to get a mammogram based on U.S. Preventive Services Task Force (USPSTF) guidelines. These guidelines recommend that women between the ages of 40 and 75 at average risk of developing breast cancer have a screening mammogram once every two years. More than 1.3 million (54.6%) of 2,388,731 women in the recommended group fell below Cedar Gate’s predictive scoring threshold. These women were identified as “unlikely” to get a mammogram.

– The data also reveals that Cedar Gate’s commercially insured breast cancer patients have an average age of 58 when primarily diagnosed, notably younger than the overall median age of 63.

Predictive AI Model Data Findings

With data from more than 12 million member lives, Cedar Gate’s proprietary national Health Benchmark Database enables payers, self-funded employers, brokers, consultants, and providers to better understand patient and member needs. The data also shows that the average age of commercially insured patients in the Cedar Gate database with breast cancer as a primary diagnosis is 58 years. This is several years younger than the median age of 63 years for all populations (including people on Medicare), according to cancer.net. It highlights the value of capturing and analyzing information on targeted patient populations like those in Cedar Gate’s Health Benchmark Database.

Additionally, the data shows a marked increase of women with estrogen- and progesterone-receptor-positive cancers (ER+ / PR+) who received a genetic test between July 2021 and June 2022 compared to the previous year, rising 34% from 11% to 15%. Genetic testing can reveal whether someone has one of nine known and actionable genetic mutations. Understanding these genetic mutations can inform surveillance recommendations, care plans, and treatment. The data supports trends showing that genetic tests are becoming more accessible for people at higher-than-average risk of developing breast cancer or when recommended by a doctor.

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