Conditions for success in introducing telemedicine in diabetes foot care: a qualitative inquiry
Bibliographic record
Abstract
BACKGROUND: The uptake of various telehealth technologies to deliver health care services at a distance is expanding; however more knowledge is needed to help understand vital components for success in using telehealth in different work settings. This study was part of a larger trial designed to investigate the effect of an interactive telemedicine platform. The platform consisted of a web based ulcer record linked to a mobile phone to provide care for people with diabetic foot ulcers in outpatient clinics in specialist hospital care in collaboration with primary health care. The aim of this qualitative study was to identify perceptions of health care professionals in different working settings with respect to facilitators to engagement and participation in the application of telemedicine. METHODS: Ten focus groups were conducted with health care professionals and leaders in Western Norway between January 2014 and June 2015 using Interpretive Description, an applied qualitative research strategy. RESULTS: Four key conditions for success in using telemedicine as a new technology in diabetes foot care were identified: technology and training that were user-friendly; having a telemedicine champion in the work setting; the support of committed and responsible leaders; and effective communication channels at the organizational level. CONCLUSIONS: Successful larger scale implementation of telemedicine must involve consideration of complex contextual and organizational factors associated with different work settings. This form of new care technology in diabetes foot care often involves health care professionals working across different settings with different management systems and organizational cultures. Therefore, attention to the distinct needs of each staff group seems an essential condition for effective implementation.
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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 | 0.023 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".