Bill Overview
Title: SOULS Act
Description: This bill requires the Centers for Disease Control and Prevention to include abortions, to the extent possible, when collecting and making available data on U.S. death numbers and rates.
Sponsors: Rep. Cawthorn, Madison [R-NC-11]
Target Audience
Population: People worldwide who rely on U.S. public health data and policy
Estimated Size: 334000000
- This bill will impact those involved in public health policy as it changes data reporting.
- Data scientists and epidemiologists who interpret mortality data will be affected due to changes in data scope.
- Public health officials who use CDC data for crafting health interventions will have access to more comprehensive data.
- Legal and policy frameworks around abortion might be influenced by any resulting awareness of new data trends.
- Healthcare providers, especially those involved in reproductive health, may need to adjust practices based on new data trends and policy responses.
Reasoning
- This policy will primarily impact professionals working with public health data, mortality statistics, and reproductive health. This includes data scientists, epidemiologists, policy makers, and healthcare providers.
- Impact on the general public may be minimal initially, as the policy's changes are more related to data interpretation rather than direct public services.
- The total budget and population size limit the policy's direct impact reach, focusing more on systemic and professional domains rather than individual life quality improvements.
- The interviews include diverse members of society ranging from data scientists and health policymakers to regular citizens interested in public health and reproductive rights.
Simulated Interviews
Data Scientist (Atlanta, GA)
Age: 35 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 5/20
Statement of Opinion:
- The inclusion of abortion data is significant as it provides a clearer picture of reproductive health trends.
- Professional workload may increase due to new data sets and adjustment of existing models.
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 | 7 |
| Year 20 | 9 | 7 |
Public Health Official (Washington, D.C.)
Age: 42 | Gender: male
Wellbeing Before Policy: 7
Duration of Impact: 15.0 years
Commonness: 3/20
Statement of Opinion:
- This policy will help refine public health interventions by providing more comprehensive data.
- Concerns about political implications of data that may be used in policy discussions separate from health benefits.
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 | 8 |
| Year 10 | 9 | 8 |
| Year 20 | 10 | 8 |
Healthcare Provider (New York, NY)
Age: 28 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 4/20
Statement of Opinion:
- While the data could aid in understanding patient needs, there may be increased scrutiny and pressure on clinics.
- Adjusting reporting practices and possibly training staff on new protocols will be necessary.
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 | 9 | 6 |
Health Policy Advisor (Chicago, IL)
Age: 50 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 10.0 years
Commonness: 3/20
Statement of Opinion:
- Vital for guiding future legislation; it might be used in debates over reproductive rights policy.
- Could shift public opinion and policy priorities related to women's health.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 6 | 5 |
| Year 2 | 7 | 5 |
| Year 3 | 8 | 5 |
| Year 5 | 8 | 6 |
| Year 10 | 9 | 6 |
| Year 20 | 9 | 6 |
Reproductive Rights Advocate (San Francisco, CA)
Age: 30 | Gender: other
Wellbeing Before Policy: 8
Duration of Impact: 12.0 years
Commonness: 4/20
Statement of Opinion:
- Access to more accurate data strengthens advocacy efforts with concrete information.
- Could lead to increased public awareness of reproductive health issues.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 8 | 8 |
| Year 3 | 9 | 8 |
| Year 5 | 9 | 8 |
| Year 10 | 9 | 8 |
| Year 20 | 10 | 8 |
Retired (Austin, TX)
Age: 65 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 8/20
Statement of Opinion:
- It's important for nurses to have access to as much health data as possible to offer informed care to patients.
- Could complicate public understanding of healthcare issues if not well-communicated.
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 | 7 | 6 |
| Year 10 | 7 | 6 |
| Year 20 | 8 | 6 |
University Student (Seattle, WA)
Age: 22 | Gender: male
Wellbeing Before Policy: 8
Duration of Impact: 3.0 years
Commonness: 10/20
Statement of Opinion:
- As a future public health professional, comprehensive data is invaluable for shaping sound policies.
- Could offer enriched contexts for academic studies and thesis work.
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 | 9 | 8 |
| Year 20 | 9 | 8 |
Epidemiologist (Miami, FL)
Age: 45 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 8.0 years
Commonness: 5/20
Statement of Opinion:
- A more complete dataset improves the quality of epidemiological modeling.
- Risks complicating current databases, requiring additional resources for data integration.
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 | 7 |
| Year 20 | 9 | 7 |
CDC Data Analyst (Boston, MA)
Age: 40 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 2/20
Statement of Opinion:
- Expect workload to increase initially as new data capture mechanisms are set up.
- The policy might impact how timely data updates are released, affecting public information flow.
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 | 9 | 7 |
| Year 20 | 9 | 7 |
Obstetrician/Gynecologist (Dallas, TX)
Age: 55 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 5.0 years
Commonness: 6/20
Statement of Opinion:
- Briefings on new data will be important for ensuring accurate patient advice and decisions.
- Sensitive data handling policies will need to be updated to reflect this change.
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 | 8 | 5 |
| Year 20 | 8 | 5 |
Cost Estimates
Year 1: $50000000 (Low: $30000000, High: $70000000)
Year 2: $30000000 (Low: $20000000, High: $40000000)
Year 3: $30000000 (Low: $20000000, High: $40000000)
Year 5: $20000000 (Low: $15000000, High: $25000000)
Year 10: $10000000 (Low: $5000000, High: $15000000)
Year 100: $1000000 (Low: $500000, High: $1500000)
Key Considerations
- The accurate recording and reporting of abortion-related data may face political and ethical challenges.
- Integration of new data streams involves logistic complexities and potential resistance from stakeholders.
- Public health outcomes and strategies may evolve as more precise data becomes available.
- Long-term benefits include potentially better-informed public health policies and interventions.