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Record W3039485390 · doi:10.1590/0102-311x00120019

Gastos com a assistência ao parto: comparação entre as coortes de nascimento de Pelotas dos anos de 2004 e 2015, Rio Grande do Sul, Brasil

2020· article· pt· W3039485390 on OpenAlexaff
Marília Cruz Guttier, César Augusto Oviedo Tejada, Fernando C. Wehrmeister, Mariângela Freitas da Silveira, Marlos Rodrigues Domingues, Aluísio J. D. Barros, Iná S. Santos, Alícia Matijasevich, Diego G. Bassani, Andréa Dâmaso Bertoldi

Bibliographic record

VenueCadernos de Saúde Pública · 2020
Typearticle
Languagept
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsHumanitiesGynecologyMedicinePhysicsArt

Abstract

fetched live from OpenAlex

Although most childbirth care in Brazil is financed by the Brazilian Unified National Health System (SUS), there are out-of-pocket expenditures (private personal costs) involved in births. This study aims to compare maternal out-of-pocket expenditures in births of children from the Pelotas Birth Cohorts of 2004 and 2015. The study drew on information collected right after birth and at three months of age. The target variables include sociodemographic and economic data, private health plan coverage, and expenditures related to the birth. Values from 2004 were adjusted to 2015 by the general price index. There was an increase in private health plan coverage from 33.4% (95%CI: 31.9-34.9) to 45.1% (95%IC: 43.6-46.7) in the target period, directly associated with the families' socioeconomic status (p < 0.001). There was an increase in mean expenditures on hospitalization for the birth, from BRL 60.38 (SD = 288.66) to BRL 171.15 (SD = 957.07), and in additional medical expenditures, from BRL 191.60 (SD = 612.86) to BRL 1,424.80 (SD = 4,459.16) among mothers admitted to hospital under their private health plans (and there was no significant difference in these expenditures for mothers that opted for direct payment). There was an important increase in expenditures for childbirth care, especially among mothers admitted to hospital under private health plans.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.023
GPT teacher head0.306
Teacher spread0.282 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2020
Admission routes1
Has abstractyes

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