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The Within‐Year Concentration of Medical Care: Implications for Family Out‐of‐Pocket Expenditure Burdens

2009· article· en· W2015506003 on OpenAlexaboutno aff
Thomas M. Selden

Bibliographic record

VenueHealth Services Research · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
FundersAgency for Healthcare Research and QualityU.S. Department of Health and Human Services
KeywordsMedical Expenditure Panel SurveyPoverty levelQuarter (Canadian coin)PovertyMedicineDemographyHealth carePopulationFamily incomeAsset (computer security)Medical careEnvironmental healthGerontologyHealth insuranceGeographyEconomicsFamily medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine the within-year concentration of family health care and the resulting exposure of families to short periods of high expenditure burdens. DATA SOURCE: Household data from the pooled 2003 and 2004 Medical Expenditure Panel Survey (MEPS) yielding nationally representative estimates for the nonelderly civilian noninstitutionalized population. STUDY DESIGN: The paper examines the within-year concentration of family medical care use and the frequency with which family out-of-pocket expenditures exceeded 20 percent of family income, computed at the annual, quarterly, and monthly levels. PRINCIPAL FINDINGS: On average among families with medical care, 49 percent of all (charge-weighted) care occurred in a single month, and 63 percent occurred in a single quarter). Nationally, 27 percent of the study population experienced at least 1 month in which out-of-pocket expenditures exceeded 20 percent of income. Monthly 20 percent burden rates were highest among the poor, at 43 percent, and were close to or above 30 percent for all but the highest income group (families above four times the federal poverty line). CONCLUSIONS: Within-year spikes in health care utilization can create financial pressures missed by conventional annual burden analyses. Within-year health-related financial pressures may be especially acute among lower-income families due to low asset holdings.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score0.747

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.136
GPT teacher head0.443
Teacher spread0.306 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations15
Published2009
Admission routes1
Has abstractyes

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