In home telerehabilitation for older adults after discharge from an acute hospital or rehabilitation unit: A proof-of-concept study and costs estimation
Bibliographic record
Abstract
PURPOSE: The purpose of this study is to investigate rehabilitation through teletreatment as an alternative to a physical homecare visit to deliver services to individuals at home following discharge from an acute hospital or rehabilitation unit. METHOD: Four community-living elderly people were recruited for telerehabilitation services prior being discharged from an acute-care hospital and a geriatric rehabilitation unit. Once the patient returned home, an appointment was made for the assessing therapist to take the clinical measurements (T1) in a face-to-face session. Four clinical variables were used (functional autonomy, balance, locomotor performance in walking and lower-body strength). Telerehabilitation sessions with the participants were conducted with trained personnel in the individual's home. The system used to support telerehabilitation services for this proof of concept was built around network-attached remotely-controlled pan/tilt/zoom cameras with MJPEG compression, media displays and hands-free phones. Before the patient was discharged from the physiotherapy program, the same assessing therapist visited the subject again to take the T2 measurements in a face-to-face session. The satisfaction of the health-care professional was determined for each session with the homemade questionnaire. Costs related to telerehabilitation were compared to theoretically home visits. RESULTS: All four subjects improved on the four clinical variables. Mean costs for the telerehabilitation program, comprising 12 sessions over 4 weeks was $487. CONCLUSION: Telerehabilitation seems to be a practical alternative for dispensing rehabilitation services after patients are discharged from an acute hospital or rehabilitation unit.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".