Deafblind DATA Act
Summary
What This Bill Does
The Deafblind DATA Act responds to the problem that national estimates of the deafblind population vary widely. The bill notes estimates ranging from 10,000 children and 40,000 adults identified by the National Center on Deafblindness, to 70,000-100,000 people from utility-regulator estimates, to 2.47 million Americans with combined hearing and vision loss from the Helen Keller National Center. It requires the Census Bureau, within 180 days, to report to Congress on the feasibility of publishing a table and expanding American Community Survey data collection for people with combined hearing and vision loss. Beginning in 2026, the Bureau must publish annual state-level tables summarizing ACS respondents who answered yes to being both deaf and blind, including sex, race, age, employment status, educational attainment, earnings, and poverty status, with personally identifiable information withheld.
Who Benefits and How
Deafblind individuals benefit because federal data would better identify the population needing communication, education, employment, and social-support services. Disability service providers benefit from more consistent state-level data for planning programs and outreach. State governments benefit from annual ACS tables that can inform service allocation and disability policy. Researchers benefit because the bill creates a public data source for demographic and economic characteristics of deafblind respondents.
Who Bears the Burden and How
The Census Bureau must assess feasibility, publish annual tables, protect privacy, and potentially expand ACS data collection. Congressional committees must receive and evaluate the 180-day feasibility report. ACS data teams must cross-reference hearing and vision limitation responses and suppress personally identifiable information. Program planners may need to adjust assumptions if the new data shows different population counts than older estimates.
Key Provisions
- Requires a Census Bureau report within 180 days on publishing deafblind data tables and expanding ACS collection.
- Directs annual publication beginning in 2026 of state-level ACS tables for respondents who are both deaf and blind.
- Requires demographic and economic fields including sex, race, age, employment, education, earnings, and poverty status.
- Protects personally identifiable information from publication.
Evidence Chain:
This summary is generated from the full bill text using AI analysis. Expand "Detailed Analysis" below for identified beneficiaries/burden bearers with clause-level evidence links.
At a Glance
What This Bill Does
Requires the Census Bureau to report on publishing American Community Survey cross-tabulations for people who are both deaf and blind and to publish annual state-level tables beginning in 2026 with demographic and economic characteristics while protecting personally identifiable information.
Key Policy Areas
Disability, Census, Data, Civil Rights
Primary Purpose
Requires the Census Bureau to report on publishing American Community Survey cross-tabulations for people who are both deaf and blind and to publish annual state-level tables beginning in 2026 with demographic and economic characteristics while protecting personally identifiable information.
Policy Domains
Resolution provisions
Identified Gains
- Deafblind individuals
- Disability service providers
- State governments
- Researchers
Identified Costs
- Census Bureau
- Congressional committees
- ACS data teams
- Program planners
Sponsors
Legislative Progress
In CommitteeMrs. McClain Delaney (for herself, Mrs. Cherfilus-McCormick, Mr. Cohen, Ms. …
Referred to the House Committee on Oversight and Government Reform.
Introduced in House
Stakeholder Effects
cui bono?How this legislation distributes effects. Mention counts reflect frequency, not effect magnitude.
ACS data teams, Census Bureau, State governments
Positive-direction: State governments
Negative-direction: ACS data teams, Census Bureau
Bill Structure & Actor Mappings
Who is "The Secretary" in each section?
We use a combination of our own taxonomy and classification in addition to large language models to assess meaning and potential beneficiaries. High confidence means strong textual evidence. Always verify with the original bill text.
Learn more about our methodology