Assessment of organizational readiness for<i>e</i>-health in a rehabilitation centre
Bibliographic record
Abstract
Purpose: The aims of this study were to assess organizational readiness for e-health among the staff of an out-patient rehabilitation centre and to identify the personal characteristics of potential users that may have influenced readiness. Methods: A cross-sectional study was conducted with 137 clinicians, 28 managers, and 47 nonclinical staff in a rehabilitation centre in Montreal, Quebec, Canada. All participants completed a self-administered questionnaire assessing organizational readiness for e-health. The measure contained three subscales: Individual, Organizational and Technological. Data were also collected on the users’ profile, use of technologies and typical response to new information. Results: Generally, participants considered themselves ready to adopt e-health in their work (X = 73.8%, SD = 8.5) and they also had a favorable view of the technologies in place (X 73.8%, SD = 7.2). However, they perceived the center as being only moderately ready (X 66.6%, SD = 9.8) for e-health changes. Perceived workload and position/duties in the organization were found to have an impact on readiness for e-health. Conclusions: These results underscore the importance of addressing organizational readiness for change as a multidimensional concept. Based on these results, implementation strategies tailored to the specific profile of a rehabilitation organization were identified.Implications for RehabilitationThe use of e-health, or the application of information and communications technologies (ICT) in the health sector, is growing in rehabilitation but its implementation can be challenging.Assessing a rehabilitation facility’s readiness for change reduces the risk of implementation failure of ICT.This study revealed personnel of an out-patient rehabilitation facility perceive themselves as being more ready than their organisation to adopt ICT.The influence of personal factors of potential users must be considered when planning and implementing ICT projects.ICT implementation requires strategies tailored to the organization and to the individuals who support it.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".