Bill Overview
Title: National All-Payer Claims Database Act of 2022
Description: This bill establishes a national all-payer claims database to collect and publish health care claims and payment information from various insurers.
Sponsors: Rep. Beyer, Donald S., Jr. [D-VA-8]
Target Audience
Population: people with health insurance
Estimated Size: 300000000
- A national all-payer claims database aims to collect healthcare claims data from all insurers, indicating that the target population would be all insured individuals.
- Health insurance is held by a majority of the global population, through public and private means, though the distribution varies by country.
- This database will influence how insurers manage and process claims, affecting policyholders' experiences and potentially their premiums and out-of-pocket costs.
Reasoning
- The policy impacts all insured individuals, which in the U.S. is about 300 million people.
- The budget constraints imply that initial years will focus on establishing the database infrastructure, with expectations of gradually increasing benefits over the long term.
- The short-term impact might be limited as insurers and healthcare providers adjust to using and contributing to the database.
- The long-term benefits could include more transparent pricing and potentially reduced healthcare costs, affecting Cantril wellbeing positively.
- Some individuals may not notice an immediate direct impact, as changes to premiums and services take time to manifest.
Simulated Interviews
Data Analyst (New York)
Age: 28 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 12/20
Statement of Opinion:
- I'm hopeful that the new database will eventually help lower my insurance premium by exposing pricing discrepancies.
- As a data analyst, I'm interested in how this data could be used to improve healthcare efficiency.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 7 | 7 |
| Year 2 | 7 | 7 |
| Year 3 | 7 | 6 |
| Year 5 | 8 | 7 |
| Year 10 | 8 | 7 |
| Year 20 | 9 | 8 |
Small Business Owner (Texas)
Age: 45 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 20.0 years
Commonness: 10/20
Statement of Opinion:
- As a business owner, I'm concerned about transparency in healthcare pricing.
- If this policy helps reduce costs, it will positively affect my business and employees.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 6 |
| Year 2 | 6 | 5 |
| Year 3 | 7 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 8 | 7 |
Retired Teacher (California)
Age: 60 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 5.0 years
Commonness: 8/20
Statement of Opinion:
- I hope the database will make claims processing more efficient, potentially reducing my out-of-pocket costs.
- I am skeptical about how quickly I'll see benefits.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 5 |
| Year 2 | 5 | 5 |
| Year 3 | 6 | 5 |
| Year 5 | 6 | 5 |
| Year 10 | 6 | 5 |
| Year 20 | 6 | 5 |
Healthcare IT Specialist (Florida)
Age: 34 | Gender: other
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 4/20
Statement of Opinion:
- This is an exciting development for the healthcare IT community.
- If implemented well, it could streamline operations and reduce errors.
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 | 9 | 7 |
| Year 10 | 9 | 8 |
| Year 20 | 9 | 8 |
Insurance Adjuster (Illinois)
Age: 50 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 20.0 years
Commonness: 5/20
Statement of Opinion:
- The new database will definitely change how we handle claims processing.
- I'm worried about the increased complexity in my job. Hopefully, it'll lead to better career opportunities.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 6 |
| Year 2 | 6 | 6 |
| Year 3 | 6 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 8 | 7 |
Nurse (Georgia)
Age: 39 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 8/20
Statement of Opinion:
- I'm interested to see how this policy will affect patient care and billing.
- Hoping for improved efficiency, but I expect some growing pains.
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 | 8 | 7 |
| Year 10 | 9 | 8 |
| Year 20 | 9 | 8 |
College Student (Oregon)
Age: 22 | Gender: male
Wellbeing Before Policy: 8
Duration of Impact: 5.0 years
Commonness: 15/20
Statement of Opinion:
- I'm curious to see if this will affect premium prices when I get my own insurance.
- This could have broader economic impacts on healthcare costs which interest me academically.
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 | 9 | 8 |
| Year 10 | 9 | 8 |
| Year 20 | 9 | 8 |
Pharmaceutical Sales Rep (Pennsylvania)
Age: 30 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 20.0 years
Commonness: 7/20
Statement of Opinion:
- There's potential for this to improve pricing transparency for medications.
- Depending on how insurers use the data, it could shift my work dynamic significantly.
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 | 7 |
| Year 10 | 8 | 7 |
| Year 20 | 9 | 8 |
Unemployed (Ohio)
Age: 55 | Gender: male
Wellbeing Before Policy: 4
Duration of Impact: 5.0 years
Commonness: 3/20
Statement of Opinion:
- I'm more concerned about immediate healthcare access than larger policy changes.
- If this helps reduce costs in the longer term, that would be beneficial.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 4 | 4 |
| Year 2 | 5 | 4 |
| Year 3 | 5 | 4 |
| Year 5 | 5 | 4 |
| Year 10 | 5 | 4 |
| Year 20 | 5 | 5 |
Policy Analyst (Washington D.C.)
Age: 40 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 20.0 years
Commonness: 4/20
Statement of Opinion:
- This database is a promising step for comprehensive healthcare reform.
- Long-term transparency is crucial for fair pricing and efficiency.
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 | 8 | 7 |
| Year 10 | 9 | 8 |
| Year 20 | 9 | 8 |
Cost Estimates
Year 1: $200000000 (Low: $150000000, High: $250000000)
Year 2: $150000000 (Low: $100000000, High: $200000000)
Year 3: $150000000 (Low: $100000000, High: $200000000)
Year 5: $0 (Low: $0, High: $0)
Year 10: $0 (Low: $0, High: $0)
Year 100: $0 (Low: $0, High: $0)
Key Considerations
- Ensuring data privacy and security is crucial to prevent breaches that could undermine trust in the healthcare system.
- Standardizing the data from numerous insurers will require significant coordination and might face technical challenges.
- Public acceptance and data privacy concerns could affect the rollout and effectiveness of the database.
- The balance of costs between federal and state responsibilities could influence the financial feasibility and political support for the initiative.