The work of a dedicated inpatient diabetes care team in a district general hospital
Bibliographic record
Abstract
Abstract We describe the work of a multidisciplinary inpatient diabetes care team in a 400 bed district general hospital over a four‐year period. Also included are some observations on a positive contribution to reduced length of stay for people with diabetes in hospital, and low incidences of prescription and management errors in the first National Diabetes Inpatient Audit in 2009. Specifically between 2005 and 2007 the average length of stay in days for all patients whose diagnosis included diabetes fell from 9.39 to 3.76 days despite the total number of patients increasing from 507 to 633 over the same quarter each year. The inpatient team provided almost 1000 visits to patients with diabetes in the first six months of each year 2008 and 2009, and at the first National Diabetes Inpatient Audit had only 5% prescription errors and 3% management errors (versus 19% and 14% respectively nationally) with 100% appropriate blood glucose testing. We suggest that a dedicated inpatient diabetes care team raises the quality of care for patients and enhances patient and professional education; we also suggest that audit standards should be developed for inpatient diabetes care and assessed in future national audits. Copyright © 2011 John Wiley & Sons.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".