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Feasibility of epilepsy follow‐up care through telemedicine: A pilot study on the patient's perspective

2007· article· en· W2044565953 on OpenAlexaffabout
S. Nizam Ahmed, Carly Mann, D. Barry Sinclair, Angela Heino, Blayne Iskiw, D. Gavin Quigley, Arto Öhinmaa

Bibliographic record

VenueEpilepsia · 2007
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsCapital District Health AuthorityUniversity of AlbertaUniversity of Alberta HospitalAlberta Hospital Edmonton
Fundersnot available
KeywordsTelemedicineMedicinePatient satisfactionEpilepsyCost analysisPopulationProductivityMedical emergencyEmergency medicineHealth careSurgeryPsychiatry

Abstract

fetched live from OpenAlex

PURPOSE: Cost analysis and patient satisfaction with telemedicine in epilepsy care. METHODS: This controlled study included out-of-town epilepsy patients coming to follow-up at the University of Alberta hospital epilepsy clinic. After an informed consent, patients were randomized to either conventional (n = 18) or telemedicine (n = 23) clinics. Patients or caregivers filled patient satisfaction and travel cost questionnaires in both alternatives. Cost per visit analysis included costs of traveling, lodging, and lost productivity. RESULTS: Average age of the population was 41 years (range 19-73; 45% women). Eighty-three percent of patients preferred their next visit through telemedicine. About 90% of patients indicated a need for companion travel (mainly by car) to conventional clinic. For the conventional group patients the value of lost productivity was CAD $201, hotel cost CAD $8.50, and the value of car mileage CAD $256.50, totaling about CAD $466.00. Patient costs for telemedicine were CAD $35.85. Telemedicine production costs are similar to the patients' savings in traveling and lost productivity. About 90% of patients in both groups were satisfied with the quality of the service. CONCLUSION: Telemedicine can play a role in follow-up care of epilepsy patients, reduce patient costs, and improve patient satisfaction. This is the first full-time epilepsy telemedicine clinic in Western 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)0.001
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 score0.170
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.082
GPT teacher head0.392
Teacher spread0.310 · 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

Citations99
Published2007
Admission routes2
Has abstractyes

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