Life & Health Insurance Data Provider · Head-to-head
KFF State Health Facts and Health Policy Data vs Addgene Plasmid Repository Catalog
Which life & health insurance data provider data fits your job: KFF State Health Facts and Health Policy Data, or Addgene Plasmid Repository Catalog. API, files, or your warehouse. Daily, weekly, or hourly.
KFF State Health Facts and Health Policy Data
Addgene Plasmid Repository Catalog
Where the fields line up
No shared field names. These two answer different questions.
| Field | KFF State Health Facts and Health Policy Data | Addgene Plasmid Repository Catalog |
|---|---|---|
Location | documented | not in this set |
Employer | documented | not in this set |
Non-Group | documented | not in this set |
Medicaid | documented | not in this set |
Medicare | documented | not in this set |
Military | documented | not in this set |
Uninsured | documented | not in this set |
Total | documented | not in this set |
Timeframe | documented | not in this set |
additional fields on request | documented | not in this set |
Plasmid # (id) | not in this set | documented |
name | not in this set | documented |
Coverage, side by side
| KFF State Health Facts and Health Policy Data | Addgene Plasmid Repository Catalog | |
|---|---|---|
| Geographic | All 50 US states, District of Columbia and territories, plus a United States national row | Global: deposits from 7,024 labs, requests from 113 countries |
| Temporal | Annual coverage blocks 2008-2024 (ACS-based); monthly Medicaid/CHIP enrollment January 2014 - April 2026 (preliminary) | Current catalog with 'Available since' dates reaching back to 2004 |
What each contains
They tie on 1 attribute. Pick by fit, not by loyalty.
| KFF State Health Facts and Health Policy Data | Addgene Plasmid Repository Catalog | |
|---|---|---|
| Source | KFF (Kaiser Family Foundation) | Addgene |
| Subject lens | State-level US health insurance coverage, Medicaid/CHIP and Medicare enrollment, ACA Marketplace costs, demographics and health-status indicators | Repository catalog metadata for research plasmids, viral vectors and recombinant antibodies |
| Geographic coverage | All 50 US states, District of Columbia and territories, plus a United States national row | Global: deposits from 7,024 labs, requests from 113 countries |
| Temporal coverage | Annual coverage blocks 2008-2024 (ACS-based); monthly Medicaid/CHIP enrollment January 2014 - April 2026 (preliminary) | Current catalog with 'Available since' dates reaching back to 2004 |
| Detail level | Indicator rows per state per period, some breaking out age bands, income groups, race/ethnicity and gender | One record per plasmid, viral prep or antibody, with backbone, selection, growth, insert and promoter attributes |
| Record formats | Tabular indicator tables with documented columns | Catalog records in JSON; sequence records in GenBank |
| Scale | 800+ indicators across about 52 geographies | 176,220 plasmids, 1,092 viral vectors, 283 recombinant antibodies |
| Best for | US coverage benchmarks, Medicaid and Marketplace tracking, policy analysis | Construct-level research metadata, citation evidence, lab operations |
What each does better
KFF State Health Facts and Health Policy Data
One schema answers who is covered by what, where. The 2024 total-population block reads the United States at 48.6 percent employer-covered, 20.4 percent Medicaid, 14.8 percent Medicare, 6.6 percent direct purchase, 1.3 percent military and 8.2 percent uninsured across a 331.2 million base - and the same columns repeat state by state, which is how the interesting gaps surface: California runs Medicaid at 27.8 percent with uninsured at 5.9 percent, while Texas posts Medicaid at 14.8 percent and uninsured at 16.8 percent. Those annual blocks rest on the American Community Survey, the same survey behind table S2701.
Currency at the program margin. Monthly Medicaid/CHIP enrollment runs from January 2014 through April 2026 (preliminary): 73,871,024 nationally in April 2026 against a pre-ACA average of 56,511,799 - a 28.5 percent climb - with Alabama at 934,554, up 16.9 percent. See Medicaid managed care for how those program splits get used.
Policy context around the numbers. Thirteen categories spanning the ACA, disparities, mental health and substance use, women's health and provider service use, plus custom multi-indicator state reports and analyst-grade tracker work on Marketplace premiums, deductibles and metal-tier selection. Nothing in this pairing matches that editorial layer.
the Addgene Plasmid Repository Catalog
Item-level scientific resolution. Plasmid 105731 - 'pcDNA6 asyn A53T' - resolves to a pcDNA6 backbone from Invitrogen in a mammalian-expression configuration, ampicillin selection at 100 ug/mL, propagation in DH5alpha at 37 degrees C, a human alpha-synuclein A53T insert keyed to Entrez gene SNCA, and a CMV promoter. An aggregate statistics file cannot answer a question like that; a per-specimen ledger can.
