Standardization in patient safety: the WHO High 5s project
Bibliographic record
Abstract
QUALITY PROBLEM: Despite its success in other industries, process standardization in health care has been slow to gain traction or to demonstrate a positive impact on the safety of care. INTERVENTION: The High 5s project is a global patient safety initiative of the World Health Organization (WHO) to facilitate the development, implementation and evaluation of Standard Operating Protocols (SOPs) within a global learning community to achieve measurable, significant and sustainable reductions in challenging patient safety problems. GOALS: The project seeks to answer two questions: (i) Is it feasible to implement standardized health care processes in individual hospitals, among multiple hospitals within individual countries and across country boundaries? (ii) If so, what is the impact of standardization on the safety problems that the project is targeting? METHOD: The two key areas in which the High 5s project is innovative are its use of process standardization both in hospitals within a country and in multiple participating countries, and its carefully designed multi-pronged approach to evaluation. STATUS: Three SOPs-correct surgery, medication reconciliation, concentrated injectable medicines-have been developed and are being implemented and evaluated in multiple hospitals in seven participating countries. Nearly 5 years into the implementation, it is clear that this is just the beginning of what can be seen as an exercise in behavior management, asking whether health care workers can adapt their behaviors and environments to standardize care processes in widely varying hospital settings.
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 | 0.153 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".