Data.gov Medicaid Managed Care Search Data

It is the precision cut of the largest public-data index in the world. Data.gov federates 552,271 datasets as of August 2026; the 'medicaid managed care' query narrows that universe to a few hundred records, and the verified top results are almost entirely CMS-authored. Ten titles anchor the slice: Managed Care Information for Medicaid and CHIP Beneficiaries by Month and by Year, the Medicaid Managed Care collection, Share of Medicaid Enrollees in Managed Care, Managed Care Enrollment Summary, Managed Care Enrollment by Program and Plan and by Program and Population (All and Duals), Managed Long Term Services and Supports (MLTSS) Enrollees, Managed Care Features By Enrollment Population and by Quality-related Requirements, the 2023 and 2024 Managed Care Programs By State editions, and the MMCC MCPAR PUF Data 2023 Medical Care Advisory Committee file.

State publishers fill in what a national table cannot see. data.ny.gov contributes Mental Health Continuity of Medication, Substance Use Disorder Ambulatory Follow-up and Mental Health Readmission outcome series cut to New York's managed-care population; California DHCS submits its own program files alongside them.

Every record arrives as structured DCAT-US metadata rather than a bare title: publishing organization with a government-level badge (Federal, State, County, City Government, University, Tribal, Non-Profit), theme and keyword tags, issued and modified dates, distribution media types, popularity counters, a catalog-sweep timestamp, a downloadable-flag and a relevance score.

At catalog level, rows describe datasets rather than beneficiaries: five entries from the August 2026 pass:

row_shape         : federal beneficiary table
title             : Managed Care Information for Medicaid and CHIP Beneficiaries by Year
publisher         : Centers for Medicare & Medicaid Services
organization_type : Federal Government
has_download      : true
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row_shape         : program collection
title             : Medicaid Managed Care
publisher         : Centers for Medicare & Medicaid Services
organization_type : Federal Government
has_download      : true
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row_shape         : MLTSS enrollment
title             : Managed Long Term Services and Supports (MLTSS) Enrollees
publisher         : Centers for Medicare & Medicaid Services
organization_type : Federal Government
has_download      : true
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row_shape         : program-feature edition
title             : 2024 Managed Care Programs By State
publisher         : Centers for Medicare & Medicaid Services
organization_type : Federal Government
has_download      : true
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row_shape         : state outcome series
title             : Mental Health Continuity of Medication: 2014-2021
publisher         : data.ny.gov
organization_type : State Government
has_download      : true

These are documented catalog records, not illustrations. Four of the five are federal CMS tables and one is a New York State outcome series, which is the publisher mix of the slice in miniature. Get a sample and the underlying row-level payloads land in whichever of these shapes you name, cut to your states, programs and years.

Twelve fields make up the confirmed core of every record. Two identify the asset (title, description), two establish provenance (publisher, organization.name), and the rest characterise it: the government-level organization.organization_type enum, the distribution pointer dcat.distribution[].downloadURL, publisher-assigned keyword and DCAT theme tags, the publisher-reported modified date, the last_harvested_date sweep stamp, the boolean has_download flag and the relevance _score. Definitions map one-to-one onto the catalog's own record structure gathered during the August 2026 research pass - nothing here is inferred, which is why anything beyond the confirmed core sits behind the request note rather than being padded with guessed columns.

Geography - United States throughout, at three altitudes: CMS national tables, state contributions led by New York (data.ny.gov) and California (DHCS), and local health department datasets where a jurisdiction published its own.

Temporal - program-feature tables publish as yearly editions, with the 2017 through 2024 runs present in the index; enrollment and beneficiary series run monthly and annually; outcome series such as the continuity-of-medication measure span 2014-2021.

Granularity - one catalog record per dataset, with the underlying data reaching national, state, program, plan and beneficiary-month levels depending on which table a record points at. That spread is the point: this slice serves a 50-state program-design question and a single-state outcome study from the same inventory.

API, files, or your warehouse. Daily, weekly, or hourly.

Your cadence is decoupled from the rhythm of the underlying publishers - take a one-off extract of the MLTSS table for a market-sizing sprint, or keep a landing schema current so newly issued program-feature editions diff cleanly into yesterday's inventory. Deliveries arrive normalized to the field dictionary above with publisher organizations intact, so a figure's provenance chain - which agency, which edition, which month - survives the trip into your storage.

• Managed-care penetration tracking - Share of Medicaid Enrollees in Managed Care plus the enrollment summaries turn 'how much of the program is delegated' into a number you can trend.
• Program-design benchmarking - Managed Care Features By Enrollment Population and by Quality-related Requirements lets you diff what states require of their plans, population by population.
• Long-term services analysis - the MLTSS Enrollees table isolates the managed long-term supports segment that most general enrollment files blur into the total.
• State outcome evaluation - New York's continuity-of-medication, ambulatory follow-up and readmission series support before-and-after studies of managed-care transitions.
• Payer-mix research - enrollment by program, plan and dual-eligible status feeds payer-mix and rate-setting models.
• Longitudinal panel assembly - the 2017-2024 run of Programs By State editions builds a year-over-year design matrix once duplicates are handled.

Market researchers and consultants lead at 3/3 relevance: penetration rates and program-feature diffs are client-deck material; see market researchers. Journalists and academics match them at 3/3 - attribution to CMS or a named state agency comes built into the publisher fields; see journalists and academics. Competitive intel and product teams (2/3) diff annual feature editions to catch states shifting plan models or adding MLTSS; see competitive intel product teams. Investors and quant researchers (2/3) track enrollment editions as payer-mix evidence; see investors and quants. Data scientists and ML engineers (2/3) assemble the CMS and state tables into longitudinal panels; see data scientists. Developers and builders (2/3) normalize the records into internal tooling; see developers and builders.

Within managed health care data, this record owns the precision position. Its closest sibling, the Data.gov managed care full-text search (data-gov-managed-care-full-text-search), runs the same engine with a wider query - recall where this page gives precision, scored row by row in our full-text vs medicaid-only comparison. The Data.Medicaid.gov CMS portal record (data-medicaid-gov-cms-medicaid-data-portal) goes deeper on a single publisher, carrying 549 public datasets including managed-care enrollment from 2016 forward, where this slice trades depth for cross-agency breadth. The KFF state health policy indicators record (kff-state-health-policy-medicaid-chip-indicators) adds roughly 209 pre-computed state indicators, Managed Care Market Tracker included, when the answer should be a ratio rather than a raw table. If your question is 'what exactly does the federal catalog hold on medicaid managed care', this is the record.

Three things worth knowing upfront. First, several CMS titles recur across years - Managed Care Programs By State alone has the 2017 through 2024 editions sitting side by side in the result set - so deduplicate on identifier before building a longitudinal panel, or ask us to hand you the latest edition per title. Second, the query is deliberately narrow: 'medicaid managed care' surfaces fewer, tighter records than the broader managed-care full-text search, so teams wanting adjacent program material should say so and we sweep both. Third, the slice is a catalog layer, not a claims feed - enrollment counts, plan inventories and program features live here; adjudicated claims belong elsewhere. Name your states, programs, years and tables, and the sample lands in exactly the schema shown above.