Safety in home care: A research protocol for studying medication management
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
BACKGROUND: Patient safety is an ongoing global priority, with medication safety considered a prevalent, high-risk area of concern. Yet, we have little understanding of the supports and barriers to safe medication management in the Canadian home care environment. There is a clear need to engage the providers and recipients of care in studying and improving medication safety with collaborative approaches to exploring the nature and safety of medication management in home care. METHODS: A socio-ecological perspective on health and health systems drives our iterative qualitative study on medication safety with elderly home care clients, family members and other informal caregivers, and home care providers. As we purposively sample across four Canadian provinces: Alberta (AB), Ontario (ON), Quebec (QC) and Nova Scotia (NS), we will collect textual and visual data through home-based interviews, participant-led photo walkabouts of the home, and photo elicitation sessions at clients' kitchen tables. Using successive rounds of interpretive description and human factors engineering analyses, we will generate robust descriptions of managing medication at home within each provincial sample and across the four-province group. We will validate our initial interpretations through photo elicitation focus groups with home care providers in each province to develop a refined description of the phenomenon that can inform future decision-making, quality improvement efforts, and research. DISCUSSION: The application of interpretive and human factors lenses to the visual and textual data is expected to yield findings that advance our understanding of the issues, challenges, and risk-mitigating strategies related to medication safety in home care. The images are powerful knowledge translation tools for sharing what we learn with participants, decision makers, other healthcare audiences, and the public. In addition, participants engage in knowledge exchange throughout the study with the use of participatory data collection methods.
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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 | 0.039 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it