Delivery of rural and remote health care via a broadband Internet Protocol network – views of potential users
Bibliographic record
Abstract
We asked the views of potential users of a proposed Canadian broadband Internet Protocol (IP) network for health, the Alberta SuperNet. The three user groups were drawn from the public, provider and private sectors. In all, 35 health-sector participants were selected (17 government, nine health-care organizations, five providers/practitioners and four private sector). The questionnaire was Web-based, semistructured and self-administered. It consisted of four major areas: value, readiness, effect on usual care and limitations. A total of 28 (80%) individuals responded to the questionnaire: 21 (81%) were from the public sector (three provincial, nine regional and nine organizational), three (60%) were from the provider sector and four (100%) were from the private sector. Overall, the items related to health services and health human resources were considered to be the most valuable to rural communities. Respondents identified the expansion of telehealth services as the most important, except those from the private sector, who ranked this a close second. The health system's move to the use of electronic health records was ranked second in importance by all respondents. The private-sector respondents viewed all user groups to be generally less ready (mean score 2.5 on a seven-point scale from 1 = not ready to 7 = ready), while the public-sector respondents were the most optimistic (mean score 4.0). Specific socioeconomic impact data were limited. The top-ranked disadvantage of the 10 suggested was that 'Changes in health-service delivery practices and/or processes will be required'.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".