Policy Impact Analysis - 117/HR/6625

Bill Overview

Title: Equal Access to Therapeutics Act

Description: This bill prohibits using race or ethnicity as a factor in decisions about an individual's access to COVID-19 treatments (e.g., monoclonal antibody therapies). Specifically, the Department of Health and Human Services (HHS) may not adopt any policy or guidance that allows race or ethnicity to be factored into such decisions. Furthermore, the Secretary of HHS shall be personally liable for the death of any individual who is denied access to COVID-19 treatments pursuant to a prohibited policy or guidance. The bill also prohibits hospitals or other health care providers that have policies restricting access to COVID-19 treatments based on race or ethnicity from receiving federal funds.

Sponsors: Rep. Davis, Rodney [R-IL-13]

Target Audience

Population: People needing COVID-19 treatment

Estimated Size: 330000000

Reasoning

Simulated Interviews

Restaurant owner (New York, NY)

Age: 56 | Gender: male

Wellbeing Before Policy: 5

Duration of Impact: 5.0 years

Commonness: 8/20

Statement of Opinion:

  • This policy seems fair because everyone deserves the same chance for treatment.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 5
Year 2 6 5
Year 3 6 5
Year 5 7 5
Year 10 7 5
Year 20 7 5

Nurse (Houston, TX)

Age: 34 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 5.0 years

Commonness: 5/20

Statement of Opinion:

  • Removing race as a factor makes sense, but each case is unique. We need to ensure everyone gets what they need.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 7 6
Year 3 6 6
Year 5 7 6
Year 10 8 6
Year 20 7 6

Health policy analyst (Los Angeles, CA)

Age: 45 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 3.0 years

Commonness: 7/20

Statement of Opinion:

  • The policy might avoid racial profiling in treatment allocation, but we must still address systemic disparities.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 6
Year 2 6 6
Year 3 6 6
Year 5 6 5
Year 10 7 5
Year 20 7 5

Software engineer (Chicago, IL)

Age: 29 | Gender: male

Wellbeing Before Policy: 8

Duration of Impact: 0.0 years

Commonness: 12/20

Statement of Opinion:

  • The policy doesn't affect me directly, but it could make the system more equitable.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 8 8
Year 2 8 8
Year 3 8 8
Year 5 8 8
Year 10 8 9
Year 20 9 9

Retired teacher (Miami, FL)

Age: 70 | Gender: female

Wellbeing Before Policy: 4

Duration of Impact: 10.0 years

Commonness: 6/20

Statement of Opinion:

  • I hope this means better chances for people like me to get necessary treatments.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 4
Year 2 5 4
Year 3 5 4
Year 5 6 4
Year 10 6 4
Year 20 6 5

Public health official (Seattle, WA)

Age: 50 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 5.0 years

Commonness: 9/20

Statement of Opinion:

  • A necessary step, but focus should also include defeating systemic inequities in health beyond a single policy.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 7
Year 3 7 7
Year 5 8 7
Year 10 8 7
Year 20 8 7

Journalist (Phoenix, AZ)

Age: 40 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 5.0 years

Commonness: 4/20

Statement of Opinion:

  • The policy seems good on paper, but real change comes from more than removing racial factors.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 7 6
Year 3 7 6
Year 5 7 6
Year 10 8 6
Year 20 7 6

Community activist (Atlanta, GA)

Age: 62 | Gender: male

Wellbeing Before Policy: 5

Duration of Impact: 20.0 years

Commonness: 7/20

Statement of Opinion:

  • It's a step in the right direction. More policies should target the root issues of systemic inequity.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 6 5
Year 2 7 5
Year 3 7 5
Year 5 7 5
Year 10 8 5
Year 20 8 5

Student (San Francisco, CA)

Age: 25 | Gender: other

Wellbeing Before Policy: 7

Duration of Impact: 2.0 years

Commonness: 10/20

Statement of Opinion:

  • Equal treatment access is essential, but the issue is nuanced, especially for underrepresented minorities.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 7
Year 2 7 7
Year 3 7 7
Year 5 7 7
Year 10 8 7
Year 20 8 8

Medical doctor (Minneapolis, MN)

Age: 37 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 10.0 years

Commonness: 8/20

Statement of Opinion:

  • Emphasizing equality in treatment is needed, but holistic changes are required for broader equity.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 7 6
Year 3 7 6
Year 5 8 6
Year 10 8 6
Year 20 8 6

Cost Estimates

Year 1: $50000000 (Low: $30000000, High: $70000000)

Year 2: $51000000 (Low: $31000000, High: $71000000)

Year 3: $52000000 (Low: $32000000, High: $72000000)

Year 5: $54000000 (Low: $34000000, High: $74000000)

Year 10: $59000000 (Low: $36000000, High: $78000000)

Year 100: $0 (Low: $0, High: $0)

Key Considerations