Patient Safety Law: From Silos to Systems
Bibliographic record
Abstract
Patient safety has become a significant and pressing policy issue. Around the world, governments, the health care sector and the public are increasingly cognizant of the need to improve the safety of care delivered by their health systems. Pressure for change has been created by highly publicized incidents in a number of countries involving unsafe acts that were significant both in scale and consequence and a number of empirical studies that revealed the high rates of unsafe acts and their consequences. The costs of unsafe health care – both personal and fiscal – to individuals, their families and their communities and to the state are massive. In this research project we explored one particular avenue for change – that is, the use of legal instruments by governments to improve patient safety. We did this through a comparative review of the use of legal instruments or frameworks in other countries (specifically Australia, Denmark, New Zealand, the United Kingdom, and the United States) as well as two non-health care related sectors in Canada (transportation and occupational health and safety). We began this research by reviewing the legal instruments and undertaking extensive literature reviews. Further information was gathered through in-person interviews with policy-makers and academics in the countries studied, and from policy-makers and academics expert in the health, occupational health and safety, and transportation sectors in Canada. Once descriptions of the various countries and sectors were drafted, we held small-group meetings with local experts on particular aspects of patient safety. We then hosted a national consultation meeting. We subsequently drafted this final report and the appendices, which fully describe the results of the background research. Finally, we prepared a summary version of the report as well as posters and papers to be published and delivered at conferences and meetings with relevant groups.
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 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 | 0.040 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.011 | 0.069 |
| Scholarly communication | 0.032 | 0.054 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".