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Record W2469748897 · doi:10.5588/ijtld.15.0889

Implementation and 8-year follow-up of an uninterrupted oxygen supply system in a hospital in The Gambia

2016· article· en· W2469748897 on OpenAlexaff
Beverly Bradley, J. D. Light, Augustine Ebonyi, Pamela Collier Njai, Readon C Ideh, Bernard E. Ebruke, Ebrima Nyassi, David Peel, S.R.C. Howie

Bibliographic record

VenueThe International Journal of Tuberculosis and Lung Disease · 2016
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsCentre for Global Health ResearchUniversity of Toronto
FundersMedical Research Council
KeywordsMedicineOperations managementUnit (ring theory)Supplemental oxygenMedical emergencyEngineering

Abstract

fetched live from OpenAlex

SETTING: A 42-bed hospital operated by the Medical Research Council (MRC) Unit in The Gambia. OBJECTIVE: To devise, test and evaluate a cost-efficient uninterrupted oxygen system in the MRC Hospital. DESIGN: Oxygen cylinders were replaced with oxygen concentrators as the primary source of oxygen. An uninterruptable power supply (UPS) ensured continuity of power. Hospital staff were trained on the use of the new system. Eight years post-installation, an analysis of concentrator maintenance needs and costs was conducted and user feedback obtained to assess the success of the system. RESULTS: The new system saved at least 51% of oxygen supply costs compared to cylinders, with savings likely to have been far greater due to cylinder leakages. Users indicated that the system is easier to use and more reliable, although technical support and staff training are still needed. CONCLUSION: Oxygen concentrators offer long-term cost savings and an improved user experience compared to cylinders; however, some technical support and maintenance are needed to upkeep the system. A UPS dedicated to oxygen concentrators is an appropriate solution for settings where power interruptions are frequent but short in duration. This approach can be a model for health systems in settings with similar infrastructure.

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)0.000
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 score0.012
Threshold uncertainty score0.126

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.009
GPT teacher head0.302
Teacher spread0.293 · 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

Citations39
Published2016
Admission routes1
Has abstractyes

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