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Age trends in direct medical costs of pediatric asthma: a population-based study

2021· preprint· en· W3131103045 on OpenAlexaffabout
Wenjia Chen, Hamid Tavakoli, J Mark FitzGerald, Padmaja Subbarao, Turvey Stuart, Mohsen Sadatsafavi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsAsthmaMedicineSocioeconomic statusPediatricsPharmacyDemographyHealth carePopulationIndirect costsFamily medicineEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Background: Quantifying age trends in healthcare costs of pediatric asthma leads to better understanding of the natural history of the disease and informed decision-making on the allocation of healthcare resources. Methods: We identified children with incident asthma from the health administrative data of British Columbia, Canada (Jan 1998 to Dec 2015), and followed them from their first diagnosis of asthma or wheezing until age 18. We estimated direct medical costs (in 2016 Canadian dollars [$]), including inpatient and outpatient encounters and pharmacy costs, attributed to asthma (primary outcome) and other respiratory diseases (secondary outcome). We assessed the impact of sex and socioeconomic status on age trends, adjusting for calendar effect. Results: The final analysis included 44,552 children with asthma (62% boys). From age 0 to 18, costs of asthma/wheezing and other respiratory conditions decreased from $1,036 to $29/child-year, and from $1,145 to $31/child-year, respectively. Children under 3 years of age incurred 4–fold higher costs for asthma/wheezing and other respiratory conditions. In particular, costs of asthma hospitalizations were 10 times higher in this age group compared to older children. Age trends were generally similar between sex groups and across socioeconomic status. However, medication costs for asthma/wheezing decreased in boys, whereas those in girls declined during childhood but increased during adolescence. Conclusions: The highest costs of pediatric asthma are concentrated in children younger than 3. Age trends were generally consistent between sex and across socioeconomic status.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, 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 score0.110
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
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 science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.067
GPT teacher head0.481
Teacher spread0.414 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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