<scp>NICE</scp> to <scp>HELP</scp> : Operationalizing National Institute for Health and Clinical Excellence Guidelines to Improve Clinical Practice
Bibliographic record
Abstract
The National Institute for Health and Clinical Excellence (NICE) in the United Kingdom developed guidelines for the diagnosis, prevention, and management of delirium in July 2010 that included 10 recommendations for delirium prevention. The Hospital Elder Life Program (HELP) is a targeted multicomponent strategy that has proven effective and cost-effective at preventing functional and cognitive decline in hospitalized older persons. HELP provided much of the basis for seven of the NICE recommendations. Given interest by new HELP sites to meet NICE guidelines, three new protocols addressing hypoxia, infection, and pain that were not previously included in the HELP program were developed. In addition, the NICE dehydration guideline included constipation, which was not specifically addressed in the HELP protocols. This project describes the systematic development of three new protocols (hypoxia, infection, pain) and the expansion of an existing HELP protocol (constipation and dehydration) to achieve alignment between the HELP protocols and NICE guidelines. Following the Institute of Medicine recommendations for developing trustworthy guidelines, an interdisciplinary group of experts conducted a systematic review of current literature, rated the quality of the evidence, developed intervention protocols based on the highest-quality evidence, and submitted the protocols first to internal review and then to external review by an interdisciplinary panel of experts. The protocols were revised based on the review process and incorporated into the HELP materials. Inclusion of these protocols enhances the scope of the HELP program and allows fulfillment of NICE guideline recommendations for delirium prevention. The rigorous process applied may provide a useful example for updating existing guidelines or protocols that may be applicable to a broad range of clinical applications.
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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 | 0.138 | 0.479 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.012 | 0.018 |
| Research integrity | 0.020 | 0.018 |
| Insufficient payload (model declined to judge) | 0.047 | 0.043 |
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".