Implementing the National Dense Breast Reporting Standard, Expanding Supplemental Screening Using Current Guidelines, and the Proposed Find It Early Act.
Wendie A BergRobin L SeitzmanJoAnn PushkinPublished in: Journal of breast imaging (2023)
Thirty-eight states and the District of Columbia (DC) have dense breast notification laws that mandate varying levels of patient notification about breast density after a mammogram, and these cover over 90% of American women. On March 10, 2023, the Food and Drug Administration issued a final rule amending regulations under the Mammography Quality Standards Act for a national dense breast reporting standard for both patient results letters and mammogram reports. Effective September 10, 2024, letters will be required to tell a woman her breasts are "dense" or "not dense," that dense tissue makes it harder to find cancers on a mammogram, and that it increases the risk of developing cancer. Women with dense breasts will also be told that other imaging tests in addition to a mammogram may help find cancers. The specific density category can be added (eg, if mandated by a state "inform" law). Reports to providers must include the Breast Imaging Reporting and Data System density category. Implementing appropriate supplemental screening should be based on patient risk for missed breast cancer on mammography; such assessment should include consideration of breast density and other risk factors. This article discusses strategies for implementation. Currently 21 states and DC have varying insurance laws for supplemental breast imaging; in addition, Oklahoma requires coverage for diagnostic breast imaging. A federal insurance bill, the Find It Early Act, has been introduced that would ensure no-cost screening and diagnostic imaging for women with dense breasts or at increased risk and close loopholes in state laws.
Keyphrases
- high resolution
- quality improvement
- case report
- adverse drug
- healthcare
- emergency department
- squamous cell carcinoma
- primary care
- type diabetes
- dendritic cells
- magnetic resonance
- risk assessment
- insulin resistance
- machine learning
- mass spectrometry
- adipose tissue
- polycystic ovary syndrome
- computed tomography
- deep learning
- health insurance
- human health
- contrast enhanced
- drug administration
- skeletal muscle
- data analysis
- lymph node metastasis
- drug induced