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Record W2012192178 · doi:10.1377/hlthaff.2012.1026

Wisconsin Experience Indicates That Expanding Public Insurance To Low-Income Childless Adults Has Health Care Impacts

2013· article· en· W2012192178 on OpenAlexaff
Thomas DeLeire, Laura Dague, Lindsey Leininger, Kristen Voskuil, Donna Friedsam

Bibliographic record

VenueHealth Affairs · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsPublic Works and Government Services Canada
Fundersnot available
KeywordsMedicaidHealth insuranceMedicineEmergency departmentPublic health insurancePopulationHealth careLow incomePrivate insurancePublic healthAmbulatory careBusinessEnvironmental healthNursingDemographic economicsEconomic growthEconomics

Abstract

fetched live from OpenAlex

As states consider expanding Medicaid to low-income childless adults under the Affordable Care Act, their decisions will depend, in part, on how such coverage may affect the use of medical care. In 2009 Wisconsin created a new public insurance program for low-income uninsured childless adults. We analyzed administrative claims data spanning 2008 and 2009 using a case-crossover study design on a population of 9,619 Wisconsin residents with very low incomes who were automatically enrolled in this program in January 2009. In the twelve months following enrollment in public insurance, outpatient visits for the study population increased 29 percent, and emergency department visits increased 46 percent. Inpatient hospitalizations declined 59 percent, and preventable hospitalizations fell 48 percent. These results demonstrate that public insurance coverage expansions to childless adults have the potential to improve health and reduce costs by increasing access to outpatient care and reducing hospitalizations.

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)0.000
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 score0.346
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
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.061
GPT teacher head0.296
Teacher spread0.236 · 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 designObservational
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

Citations82
Published2013
Admission routes1
Has abstractyes

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