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Record W2914655752 · doi:10.1080/22423982.2019.1573163

Evaluation of a pilot paediatric concussion telemedicine programme for northern communities in Manitoba

2019· article· en· W2914655752 on OpenAlexafffundabout
Michael J. Ellis, Susan Boles, Vickie Derksen, Brenda Dawyduk, Adam Amadu, Karen Stelmack, Matthew Kowalchuk, Kelly Russell

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsResearch ManitobaManitoba Harm Reduction NetworkPan Am ClinicUniversity of ManitobaChildren's Hospital Research Institute of Manitoba
FundersUniversity of Manitoba
KeywordsConcussionTelemedicineMedicineReferralPoison controlInjury preventionOccupational safety and healthHuman factors and ergonomicsSuicide preventionTelehealthMedical emergencyHealth carePhysical therapyEmergency medicineFamily medicine

Abstract

fetched live from OpenAlex

Pediatric concussion patients living in northern communities in Canada can face unique challenges accessing primary and specialized healthcare. In this study we report the clinical characteristics, healthcare utilization, outcomes and estimated cost avoidance associated with a pilot pediatric concussion telemedicine program established between a multi-disciplinary pediatric concussion program in Winnipeg, Manitoba and a hospital in Thompson, Manitoba. From October 1st- July 1st, 2018, 20 patients were evaluated; mean age 13.1 years, 15 (75%) males and 14 (70%) self-identified as Indigenous. Injury mechanisms included hockey (50%), falls (35%) and assaults (15%). Median time from referral to initial consultation was 2.0 days. After screening by the neurosurgeon, 90% of patients underwent initial consultation via real-time videoconferencing with 80% managed exclusively through telemedicine. At the end of the study, 90% met the criteria for clinical recovery, one remained in treatment and one was discharged to a headache neurologist. Sixty-six telemedicine encounters were completed including 57 videoconferencing appointments and 9 telephone follow-ups representing an estimated cost avoidance of $40,972.94. This study suggests telemedicine may be a useful approach to assist pediatric concussion programs with delivering timely, safe and cost-effective care to patients living in medically underserviced remote and northern communities in Canada.

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)0.009
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 score0.356
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.176
GPT teacher head0.424
Teacher spread0.249 · 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

Citations53
Published2019
Admission routes3
Has abstractyes

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