Telehealth adoption in hospitals:an organisational perspective
Bibliographic record
Abstract
PURPOSE: The purpose of this study is to explore the influence of hospitals' organisational characteristics on telehealth adoption by health-care centres involved in the extended telehealth network of Quebec (French acronym RQTE) DESIGN/METHODOLOGY/APPROACH: The article is based on a review of the literature and a questionnaire, which was administered via telephone interviews to the 32 hospitals involved in the Extended Telehealth Network of Quebec. Contingency analyses were performed to determine which organisational factors have influenced telehealth adoption. Subsequently, a multiple case study was conducted among nine hospitals representative of different categories of telehealth adopters. In-depth interviews with various actors involved in telehealth activities have permitted a deepening of one's understanding of the impact of clinical and administrative contexts on telehealth adoption. FINDINGS: The results from both the questionnaire and interviews support the observation made by Whitten and Adams in 2003 that telehealth programs are not isolated, but located within larger health organisations. Moreover, health-care organisations are also positioned in a larger geographical, economical and socio-political environment. Therefore, it is important to investigate the context in which telehealth projects are taking place prior to experimentation. ORIGINALITY/VALUE: This study has highlighted the relevance of considering the characteristics and the dynamics of health-care organisations at each stage of telehealth implementation in order to take their specific needs into account.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".