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Record W2121031461 · doi:10.1136/ip.2010.029215.398

Cost effectiveness analysis of playground surfacing at preventing arm fractures in a randomised study

2010· article· en· W2121031461 on OpenAlexaffabout
Linda Rothman, Andrew J. Macpherson, Angela Howard

Bibliographic record

VenueInjury Prevention · 2010
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsActivity-based costingTotal costScheduleCost analysisMedicineCost effectivenessEngineeringForensic engineeringEnvironmental scienceOperations managementBusinessManagement

Abstract

fetched live from OpenAlex

Background Upper extremity fractures resulting from playground falls are commonly seen in emergency departments. A 2-year randomised surfacing trial conducted in 19 schools in Toronto, Canada, found that the risk of fracture from playground equipment falls was 4.9 times lower in schools with granite sand playground surfacing (0.019/1000 student months) compared to engineered wood fibre (EWF; 0.094/1000 student months). A subsequent analysis was conducted to determine the cost effectiveness of granite sand in reducing arm fractures in school playgrounds. Methods The Ontario Case Costing Initiative provided hospital costs. Physician service costs were obtained from the Ontario Health Insurance Schedule of Benefits. The Toronto District School Board provided costs of installation and maintenance for each surface type. Total cost was calculated per 1000 student months, by combining treatment costs with surfacing costs. Cost saved per fracture prevented was calculated. Results The total cost of surfacing and injury was $890.61 for sand and $949.00 per 1000 student months for EWF. Although the cost of surfacing was greater for sand ($887.14 vs $841.83 for EWF), the cost per injury was substantially lower for those injured on sand ($3.47 vs $107.17 for EWF). Sand surfacing resulted in 0.08/1000 fractures prevented. The total cost saving per fracture prevented with sand was $779.00. Discussion Both healthcare and schools are publicly funded in Toronto through the provincial government. The installation of sand surfacing in school playgrounds would generate a cost savings to the public, while substantially reducing the number of arm fractures.

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)0.006
metaresearch head score (Gemma)0.001
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 score0.086
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.400
Teacher spread0.369 · 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

Citations1
Published2010
Admission routes2
Has abstractyes

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