Telemedicine follow‐up facilitates more comprehensive diabetes foot ulcer care: A qualitative study in home‐based and specialist health care
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To investigate the application of a telemedicine intervention in diabetes foot ulcer care, and its implications for the healthcare professionals in the clinical field. BACKGROUND: Contextual factors are found to be important when applying technology in health care and applying telemedicine in home-based care has been identified as particularly complex. DESIGN AND METHODS: We conducted field observations and individual interviews among healthcare professionals in home-based care and specialist health care in a diabetes foot care telemedicine RCT (Clin.Trial.gov: NCT01710774) during 2016. This study was guided by Interpretive Description, an inductive qualitative methodology. RESULTS: Overall, we identified unequal possibilities for applying telemedicine in diabetes foot ulcer care within the hospital and home care contexts. Different circumstances and possibilities in home-based care made the application of telemedicine as intended more difficult. The healthcare professionals in both care contexts perceived the application of telemedicine to facilitate a more comprehensive approach towards the patients, but with different possibilities to enact it. CONCLUSIONS: Application of telemedicine in home-based care was more challenging than in the outpatient clinic setting. Introducing more updated equipment and minor structural adjustments in consultation time and resources could make the use of telemedicine in home-based care more robust. RELEVANCE TO CLINICAL PRACTICE: Application of telemedicine in diabetes foot ulcer follow-up may enhance the nursing staff's ability to conduct comprehensive assessment and care of the foot ulcer as well as the patient's total situation. Access to adequate equipment and time, particularly in home-based care, is necessary to capitalise on this new technology.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".