Bibliographic record
Abstract
Dear Editor: Vigod et al1 found that patients in Ontario were often readmitted to another psychiatric hospital within 30 or 90 days after discharge. It was already debatable whether readmission rates could be a reliable indicator of inpatient care, given that readmission rates also depend on what kind of treatment and support are available in the community.2 The study by Vigod et al made a significant contribution to the debate by demonstrating that, given the number of readmissions to other hospitals, readmission rates to the same hospital cannot be considered a reliable indicator of quality of inpatient care, at least not in regions such as Ontario, where there is no incentive for patients to go to the same hospital. However, we think that readmissions to other hospitals (and not the same hospital) should be taken into consideration as a possible indicator of quality of care under certain conditions. We work in the British National Health Service (NHS), where, at least in mental health, people have to be admitted to their local hospital. This is good for continuity of care, but the downside is that patients cannot choose for themselves.3 If NHS patients want to be admitted to a different hospital, they will have to go to a private hospital. They have to pay for it themselves, unless they have taken out private insurance and their insurance company agrees to pay. Patients might prefer to go to another hospital, if they are not satisfied with the care they received or because there was no bed available. The data from Vigod et al1 offer some support that readmissions to another hospital are related to the quality of care, at least in services where (unlike the British NHS) patients have free choice and where care in the community is organized independently from the hospital. Under those circumstances, readmissions overall might be determined, at least partly, by the quality of care in the community, but readmissions to a different hospital may be determined by patient choice or unavailability of beds.
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 | 0.006 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.009 | 0.005 |
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".