The effect of continuous pressure monitoring on strategic shifting of medical inpatients at risk for PUs
Bibliographic record
Abstract
OBJECTIVE: To assess the impact of continuous pressure imaging technology on strategic turning of patients by health professionals. METHOD: This pilot study of a newly-developed continuous pressure imaging technology (XSENSOR ForeSite PatientTurn System) involved two phases of videotaped observation of medical inpatients, with each patient serving as his/her own control: a control phase in which continuous pressure imaging was not available to health-care providers and an intervention phase where it was. The primary outcome was to determine whether access to the technology influenced the rate of patient turns/shifts by nursing staff. Secondary outcomes included a comparison of the rates of other care provider shifts, patient self-shifts, and family assisted shifts. Qualitative data regarding nurse and patient/family perspectives were also obtained. RESULTS: Complete control/intervention data were available for nine patients.The mean rate of two-person assisted turns was 0.274 +/- 0.087 turns per hour in the control phase versus 0.413 +/- 0.091 turns per hour in the intervention phase (p = 0.08). For the combined endpoint of two-person assisted turns or patient transfers off the bed into a wheelchair/chair, there was a statistically significant difference in the mean number of turns per hour: mean of 0.491 +/- 0.271 turns per hour for the intervention group versus 0.327 +/- 0.235 turns per hour for the control group (p = 0.04). Provider interviews confirmed that nurses used information from the technology to inform their patient shifting strategies and behaviours. CONCLUSION: This pilot study provides some initial data supporting the hypothesis that continuous pressure imaging technology could positively impact the frequency of patient turns by care providers, as well as provide impetus to inspect specific skin locations,thereby providing a potential targeted risk mitigation strategy for the development of pressure ulcers. DECLARATION OF INTEREST: Funding for the study was obtained from PreCarn Inc., an independent, nonprofit company supporting the pre-commercial development of new technologies, and from the Alberta Enterprise and Advanced Education (formally Alberta Advanced Education and Technology). The industry partner, XSENSOR, was involved in setup and maintenance of the technology, but was not involved in the evaluative research protocol. Specifically, XSENSOR personnel were not involved in the collection, coding, or analysis of outcome data, nor in the compilation and writing of this paper. None of the listed authors have any conflicts of interest, financial or otherwise, relating to the technology tested.
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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 | 0.003 | 0.001 |
| 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) | 0.000 | 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".