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Record W2009188743 · doi:10.1089/tmj.2007.0079

Development of a Multidisciplinary Osteoporosis Telehealth Program

2008· article· en· W2009188743 on OpenAlexafffundabout
Leigh Dickson, Cathy Cameron, Gillian Hawker, Azeena Ratansi, Ina Radziunas, V. Bansod, Susan Jaglal

Bibliographic record

VenueTelemedicine Journal and e-Health · 2008
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsOsteoporosis CanadaWomen's College Hospital
FundersUniversity of TorontoToronto Rehabilitation Institute
KeywordsTelehealthMultidisciplinary approachMedicineOsteoporosisTelemedicineFamily medicineOutpatient clinicHealth carePhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

Osteoporosis is a disease characterized by low bone mass and changes to bone structure. The optimal treatment requires both pharmacologic and nonpharmacologic treatment including adequate levels of calcium and vitamin D, exercise, and fall prevention. There is currently a shortage of family physicians and specialists in Ontario, which can result in patients not receiving optimal osteoporosis care. In 2005, a multidisciplinary osteoporosis telehealth program, based on an existing outpatient program, was developed at Women's College Hospital in conjunction with NORTH Network (now part of the Ontario Telemedicine Network). The objectives of this study were to determine the feasibility of delivering a multidisciplinary model of care through telehealth and to improve access to specialist care for osteoporosis investigation and management. Patients were referred by family physicians (n = 20). The average length of the consultations was 2 hours. Ninety-two percent of the participants would use it again and would also recommend it to family and friends, 90% increased their knowledge about osteoporosis, and 83% felt completely comfortable discussing their health problems during their consultation. The results demonstrate that it is feasible to deliver an existing outpatient multidisciplinary osteoporosis program via telehealth. In addition, the program increased access to osteoporosis care, for complex patients in particular, highlighting an unmet need in their communities.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.821
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.053
GPT teacher head0.364
Teacher spread0.311 · 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

Citations14
Published2008
Admission routes3
Has abstractyes

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