Home Care Safety Perspectives from Clients, Family Members, Caregivers and Paid Providers
Bibliographic record
Abstract
Designing Safer Systems T he demand for home care services is growing in Canada (Canada Institute for Health Information 2003).There has been a 51% increase in the number of home care clients since 1997, with over 900,000 receiving services in 2007 (Canadian Home Care Association 2008).Yet, overwhelmingly, research on patient safety has focused on institutional settings.Moreover, there has been an augmentation in the medicalization of private homes, resulting not only from the escalating threshold for admission to hospital but also from the increasing acuity of patients at the time of their discharge.This shift in care setting has been facilitated by the explosion of "hospital at home" services and the ever-growing availability of mobile technology (e.g., hemo-and peritoneal dialysis, long-term intravenous catheters and oxygen/inhalation therapy) (Williams 2002).The physical environment, socioeconomic status, family dynamics and cognitive and physical abilities of the client and caregivers are essential factors to be considered when delivering services.Family members or friends who are unpaid caregivers are often untrained, elderly and contending with their own health challenges.They frequently lack sleep as they provide around-Abstract There is a growing demand for home care services in Canada.Yet, overwhelmingly, research on patient safety has focused on institutional settings.The Canadian Patient Safety Institute convened a Core Safety in Home Care Team of researchers and decision-makers to identify priority research areas and to advance patient safety research in home care.As part of this initiative to investigate and extend our understanding of home care safety, key informant interviews were carried out with a wide range of respondents including researchers, decision-makers, service providers and regulators.In-depth audiotaped interviews were conducted in two Canadian provinces.Interpretive descriptive analyses revealed three main themes: the meaning of home care, safety concerns and the place of technology in the future of home care.Given the multidimensionality and complexity of home care as well as the challenges and strains involved, the risk to all the players is becoming increasingly evident.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| 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".