Co-development of a transitions in care bundle for patient transitions from the intensive care unit: a mixed-methods analysis of a stakeholder consensus meeting
Bibliographic record
Abstract
BACKGROUND: Intensive care unit (ICU) patients undergoing transitions in care are at increased risk of adverse events and gaps in medical care. We evaluated existing patient- and family-centered transitions in care tools and identified facilitators, barriers, and implementation considerations for the application of a transitions in care bundle in critically ill adults (i.e., a collection of evidence-based patient- and family-centred tools to improve outcomes during and after transitions from the intensive care unit [ICU] to hospital ward or community). METHODS: We conducted a concurrent mixed methods (quan + QUAL) study, including stakeholders with experience in ICU transitions in care (i.e., patient/family partners, researchers, decision-makers, providers, and other knowledge-users). First, participants scored existing transitions in care tools using the modified Appraisal of Guidelines, Research and Evaluation (AGREE-II) framework. Transitions in care tools were discussed by stakeholders and either accepted, accepted with modifications, or rejected if consensus was achieved (≥70% agreement). We summarized quantitative results using frequencies and medians. Second, we conducted a qualitative analysis of participant discussions using grounded theory principles to elicit factors influencing AGREE-II scores, and to identify barriers, facilitators, and implementation considerations for the application of a transitions in care bundle. RESULTS: Twenty-nine stakeholders attended. Of 18 transitions in care tools evaluated, seven (39%) tools were accepted with modifications, one (6%) tool was rejected, and consensus was not reached for ten (55%) tools. Qualitative analysis found that participants' AGREE-II rankings were influenced by: 1) language (e.g., inclusive, balance of jargon and lay language); 2) if the tool was comprehensive (i.e., could stand alone); 3) if the tool could be individualized for each patient; 4) impact to clinical workflow; and 5) how the tool was presented (e.g., brochure, video). Participants discussed implementation considerations for a patient- and family-centered transitions in care bundle: 1) delivery (e.g., tool format and timing); 2) continuity (e.g., follow-up after ICU discharge); and 3) continuous evaluation and improvement (e.g., frequency of tool use). Participants discussed existing facilitators (e.g., collaboration and co-design) and barriers (e.g., health system capacity) that would impact application of a transitions in care bundle. CONCLUSIONS: Findings will inform future research to develop a transitions in care bundle for transitions from the ICU, co-designed with patients, families, providers, researchers, decision-makers, and knowledge-users.
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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 | 0.125 | 0.147 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".