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Massachusetts General Court· H1210Accompanied a study order, see H5066

An Act relative to AI health communications and informed patient consent, the official text

Shown verbatim: the complete text as captured from the official source posted by the Massachusetts General Court, fetched 2026-07-15. Nothing is edited or removed. The official bill page.
	SECTION 1. Section 70E of Chapter 111 of the General Laws, as appearing in the 2022 Official Edition, is hereby amended by striking out, in line 46, subsection (b), and inserting in place thereof the following language; 
	(b) to confidentiality of all records and communications to the extent provided by law; 
	(b ½) to be informed, if the information they are receiving either verbally or in writing has been generated by artificial intelligence, and to be provided with instructions about how to contact a human healthcare provider in the event that such information was not previously reviewed and approved by their provider; 
	SECTION 2. Section 6 of Chapter 176O of the General Laws, as appearing in the 2022 Official Edition, is hereby amended by inserting after subsection (9) the following: 
	(9 ½) a disclosure if artificial intelligence algorithms or automated decision tools are being utilized or will be utilized in the claims review process, such a disclosure must include a summary of what tools are being used and how they are being used throughout the claims review process; 
	SECTION 3. Section 12 of Chapter 176O of the General Laws, as appearing in the 2022 Official Edition, is hereby amended by inserting the following subsection: 
	(g) A carrier shall submit to the division of insurance, no later than December 31 each year, a form to be prescribed by the division, which shall detail the artificial intelligence algorithms and data training sets that are currently being used or will be used in the utilization review process by the carrier. A carrier shall also submit an attestation, in a manner and form prescribed by the division, that such algorithms and training data sets have minimized the risk of bias based on the covered person's race, color, religious creed, ancestry, age, sex, gender, national origin, handicap or disability, and adhere to evidence-based clinical guidelines.  
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