Safety in home care: a broadened perspective of patient safety
Bibliographic record
Abstract
BACKGROUND: Home care is the most rapidly growing segment of the Canadian healthcare system. Overwhelmingly, research on patient safety has been conducted within institutional settings, resulting in a significant knowledge gap about safety in homecare. Given the dramatic increase in the amount, acuity and complexity of health care being provided in the home and community, it is essential to develop our understanding of safety in this sector. OBJECTIVE: The objective of this paper is to describe the landscape of safety in home care in Canada. METHOD: This pan-Canadian initiative included three phases: a literature review, 20 key informant interviews and an invitational roundtable. Data were synthesized using a content analysis approach. RESULTS: Patient safety is a failure of systems rather than of humans; there are many change processes required to create safe environments; organizational culture and workplace factors are critical. Patients have a key role to play in their care and thus must be part of the patient safety discourse. Themes central to safety in home care are: the inextricably linked relationships and communication among clients/families and caregivers/providers; unregulated and uncontrolled settings, autonomy and isolation; the multidimensionality of safety (physical, emotional, social, functional); a diminishing focus on prevention, health promotion and chronic care; challenges of human resources and maintenance of competence. CONCLUSION: Addressing safety in home care and mitigating the risks presents unique challenges and requires a major rethink of underlying institutionally oriented assumptions and guiding frameworks.
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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 | 0.015 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.016 | 0.050 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".