Webinar Complying with OCR Section 1557: Discrimination, Interpreters, Required Signs


Webinar  
Tuesday, August 06, 2024 10:00 AM - 12:00 PM   iCalendar Eastern Standard Time

This educational activity is provided jointly by AXIS Medical Education and North Carolina Healthcare Association
This webinar is being offered in cooperation with the Georgia Hospital Association
 
This webinar will discuss a law that applies to all hospitals, including Critical Access Hospitals and other health care providers such as physician offices and nursing homes. Under Section 1557 of the Affordable Care Act, the law addresses nondiscrimination required signs and notices, interpreters, a civil rights law for health care providers, and more. It forbids discrimination based on sex, race, color, national origin, age, and disability. It builds on long standing and familiar federal civil rights laws. This is the first law to prohibit discrimination based on sex, including gender and gender identity, in covered health programs and activities. This program will discuss changes by the Office of Civil Rights (OCR) to comply with the laws as well as case law regarding several issues important to hospitals. Hospitals are required to have a policy on nondiscrimination and must educate their staff. Patients must 1) be notified in a language they comprehend and 2) understand how to file a complaint if they encounter discrimination. Additionally, interpreters must be qualified, the definition of which will be explained. This program will provide resources and information to help meet the education requirements to ensure your employees know and follow this law. A list of each state‚Äôs 15 taglines will be provided as an additional resource. Sample notices to be posted and sample grievance procedures will also be provided.
 
Target Audience:
Chief Medical Officer, Chief Nursing Officer, Compliance Officer, Emergency Department Personnel, Joint Commission Coordinator, Medical Records, Quality Improvement personnel, Risk Manager, Legal Counsel.

Webinar