Bibliographic record
Abstract
The theme of the congress was Quality and Innovation in the 21st Century: Challenges and Opportunities.The special issue contains papers on many interesting topics.Quality and innovation is the central theme.It has a mixture of theoretical, practical and those that are rooted in conceptual framework thinking for improving health-care organizations.Leadership is at the core of all issues discussed.The papers represent very timely topics that are currently hotly debated and discussed throughout North America and in other parts of the world, that is, the quality and patient satisfaction must improve and costs must go down.The first paper discusses how leveraging supply chain infrastructure can advance patient safety in community-based health-care settings.The authors argue that while the majority of patient safety studies in Canada and abroad have focused on safety in hospital settings, deaths and harm experienced by patients in the community settings (home care, long-term care, complex care and rehabilitation) are less well understood.The authors suggest that improving system infrastructure would reduce the occurrence of adverse events.According to them, the visibility across the continuum of care holds the potential to transform health care in Canada rather than a fragmented system where information is inadequately captured and transferred from provider to provider, to a system that would provide complete, accurate and up-to-date information of patient care, procedures, medications and outcomes to inform the best and safest care possible.The second paper presents a comprehensive approach for studying organizational culture using "soft measures" to facilitate sustainable quality development.The author's work consists of a number of different methods to collect soft data that influences the culture and the leadership within three organizations that were shown statistically significant with positive changes in organizational work culture only after a short period of one year.The next paper is about improving patient flow in an emergency department of hospital using lean methodologies.The emergency department overcrowding (EDOC) and increased length of stay (LOS) have been key global issues for more than 20 years with many serious repercussions.Guided by the Lean management concepts, the author proposes solutions that fall under three themes: ensuring effective triaging of all patients, reducing the total number of patients referred to observation room and reducing maximum LOS and wait times in observation room.The solutions address the vital few causes of the EDOC and prolonged EDLOS that are critical to solving ED problems.The fourth paper is about developing a model for measuring effectiveness of quality management practices in health-care organizations.Health care is the example where the needs of potential clients often exceeds the capabilities of the service delivery system.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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; both teacher heads agree on what is shown here.
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".