Policy Impact Analysis - 117/S/4915

Bill Overview

Title: Restoring Accountability in the Indian Health Service Act of 2022

Description: 2022 This bill establishes a series of programs and requirements relating to recruitment and retention in the Indian Health Service, including provisions regarding pay, credentialing, and housing needs of workforce personnel.

Sponsors: Sen. Barrasso, John [R-WY]

Target Audience

Population: American Indian and Alaska Native individuals using Indian Health Service

Estimated Size: 2600000

Reasoning

Simulated Interviews

Registered Nurse (Navajo Nation, AZ)

Age: 34 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 5.0 years

Commonness: 15/20

Statement of Opinion:

  • The policy sounds promising if it means better pay and housing for us. I'm worried it's just talk and won't lead to real changes.

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 8 5
Year 10 9 5
Year 20 9 6

Primary Care Physician (Anchorage, AK)

Age: 28 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 10.0 years

Commonness: 10/20

Statement of Opinion:

  • Improved credentialing and housing could help retain more professionals like me in the long term.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 7 6
Year 3 8 6
Year 5 8 6
Year 10 9 6
Year 20 9 7

IHS Administrator (Minneapolis, MN)

Age: 48 | Gender: other

Wellbeing Before Policy: 5

Duration of Impact: 8.0 years

Commonness: 8/20

Statement of Opinion:

  • We always need more funding and this policy could help, but I worry about the long-term commitment.

Wellbeing Over Time (With vs Without Policy)

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

Community Health Representative (Cheyenne, WY)

Age: 54 | Gender: female

Wellbeing Before Policy: 4

Duration of Impact: 20.0 years

Commonness: 13/20

Statement of Opinion:

  • Better staffing and pay to match efforts would increase job satisfaction significantly.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 5 4
Year 2 6 4
Year 3 7 4
Year 5 8 4
Year 10 8 4
Year 20 8 4

Medical Student (San Diego, CA)

Age: 22 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 5.0 years

Commonness: 5/20

Statement of Opinion:

  • Increased opportunities and better support may drive more students like me to consider careers in IHS.

Wellbeing Over Time (With vs Without Policy)

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

Retired (Phoenix, AZ)

Age: 65 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 7.0 years

Commonness: 18/20

Statement of Opinion:

  • If the services improve as stated, it could mean a lot for the younger ones especially. I'm skeptical though.

Wellbeing Over Time (With vs Without Policy)

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

Dentist (Tulsa, OK)

Age: 37 | Gender: female

Wellbeing Before Policy: 5

Duration of Impact: 15.0 years

Commonness: 12/20

Statement of Opinion:

  • Credentialing and pay increases could help, but real change takes time.

Wellbeing Over Time (With vs Without Policy)

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

Public Health Official (Sante Fe, NM)

Age: 42 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 20.0 years

Commonness: 9/20

Statement of Opinion:

  • Ensuring these changes are allocation-transparent is key to lasting improvements.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 7 6
Year 3 8 6
Year 5 8 6
Year 10 9 6
Year 20 9 7

Pharmacist (Billings, MT)

Age: 30 | Gender: male

Wellbeing Before Policy: 6

Duration of Impact: 10.0 years

Commonness: 6/20

Statement of Opinion:

  • If housing assistance is real, it would make a huge difference for my family.

Wellbeing Over Time (With vs Without Policy)

Year With Policy Without Policy
Year 1 7 6
Year 2 8 6
Year 3 8 6
Year 5 8 6
Year 10 9 7
Year 20 9 7

Software Engineer (Los Angeles, CA)

Age: 29 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 0.0 years

Commonness: 20/20

Statement of Opinion:

  • This policy doesn't affect me directly, but improvements in any healthcare system can have broad benefits.

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 7 7
Year 20 7 7

Cost Estimates

Year 1: $250000000 (Low: $200000000, High: $300000000)

Year 2: $260000000 (Low: $210000000, High: $310000000)

Year 3: $270000000 (Low: $220000000, High: $320000000)

Year 5: $290000000 (Low: $240000000, High: $340000000)

Year 10: $320000000 (Low: $270000000, High: $370000000)

Year 100: $560000000 (Low: $500000000, High: $620000000)

Key Considerations