Bill Overview
Title: Improving DATA in Public Health Act
Description: This bill addresses the collection and reporting of public health data with a particular focus on electronic health information. Specifically, the Centers for Disease Control and Prevention (CDC) must designate data and technology standards for public health data systems no later than two years after enactment of this act. These standards must, among other requirements, align with standards designated by the Office of the National Coordinator for Health Information Technology (ONC). In addition, the ONC must study matters concerning the use of standards for certain laboratory information. Further, the CDC may require, subject to some limits, additional reporting of public health and health care data by health care providers, health departments, and other entities for public health surveillance. Additionally, the bill addresses agreements regarding access to, exchange of, and use of public health data, including for public health preparedness and response activities. The Department of Health and Human Services (HHS) must develop or update interagency agreements while the CDC and the Office of the Assistant Secretary for Preparedness and Response may develop and update agreements with health departments and other nonfederal entities. The bill also requires HHS to award grants and other support for developing and disseminating best practices to collect electronic health information. Entities eligible for the awards include state, tribal, and local governments; health care providers; and nonprofits.
Sponsors: Sen. Kaine, Tim [D-VA]
Target Audience
Population: People whose wellbeing is linked to public health data improvements
Estimated Size: 331000000
- The bill focuses on improving public health data systems, which will likely impact all entities involved in health data collection and reporting.
- Healthcare providers are directly impacted as they need to comply with new reporting standards and data sharing agreements.
- Public health departments at local, state, and federal levels will see changes in data management and requirements.
- The general public will indirectly be impacted as improvements in public health data are aimed at enhancing public health outcomes.
Reasoning
- The Improving DATA in Public Health Act is intended to enhance public health data systems, which have far-reaching implications encompassing healthcare providers, public health departments, and indirectly the general public.
- Healthcare providers will be affected due to changes in data reporting requirements and the need to upgrade systems to comply with new standards. This could lead to initial adaptation costs followed by potential efficiency gains.
- Public health departments will gain better access to standardized health data, improving public health surveillance but requiring resource investment initially.
- The general public will benefit from improved public health responses and potentially better healthcare quality, although direct impacts on individual well-being may not be immediately measurable.
- The act involves a significant budget and serves a large population, so individual impacts might vary widely depending on each person's interaction with healthcare data.
Simulated Interviews
Public Health Official (New York City, NY)
Age: 45 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 20.0 years
Commonness: 5/20
Statement of Opinion:
- This policy is crucial for standardizing data, which will improve our response to public health emergencies.
- Initially, it will require substantial adjustments in our data systems.
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 | 6 |
Software Developer (Austin, TX)
Age: 30 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 10/20
Statement of Opinion:
- This policy creates growth opportunities for my company as more healthcare providers will need updated systems.
- It leads to better job security for me.
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 | 8 | 7 |
Retired (Rural Mississippi)
Age: 65 | Gender: female
Wellbeing Before Policy: 5
Duration of Impact: 5.0 years
Commonness: 15/20
Statement of Opinion:
- I hope this policy leads to better healthcare management and quicker service.
- I'm worried about my local clinic's capacity to adapt to new standards.
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 | 7 | 5 |
| Year 20 | 6 | 5 |
Primary Care Physician (Chicago, IL)
Age: 50 | Gender: male
Wellbeing Before Policy: 6
Duration of Impact: 10.0 years
Commonness: 10/20
Statement of Opinion:
- I am concerned about the costs associated with upgrading our current EHR system.
- Better data integration might help me provide more informed care to my patients.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 5 | 6 |
| Year 2 | 5 | 6 |
| Year 3 | 6 | 6 |
| Year 5 | 7 | 6 |
| Year 10 | 8 | 6 |
| Year 20 | 8 | 6 |
Data Analyst (San Francisco, CA)
Age: 28 | Gender: other
Wellbeing Before Policy: 8
Duration of Impact: 10.0 years
Commonness: 5/20
Statement of Opinion:
- This act will enhance my work efficiency with more standard data formats.
- It promotes better collaboration across public health sectors.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 8 | 8 |
| Year 2 | 9 | 8 |
| Year 3 | 9 | 8 |
| Year 5 | 9 | 8 |
| Year 10 | 9 | 8 |
| Year 20 | 8 | 8 |
Hospital Administrator (Miami, FL)
Age: 55 | Gender: male
Wellbeing Before Policy: 5
Duration of Impact: 20.0 years
Commonness: 7/20
Statement of Opinion:
- This policy mandates revisiting our data policies - a daunting task but necessary for future readiness.
- Initial disruptions are expected, but long-term benefits should outweigh them.
Wellbeing Over Time (With vs Without Policy)
| Year | With Policy | Without Policy |
|---|---|---|
| Year 1 | 4 | 5 |
| Year 2 | 5 | 5 |
| Year 3 | 6 | 5 |
| Year 5 | 8 | 5 |
| Year 10 | 8 | 5 |
| Year 20 | 8 | 5 |
Community Health Worker (Los Angeles, CA)
Age: 40 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 5.0 years
Commonness: 8/20
Statement of Opinion:
- Better data helps address health disparities more effectively.
- Transition periods might affect service delivery.
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 | 6 |
| Year 20 | 8 | 6 |
Health Policy Expert (Philadelphia, PA)
Age: 42 | Gender: female
Wellbeing Before Policy: 7
Duration of Impact: 10.0 years
Commonness: 5/20
Statement of Opinion:
- Data standardization is long overdue and could align US practices with global standards.
- Monitoring policy impacts and execution should be thorough.
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 |
Medical Student (Seattle, WA)
Age: 25 | Gender: male
Wellbeing Before Policy: 8
Duration of Impact: 20.0 years
Commonness: 12/20
Statement of Opinion:
- Excited about the potential integrations improving clinical practice education.
- Concerned about the financial implications for smaller clinics.
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 |
Nurse (Detroit, MI)
Age: 60 | Gender: female
Wellbeing Before Policy: 6
Duration of Impact: 15.0 years
Commonness: 8/20
Statement of Opinion:
- I hope this means less paperwork and more time with patients.
- The hospital's adaptation curve might be steep but beneficial.
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 | 8 | 6 |
| Year 10 | 9 | 6 |
| Year 20 | 8 | 6 |
Cost Estimates
Year 1: $150000000 (Low: $120000000, High: $180000000)
Year 2: $180000000 (Low: $150000000, High: $210000000)
Year 3: $200000000 (Low: $170000000, High: $230000000)
Year 5: $230000000 (Low: $200000000, High: $260000000)
Year 10: $300000000 (Low: $260000000, High: $340000000)
Year 100: $1000000000 (Low: $800000000, High: $1200000000)
Key Considerations
- The success and cost-effectiveness of the program are highly dependent on the inter-agency collaboration and the accuracy of data systems.
- The scalability and adaptability of the implemented data systems will influence long-term efficacy and cost management.
- Data privacy and security remain crucial aspects that need consideration to maintain public trust.