Pressure ulcer multidisciplinary teams via telemedicine: a pragmatic cluster randomized stepped wedge trial in long term care
Bibliographic record
Abstract
BACKGROUND: The study was conducted to determine the clinical and cost effectiveness of enhanced multi-disciplinary teams (EMDTs) vs. 'usual care' for the treatment of pressure ulcers in long term care (LTC) facilities in Ontario, Canada METHODS: We conducted a multi-method study: a pragmatic cluster randomized stepped-wedge trial, ethnographic observation and in-depth interviews, and an economic evaluation. Long term care facilities (clusters) were randomly allocated to start dates of the intervention. An advance practice nurse (APN) with expertise in skin and wound care visited intervention facilities to educate staff on pressure ulcer prevention and treatment, supported by an off-site hospital based expert multi-disciplinary wound care team via email, telephone, or video link as needed. The primary outcome was rate of reduction in pressure ulcer surface area (cm2/day) measured on before and after standard photographs by an assessor blinded to facility allocation. Secondary outcomes were time to healing, probability of healing, pressure ulcer incidence, pressure ulcer prevalence, wound pain, hospitalization, emergency department visits, utility, and cost. RESULTS: 12 of 15 eligible LTC facilities were randomly selected to participate and randomized to start date of the intervention following the stepped wedge design. 137 residents with a total of 259 pressure ulcers (stage 2 or greater) were recruited over the 17 month study period. No statistically significant differences were found between control and intervention periods on any of the primary or secondary outcomes. The economic evaluation demonstrated a mean reduction in direct care costs of $650 per resident compared to 'usual care'. The qualitative study suggested that onsite support by APN wound specialists was welcomed, and is responsible for reduced costs through discontinuation of expensive non evidence based treatments. Insufficient allocation of nursing home staff time to wound care may explain the lack of impact on healing. CONCLUSION: Enhanced multi-disciplinary wound care teams were cost effective, with most benefit through cost reduction initiated by APNs, but did not improve the treatment of pressure ulcers in nursing homes. Policy makers should consider the potential yield of strengthening evidence based primary care within LTC facilities, through outreach by APNs. TRIAL REGISTRATION: ClinicalTrials.gov identifier NCT01232764.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".