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Record W4311572527 · doi:10.1186/s13049-022-01053-x

Aeromedical retrieval services characteristics globally: a scoping review

2022· review· en· W4311572527 on OpenAlexaboutno aff
Kuda Muyambi, F Gardiner, Stephen Sollid, Per Kristian Hyldmo, Engida Yisma, Breeanna Spring, Per P. Bredmose, Martin Jones, Sandra Walsh, Zoe Schofield, Marianne Gillam

Bibliographic record

VenueScandinavian Journal of Trauma Resuscitation and Emergency Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMedical emergencyEmergency medical servicesEmergency medicineMedical physics

Abstract

fetched live from OpenAlex

BACKGROUND: Aeromedical emergency retrieval services play an important role in supporting patients with critical and often life-threatening clinical conditions. Aeromedical retrieval services help to provide fast access to definitive care for critically ill patients in under-served regions. Typically, fixed-wing aeromedical retrieval becomes the most viable transport option compared with rotary-wing aircraft when distances away from centres of definitive care extend beyond 200 kms. To our knowledge, there are no studies that have investigated fixed-wing aeromedical services in the member countries of the organisation for economic cooperation and development (OECD). A description of the global characteristics of aeromedical services will inform international collaboration to optimise clinical outcomes for patients. AIM: In this scoping review, we aimed to describe the features of government- and not-for-profit organisation-owned fixed-wing aeromedical retrieval services in some of the member countries of the OECD. METHODS: We followed scoping review methodology based on the grey literature search strategy identified in earlier studies. This mostly involved internet-based searches of the websites of fixed-wing aeromedical emergency retrieval services affiliated with the OECD member countries. RESULTS: We identified 460 potentially relevant records after searching Google Scholar (n = 24) and Google search engines (n = 436). After removing ineligible and duplicate information, this scoping review identified 86 government-and not-for-profit-operated fixed-wing aeromedical retrieval services as existing in 17 OECD countries. Concentrations of the services were greatest in the USA followed by Australia, Canada, and the UK. The most prevalent business models used across the identified OECD member countries comprised the government, not-for-profit, and hybrid models. Three-quarters of the not-for-profit and two-fifths of the hybrid business models were in the USA compared to other countries studied. The government or state-funded business model was most common in Australia (11/24, 46%), Canada (4/24, 17%), and the UK (4/24, 17%). The frequently used service delivery models adopted for patients of all ages included primary/secondary retrievals, secondary retrievals only, and service specialisation models. Of these service models, primary/secondary retrieval involving the transportation of adults and children from community clinics and primary health care facilities to centres of definitive care comprised the core tasks performed by most of the aeromedical retrieval services studied. The service specialisation model provided an extra layer of specialist health care dedicated to the transportation of neonates and paediatrics. At least eight aeromedical retrieval services catered solely for children from birth to 16 years of age. One aeromedical service, the royal flying doctor service in Australia also provided primary health care and telehealth services in addition to primary retrieval and interhospital transfer of patients. The doctor and registered nurse/paramedic (Franco-German model) and the nurse and/or paramedic (Anglo-American model) configurations were the most common staffing models used across the aeromedical services studied. CONCLUSIONS: The development and composition of fixed-wing aeromedical emergency retrieval services operated by not-for-profit organisations and governments in the OECD countries showed diversity in terms of governance arrangements, services provided, and staffing models used. We do not fully understand the impact of these differences on the quality of service provision, including equitable service access, highlighting a need for further research.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.033
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.005
Bibliometrics0.0330.049
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.103
GPT teacher head0.422
Teacher spread0.318 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

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Citations18
Published2022
Admission routes1
Has abstractyes

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