Using experience-based co-design to explore care experiences and identify practice change priorities for children with medical complexity in the paediatric intensive care unit
Bibliographic record
Abstract
OBJECTIVES: Children with medical complexity (CMC) frequently experience acute deterioration requiring paediatric intensive care unit (PICU) hospitalisation. Collaboration between families and healthcare professionals (HCPs) is vital yet often challenging, suggesting a new care approach is needed. This study explored the PICU care experiences of CMC, parents and HCPs and identified common priorities and practice changes to enhance care. DESIGN: An experience-based co-design (EBCD) approach was used. Semistructured interviews were conducted with CMC and parents (stage 1) and HCPs (stage 2). A co-design event with parents and HCPs followed (stage 3). SETTING: Interviews took place in family homes, hospital meeting rooms and virtually. The co-design event took place at the hospital. PARTICIPANTS: Interviews: CMC and parents (n=21, 13 families) within 1 year of their most recent PICU discharge. PICU and complex care service HCPs (n=15). Co-design event: parents and HCPs (n=22). Maximum variation sampling was used. RESULTS: Stage 1: Child and family-related themes included becoming known, becoming a parent caregiver or child care receiver, establishing caregiver relationships, and expecting a responsive and dignified caregiving environment. Stage 2: HCP-related themes included adapting to a different care approach, positioning parents as collaborators, navigating personal connections, and providing continuity of care. Stage 3: Two videos (sharing child and family perspectives, and HCPs' perspectives) were produced to promote discussion at the co-design event. Common care priorities included increase HCPs' awareness of who the child is when they are well; improve interdepartmental communication; enhance HCPs' understanding of families' expertise and needs; enhance parent-HCP partnerships and develop HCP training programmes. Potential practice changes were identified. CONCLUSIONS: Participants identified the need for a collaborative approach to care for critically ill CMC, integrating the expertise of children, parents and HCPs. EBCD can help ground the perspectives and needs of HCPs, children and families in future PICU patient and family-centred care interventions.
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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 | 0.036 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".