Protocol for developing a set of performance measures to monitor and evaluate delirium care quality for older adults in the emergency department using a modified e-Delphi process
Bibliographic record
Abstract
INTRODUCTION: Older adults are at high risk of developing delirium in the emergency department (ED). Delirium associated with an ED visit is independently linked to poorer outcomes such as increased length of hospital stay and mortality. Performance measures (PMs) are needed to identify variations in the quality of delirium care to help focus improvement efforts where they are most needed. A preliminary list of 11 quality statements and 24 PMs was developed based on a synthesis of high-quality clinical practice guidelines. The purpose of this study is to gain consensus on a subset of PMs that can be used to evaluate delirium care quality for older ED patients. METHODS AND ANALYSIS: This protocol for a modified e-Delphi study is informed by the Guidance on Conducting and REporting DElphi Studies. Clinical experts from across Canada and internationally will be recruited through peer referral, professional organisations and social media calls for expressions of interest. A minimum of 17 participants will be recruited. The primary survey for each round will consist of closed-ended questions with the opportunity to provide comments to justify decisions and clarify understanding. Using 9-point Likert scales, participants will rate each quality statement according to the concepts of importance and actionability, then its associated PMs according to the concept of necessity. Results will be fed back to participants in subsequent rounds. A priori stopping criteria have been defined in terms of consensus and stability. A minimum of three rounds will be undertaken to allow participants to have feedback, revise previous responses, then stabilise responses. ETHICS AND DISSEMINATION: Ethical approval was provided at the University of Manitoba Health Research Ethics Board (ID HS25728 (H2022:340)). Informed consent will be obtained electronically using the Research Electronic Data Capture secure online platform. Knowledge translation and dissemination will be done through traditional (eg, conference presentations, peer-reviewed publications) and non-traditional (eg, ED Grand Rounds) strategies.
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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 | 0.151 | 0.118 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.062 | 0.016 |
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".