Enhancing Patient Safety through the Management of Clostridium difficile at Toronto East General Hospital
Bibliographic record
Abstract
In 2005 Toronto East General Hospital experienced a steady increase in the number of C. difficile cases diagnosed within the hospital. This was identified as a patient safety issue, and several areas of the hospital came together to address the problem. Pharmacy immediately started a medication review of past cases. Environmental services took the lead on the environmental cleaning, and a process was put into place with Infection Control so that housekeeping knew of every room that contained a patient with C. difficile and enhanced cleaning could be practised. Staff, including nursing, housekeeping and porters, were educated on C. difficile and the methods of transmission. A business case was developed for a disposable bedpan system, and this was approved by the senior team. A new washable product was tried out with success for the overhead patient light pulls and bathroom call bell systems. Infection rates were shared with staff through a variety of venues. As a result of the initiatives, the hospital has seen a decrease of 50% in the rates of C. difficile. A bonus was that our MRSA rates dropped as well.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".