Policy Impact Analysis - 117/HR/7188

Bill Overview

Title: Modernizing Department of Veterans Affairs Disability Benefit Questionnaires Act

Description: This bill requires that all disability benefit questionnaire data collected by persons other than employees of the Department of Veterans Affairs (VA) in the course of VA medical disability examinations must be transmitted to the VA in a machine-readable format.

Sponsors: Rep. Nehls, Troy E. [R-TX-22]

Target Audience

Population: People undergoing VA medical disability examinations

Estimated Size: 8000000

Reasoning

Simulated Interviews

Retired Army Veteran (Colorado Springs, CO)

Age: 68 | Gender: male

Wellbeing Before Policy: 5

Duration of Impact: 10.0 years

Commonness: 5/20

Statement of Opinion:

  • The process can be quite slow and frustrating sometimes, so anything to speed it up would be welcome.

Wellbeing Over Time (With vs Without Policy)

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

Health Care Provider (Fayetteville, NC)

Age: 34 | Gender: female

Wellbeing Before Policy: 7

Duration of Impact: 5.0 years

Commonness: 3/20

Statement of Opinion:

  • It's crucial to make data handling more efficient for the benefit of clients.

Wellbeing Over Time (With vs Without Policy)

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

VA Disability Claims Officer (Los Angeles, CA)

Age: 50 | Gender: male

Wellbeing Before Policy: 8

Duration of Impact: 20.0 years

Commonness: 10/20

Statement of Opinion:

  • Better machinery and processes can really streamline our work, reducing claim backlogs.

Wellbeing Over Time (With vs Without Policy)

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

Retired Air Force Veteran (San Antonio, TX)

Age: 39 | Gender: other

Wellbeing Before Policy: 6

Duration of Impact: 5.0 years

Commonness: 5/20

Statement of Opinion:

  • I am hopeful that the process improvements will reduce waiting time.

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 7 6
Year 20 7 6

Surviving spouse dependent on VA benefits (Jacksonville, FL)

Age: 73 | Gender: female

Wellbeing Before Policy: 4

Duration of Impact: 10.0 years

Commonness: 15/20

Statement of Opinion:

  • I depend on timely processing of benefits to cover my living expenses.

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 7 4
Year 10 7 4
Year 20 6 3

Retired Marine Corps Veteran (Phoenix, AZ)

Age: 65 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 10.0 years

Commonness: 6/20

Statement of Opinion:

  • If it means fewer errors and quicker results, I'm all for it.

Wellbeing Over Time (With vs Without Policy)

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

Active Duty Navy (San Diego, CA)

Age: 28 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 5.0 years

Commonness: 3/20

Statement of Opinion:

  • I hope this helps my claim process faster, as I need these benefits soon.

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 7 6
Year 20 6 5

Private Healthcare Provider (Nashville, TN)

Age: 55 | Gender: male

Wellbeing Before Policy: 7

Duration of Impact: 10.0 years

Commonness: 7/20

Statement of Opinion:

  • This will help streamline reporting and improve service outcomes.

Wellbeing Over Time (With vs Without Policy)

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

VA Administrator (Seattle, WA)

Age: 62 | Gender: female

Wellbeing Before Policy: 6

Duration of Impact: 20.0 years

Commonness: 2/20

Statement of Opinion:

  • The automation of data fills me with optimism for an increased claim processing speed.

Wellbeing Over Time (With vs Without Policy)

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

Veterans Advocate (Chicago, IL)

Age: 48 | Gender: other

Wellbeing Before Policy: 7

Duration of Impact: 10.0 years

Commonness: 8/20

Statement of Opinion:

  • Ensuring accurate and timely data transfer can really help the population we serve.

Wellbeing Over Time (With vs Without Policy)

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

Cost Estimates

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

Year 2: $40000000 (Low: $20000000, High: $60000000)

Year 3: $35000000 (Low: $15000000, High: $55000000)

Year 5: $30000000 (Low: $10000000, High: $50000000)

Year 10: $25000000 (Low: $5000000, High: $45000000)

Year 100: $10000000 (Low: $1000000, High: $25000000)

Key Considerations