A mHealth Application for Chronic Wound Care: Findings of a User Trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper reports on the findings of a user trial of a mHealth application for pressure ulcer (bedsore) documentation. Pressure ulcers are a leading iatrogenic cause of death in developed countries and significantly impact quality of life for those affected. Pressure ulcers will be an increasing public health concern as the population ages. Electronic information systems are being explored to improve consistency and accuracy of documentation, improve patient and caregiver experience and ultimately improve patient outcomes. A software application was developed for Android Smartphones and tablets and was trialed in a personal care home in Western Canada. The software application provides an electronic medical record for chronic wounds, replacing nurses' paper-based charting and is positioned for integration with facility's larger eHealth framework. The mHealth application offers three intended benefits over paper-based charting of chronic wounds, including: (1) the capacity for remote consultation (telehealth between facilities, practitioners, and/or remote communities), (2) data organization and analysis, including built-in alerts, automatically-generated text-based and graph-based wound histories including wound images, and (3) tutorial support for non-specialized caregivers. The user trial yielded insights regarding the software application's design and functionality in the clinical setting, and highlighted the key role of wound photographs in enhancing patient and caregiver experiences, enhancing communication between multiple healthcare professionals, and leveraging the software's telehealth capacities.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it