ACR Releases Summary of MedPAC March Report
Highlighting MedPACās March findings on Medicare spending, payment adequacy, and key recommendations for physicians and hospitals.
Read moreA proposed rule to update regulations regarding health IT certification criteria and information blocking was published by the U.S. Department of Health and Human Services (HHS) Dec. 29. Additionally, HHS withdrew its 2024 proposed rule on these topics.
The latest proposals would reduce certification-related burdens for EHR developers, including elimination of AI model card (“nutrition label” style) transparency requirements. These model card requirements were previously intended to help providers understand if EHR-integrated AI models were “fair, appropriate, valid, effective, and safe” by making key information accessible to users about training, validation, and use. For example, a healthcare provider for pediatric patients would be able to access this information to confirm that a predictive decision support feature of their EHR platform was indeed trained and tested with pediatric data.
The proposals also provide clarifications and tightening of information blocking rules. To learn more about information blocking regulations, visit the ACR® resource page.
ACR is reviewing the latest proposed rule and preparing comments. For more information or to provide input on the proposed rule, contact Michael Peters, ACR Senior Director, Government Affairs, and Lindsay Robbins, ACR Regulatory Policy Specialist.
ACR Releases Summary of MedPAC March Report
Highlighting MedPACās March findings on Medicare spending, payment adequacy, and key recommendations for physicians and hospitals.
Read moreState AI Healthcare Bills Draw ACR Attention
State legislatures are advancing AI healthcare bills targeting insurer denials, clinical guardrails, and transparency for AI use in care and coverage.
Read moreACR Backs Fix to Burdensome Noridian TPE Reviews
ACR urges Noridian to end prepayment reviews of radiologistsā professional components, citing access barriers and high denial rates.
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