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Record W2156739230 · doi:10.1258/135763303771005207

The socio-economic impact of telehealth: A systematic review

2003· review· en· W2156739230 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Telemedicine and Telecare · 2003
Typereview
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsInstitute of Health EconomicsMcGill UniversityUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsTelehealthGeneralizability theoryTelemedicineMedicineHealth careMental healthRural areaRehabilitationNursingEconomic impact analysisFamily medicineEconomic growthPsychologyPsychiatryPhysical therapy

Abstract

fetched live from OpenAlex

We reviewed the socio-economic impact of telehealth, focusing on nine main areas: paediatrics, geriatrics, First Nations (i.e. indigenous peoples), home care, mental health, radiology, renal dialysis, rural/remote health services and rehabilitation. A systematic search led to the identification of 4646 citations or abstracts; from these, 306 sources were analysed. A central finding was that telehealth studies to date have not used socio-economic indicators consistently. However, specific telehealth applications have been shown to offer significant socio-economic benefit, to patients and families, health-care providers and the health-care system. The main benefits identified were: increased access to health services, cost-effectiveness, enhanced educational opportunities, improved health outcomes, better quality of care, better quality of life and enhanced social support. Although the review found a number of areas of socio-economic benefit, there is the continuing problem of limited generalizability.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.418
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.433
Teacher spread0.385 · 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