Understanding organizational context and heart failure management in long term care homes in Ontario, Canada
Bibliographic record
Abstract
Objective: To assess current heart failure (HF) care processes and organizational context in long-term care (LTC) homes as a prelude to adapting the Canadian Cardiovascular Society (CCS) HF guidelines for use in these settings. Methods: This research reports on the results of thirteen focus groups (N = 83 participants; average of 60 minutes duration) conducted in three Ontario LTC homes to better understand how HF was managed and how organizational context impacted care. Participants included physicians, nurse practitioners, registered nurses, registered practical nurses, and personal support workers. Results: Focus group findings revealed that the complexity of the LTC environment presents challenges for managing HF. Most residents have multiple advanced chronic conditions that must be managed simultaneously. Culturally, LTC is first and foremost a resident’s home where residents may choose not to comply with care recommendations. Staff routines, scopes of practice, professional hierarchies, available resources and government regulations limit flexibility in providing care. Staff lacked knowledge, skills and resources for managing HF. Nevertheless, all staff viewed LTC as the preferred place for managing HF, avoiding residents’ hospitalizations wherever possible. These data suggest that strategies for improving LTC staff communication and education, strengthening existing relationships between staff, family, residents and community resources, and acquiring additional resources in LTC homes have the potential to improve HF management in this setting. Conclusion: LTC is a complex and dynamic environment that presents many challenges for providing care for residents. This research provides the foundation for subsequent work to develop and test implementation strategies to manage HF in LTC, which are consistent with the CCS HF guidelines and are feasible within LTC staff’s work routines, capacities and resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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".