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Record W2513330805 · doi:10.1377/hlthaff.2015.1344

Uncompensated Care Decreased At Hospitals In Medicaid Expansion States But Not At Hospitals In Nonexpansion States

2016· article· en· W2513330805 on OpenAlex
David Dranove, Craig Garthwaite, Christopher Ody

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Affairs · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsKellogg's (Canada)
Fundersnot available
KeywordsMedicaidUncompensated CarePatient Protection and Affordable Care ActHealth insuranceMedicineHealth careBusinessDemographyDemographic economicsEconomicsEconomic growth

Abstract

fetched live from OpenAlex

One pillar of the Affordable Care Act (ACA) was its expected impact on the growing burden of uncompensated care costs for the uninsured at hospitals. However, little is known about how this burden changed as a result of the ACA's enactment. We examine how the Affordable Care Act (ACA)'s coverage expansions affected uncompensated care costs at a large, diverse sample of hospitals. We estimate that in states that expanded Medicaid under the ACA, uncompensated care costs decreased from 4.1 percentage points to 3.1 percentage points of operating costs. The reductions in Medicaid expansion states were larger at hospitals that had higher pre-ACA uncompensated care burdens and in markets where we predicted larger gains in coverage through expanded eligibility for Medicaid. Our estimates suggest that uncompensated care costs would have decreased from 5.7 percentage points to 4.0 percentage points of operating costs in nonexpansion states if they had expanded Medicaid. Thus, while the ACA decreased the variation in uncompensated care costs across hospitals within Medicaid expansion states, the difference between expansion and nonexpansion states increased substantially. Policy makers and researchers should consider how the shifting uncompensated care burden affects other hospital decisions as well as the distribution of supplemental public funding to hospitals.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.024
GPT teacher head0.269
Teacher spread0.245 · 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