Evidence of scientific weight. Citation counts ride along on search listings, with heavily used constructs reaching into the thousands of citing articles, and the repository's own adoption ledger is large: more than 2.4 million material requests from 113 countries. For anyone scoring constructs by demonstrated usefulness, that column is the point.
Scale with a consistent attribute spine. 176,220 plasmids from 7,024 labs carry the same fields end to end, browsable by research family - a CRISPR query alone returns 24,827 catalog entries - alongside 1,092 viral vectors sortable by engineered serotype and function, and 283 recombinant antibodies.
Where they're equivalent
On everything that makes a record trustworthy, they match. Both score 8/10, above the catalog's 7.81 average. Both field dictionaries were verified during research. Both publish tabular records with documented columns rather than narrative reports alone, and both attribute every figure upward - KFF indicators carry dated source citations to CMS and federal programs, Addgene records credit depositing labs and publications. Both are curated by nonprofit institutions that treat the data as mission rather than merchandise. And both hold reference positions in this slice: KFF as the widest state-level health-policy compendium among its 16 primary datasets, Addgene as the largest specimen-metadata record in it.
The verdict
Verdict: sample both, pick by fit - they are different instruments pointed at loosely adjacent questions.
Take KFF State Health Facts and Health Policy Data if your question names American coverage. Rate benchmarking against state uninsured rates, managed-care and Medicaid exposure, Marketplace premium and deductible tracking, actuarial inputs for premium prediction work - anything answered by state-by-state distributions. Accept the border: no non-US geography appears anywhere in it.
Take Addgene Plasmid Repository Catalog if your question names a construct. Life-sciences landscape scans, citation-weighted evidence that a gene or cloning strategy matters, specimen-level attributes for lab operations - anything keyed to an individual plasmid, vector or antibody. Accept the lens: coverage and insurance concepts are absent by construction.
Market researchers and investors and quants usually want KFF first for coverage-economics work; data scientists and journalists and academics split by brief, and complements such as small-area health insurance estimates sharpen the KFF side when substate resolution matters.
Sample both, pick by fit. See KFF State Health Facts and Health Policy Data · See Addgene Plasmid Repository Catalog
Or take both in one feed
Honestly - rarely in the same pipeline. There is no join key: state-by-period coverage cells and plasmid-level specimen records share no entity, and forcing one produces nonsense. Where they legitimately coexist is at the brief level: a health-economics engagement that also touches life-sciences clients, or a due-diligence file covering both an insurer's book and a biotech's research dependencies. Order each on its own grain - populations for KFF, specimens for Addgene - and align on calendar, not keys.
Browse the rest of the shelf at the Life & Health Insurance data hub. Datadory ships either record alone or both merged onto one calendar, delivered daily, weekly, or hourly - your call. Or take both in one feed.
API, files, or your warehouse. Daily, weekly, or hourly.
Fair questions
Is KFF State Health Facts and Health Policy Data better than the Addgene Plasmid Repository Catalog?
Better at different jobs. KFF owns American coverage statistics: more than 800 indicators placing employer, Medicaid, Medicare, Marketplace and uninsured shares on every state, with monthly Medicaid/CHIP enrollment through April 2026. Addgene owns specimen metadata: structured records for 176,220 plasmids, 1,092 viral vectors and 283 recombinant antibodies with backbone, resistance, insert, promoter and citation-count fields.
Do the two datasets cover the same ground?
Barely. They share an industry filing and little else: KFF describes populations by state and period, Addgene describes individual biological constructs deposited by 7,024 labs worldwide. There is no shared entity, identifier or unit of measure between them.
Which dataset is bigger?
Depends on the axis. Addgene holds roughly 178,000 physical items - 176,220 plasmids, 1,092 viral vectors and 283 recombinant antibodies. KFF holds fewer objects, 800-plus indicators, but repeats each across about 52 geographies year after year, so its measured cells accumulate fast.
Which should a health insurer sample first?
KFF. The 2024 distribution puts the United States at 48.6 percent employer coverage, 20.4 percent Medicaid and 8.2 percent uninsured, and the state columns expose exactly the variation between pricing teams and network planners - California's 27.8 percent Medicaid against Texas's 14.8 percent, for instance. Add Addgene only if the brief reaches life-sciences clients.
Can Datadory deliver both datasets together?
Yes. Each arrives normalized to its verified field dictionary with sample rows for inspection before anything ships, and both can land on one calendar, delivered daily, weekly, or hourly, your call. They keep separate grains: populations from KFF, specimens from Addgene. Or take both in one feed.