Get emailed when this bill changes status, is amended, or advances.
Disclaimer: This page provides general informational summaries only and does not constitute legal advice. AI-generated content may contain errors. Always consult a qualified attorney for guidance specific to your situation.
Read full disclaimer →
If you operate a health care plan using automated decision-making in Illinois, you must ensure clinical peer review of adverse determinations by January 1, 2025.
State
Illinois
Bill Number
HB2472
Status
Passed Both Chambers
Risk Level
Medium
Category
Comprehensive
Effective Date
Jan 1, 2025
Last Action
Jul 19, 2024
Last Verified
May 1, 2026
Data Updated
May 1, 2026
What do these statuses mean?▼
Introduced— Filed in the legislature; not yet heard in committee
In Committee— Assigned to and being reviewed by a legislative committee
Passed— Approved by one or both chambers; awaiting further action
Signed / Enacted— Signed into law by the governor; may or may not be in effect yet
Dead / Vetoed— Vetoed, failed to pass, or session expired without action
Unknown— Status data not yet available or awaiting classification
Illinois HB2472 addresses the use of algorithmic processes in health care utilization reviews. It ensures that only clinical peers can make adverse determinations, impacting health care plans and utilization review programs. The bill aims to enhance accountability and compliance with accreditation standards.
Key Provisions
Only clinical peers can make adverse determinations based on medical necessity.
Utilization review programs must certify compliance with the National Committee for Quality Assurance.
Programs using automated processes must apply objective, evidence-based criteria.
Definition of 'adverse determination' modified to include decisions made using automated processes.
Latest Legislative Action
Public Act . . . . . . . . . 103-0656
Bill Sponsors (showing 5 of 30)
Name
Role
Barbara Wheeler
Primary
Bob MorganD
Primary
Deanne M. Mazzochi
Primary
Frank J. Mautino
Primary
Fred CrespoD
Primary
Jackie HaasR
Primary
Jim Durkin
Primary
John J. Millner
Primary
Julie Hamos
Primary
Kelly M. Burke
Primary
Laura FineD
Primary
Monique D. Davis
Primary
Terry Link
Primary
Tom Cross
Primary
Amy GrantR
Cosponsor
Bill CunninghamD
Cosponsor
CLAYBORNE
Cosponsor
Daniel Swanson
Cosponsor
HANNIG
Cosponsor
Iris Y. Martinez
Cosponsor
Janet Yang RohrD
Cosponsor
Jay HoffmanD
Cosponsor
Lilian JiménezD
Cosponsor
MITCHELL,JERRY
Cosponsor
MYERS,RICHARD
Cosponsor
Ram VillivalamD
Cosponsor
Rita MayfieldD
Cosponsor
RUTHERFORD
Cosponsor
SCHOENBERG
Cosponsor
STROGER
Cosponsor
Roll Call Votes (showing 3 of 5)
Third Reading ·
May 15, 2024
57 Yea 0 Nay 2 OtherPassed ✓
Insurance ·
May 7, 2024
10 Yea 0 Nay 1 OtherPassed ✓
Third Reading ·
Apr 19, 2024
106 Yea 0 Nay 12 OtherPassed ✓
Insurance, Amendment 2 ·
Apr 18, 2024
15 Yea 0 NayPassed ✓
Insurance ·
Mar 20, 2024
13 Yea 0 Nay 2 OtherPassed ✓
Amendments (2)
House Amendment 001Pending2024-03-14
House Amendment 002Pending2024-04-16
Compliance Checklist
Ensure clinical peer review of adverse determinations Who: Health care plans and utilization review programs Deadline: By January 1, 2025 Penalty: Potential penalties for non-compliance not specified
Certify compliance with accreditation standards Who: Utilization review programs Deadline: By January 1, 2025 Penalty: Potential penalties for non-compliance not specified
Full Legal Analysis
HB2472 establishes that health care plans and utilization review programs utilizing algorithmic automated processes for determining medical necessity must ensure that only clinical peers make any adverse determinations. This requirement aims to enhance the quality and accountability of health care decisions made through automated systems. The bill also mandates that these programs use objective, evidence-based criteria that comply with accreditation requirements, thus ensuring a standard of care in automated decision-making. Compliance is required by January 1, 2025. The bill modifies the definition of 'adverse determination' to specify that it includes decisions made using automated processes, emphasizing the importance of human oversight in automated health care decisions.
We use cookies for analytics to understand how visitors use this site. We also use essential cookies for site functionality.
See our Privacy Policy for details.