Study quality and evidence of benefit in recent assessments of telemedicine
Bibliographic record
Abstract
We carried out a systematic review of recent telemedicine assessments to identify scientifically credible studies that included comparison with a non-telemedicine alternative and that reported administrative changes, patient outcomes or the results of an economic assessment. From 605 publications identified in the literature search, 44 papers met the selection criteria and were included in the review. Four other publications were identified through references cited in one of the retrieved papers and from a separate project to give a total of 48 papers for consideration, which referred to 42 telemedicine programmes and 46 studies. Some kind of economic analysis was included in 25 (52%) of the papers. In considering the studies, we used a quality appraisal approach that took account of both study design and study performance. For those studies that included an economic analysis, a further quality-scoring approach was applied to indicate how well the economic aspects had been addressed. Twenty-four of the studies were judged to be of high or good quality and 11 of fair to good quality but with some limitations. Seven studies were regarded as having limited validity and a further four as being unacceptable for decision makers. New evidence on the efficacy and effectiveness of telemedicine was given by studies on geriatric care, intensive care and some of those on home care. For a number of other applications, reports of clinical or economic benefits essentially confirmed previous findings. Although further useful clinical and economic outcomes data have been obtained for some telemedicine applications, good-quality studies are still scarce.
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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 | 0.204 | 0.536 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.015 |
| Bibliometrics | 0.028 | 0.021 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".