The National Asthma and COPD Audit Programme in East Kent Hospitals University NHS Foundation Trust – The first year
Bibliographic record
Abstract
Background: –The National Asthma and COPD Audit Programme (NACAP) aims to drive improvements in the quality of care and services provided forRespiratory patients in England and Wales (RCP / BTS 2017) –Part of this programme is the continuous audit of admission to hospital for those patients with COPD –This commenced in April 2017 and currently is scheduled to continue until March 2019 –Best Practice Tariff (BPT) was introduced to improve the proportion of patients who receive specialist respiratory input to their care within 24 hours of admission and completion of a COPD discharge bundle. Aims: –Primary aim was to deliver on the COPD BPT –Secondary aim was to improve the inpatient experience and deliver evidence based care –This would be evidenced by length of stay, readmission rates and inpatient mortality rates Methods: Recruited Associate Practitioners, Registered Nurse and Physiotherapist to into Specialist Practioner Roles. Results: Development of an Inpatient Respiratory Practitioner Team has enabled the Trust to achieve the required 60% for BPT by quarter 3 (Oct-Dec 2017) and thus qualification for the enhanced tariff
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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 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".