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Record W4395079182 · doi:10.1016/j.bjid.2024.103744

Costs of hospital admissions due to COVID-19 in the federal capital of Brazil: a study based on hospital admission authorizations

2024· article· en· W4395079182 on OpenAlexfundno aff
Ana Carolina Esteves da Silva Pereira, Luciana Guerra Gallo, Ana Flávia de Morais Oliveira, Maria Regina Fernandes de Oliveira, Henry Maia Peixoto

Bibliographic record

VenueThe Brazilian Journal of Infectious Diseases · 2024
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsnot available
FundersMinistério da EducaçãoMinisterio de Economía y CompetitividadUniversity of New BrunswickUniversidade de Brasília
KeywordsMedicineAuthorizationCoronavirus disease 2019 (COVID-19)Emergency medicineActivity-based costingCohortInternal medicineBusinessDisease

Abstract

fetched live from OpenAlex

This is a cost analysis study based on hospital admissions, conducted from the perspective of the Brazilian Unified Health System (SUS), carried out in a cohort of patients hospitalized at the University Hospital of Brasília (UHB) due to Severe Acute Respiratory Infections (SARI) caused by COVID-19, from April 1, 2020, to March 31, 2022. An approach based on macro-costing was used, considering the costs per patient identified in the Hospital Admission Authorizations (HAA). Were identified 1,015 HAA from 622 patients. The total cost of hospitalizations was R$ 2,875,867.18 for 2020 and 2021. Of this total, 86.41 % referred to hospital services and 13.59 % to professional services. The highest median cost per patient identified was for May 2020 (R$ 19,677.81 IQR [3,334.81-33,041.43]), while the lowest was in January 2021 (R$ 1,698.50 IQR [1,602.70-2,224.11]). The high cost of treating patients with COVID-19 resulted in a high economic burden of SARI due to COVID-19 for UHB and, consequently, for SUS.

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)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.374
Teacher spread0.354 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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