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Record W2559976625 · doi:10.1377/hlthaff.2016.0599

Contrary To Popular Belief, Medicaid Hospital Admissions Are Often Profitable Because Of Additional Medicare Payments

2016· article· en· W2559976625 on OpenAlexaff
Jeffrey Stensland, Zachary R. Gaumer, Mark E. Miller

Bibliographic record

VenueHealth Affairs · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsMiller Group (Canada)
Fundersnot available
KeywordsMedicaidPaymentActuarial scienceBusinessMedicineFamily medicineEconomicsFinanceHealth careEconomic growth

Abstract

fetched live from OpenAlex

It is generally believed that most hospitals lose money on Medicaid admissions. The data suggest otherwise. Medicaid admissions are often profitable for hospitals because of payments from both the Medicaid program and the Medicare program, including payments for uncompensated care and from the Medicare disproportionate-share hospital program. On average, adding a single Medicaid patient day in fiscal year 2017 will increase most hospitals' Medicare payments by more than $300. When added to Medicaid payments, these payments often cause Medicaid patients to be profitable for hospitals. In contrast, adding a single charity care day in the same year will decrease overall Medicare payments by about $20 on average. The Centers for Medicare and Medicaid Services recently announced a proposal to shift some Medicare payments from supporting hospitals' costs for Medicaid patients to directly supporting their costs for uncompensated care. If that proposal is adopted, hospitals' profits on Medicaid patients would decrease, but their losses on care for the uninsured would be reduced.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.980
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.276
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2016
Admission routes1
Has abstractyes

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