19 How are paediatric tertiary care hospitals structured to respond to the needs of children with medical complexity during acute deteriorations? A landscape study in Canada
Bibliographic record
Abstract
Abstract Background Children with medical complexity (CMC) are at risk of unplanned healthcare visits especially due to acute clinical deteriorations. Complex care (CC) programs help facilitate the needs of CMC. Objectives To identify the organizational and administrative resources available for the care of CMC in Canadian tertiary care paediatric hospitals and to assess how physicians believe these resources are adapted to the specific urgent needs of CMC. Design/Methods In this observational study, key informants representing complex care (CC) and paediatric emergency medicine (PEM) services from 15 paediatric tertiary care hospitals in Canada completed cross-sectional structured questionnaires. Participants were identified through national research networks (Pediatric Emergency Research Canada (PERC), Pediatric Inpatient Research Network (PIRN) and by snowball sampling. Utilizing the Lime Survey web application, two questionnaires (one for PEM, one for CC) were develop based on a literature review and following Burns methodology. Verbal questionnaires were administered via a secured teleconference application or completed digitally. Descriptive data were generated using Excel and SPSS v.29. Results From 09/2022 to 09/2023, 93% (28/30) key informants completed questionnaires (15 PEM, 13 CC, Table 1). Across the 15 sites, 12 had a CC program or clinic. Information about established CC programs was available for 10 sites (Table 2), from participating CC informants: 4/10 offered outpatient services; 6/10 offered inpatient and outpatient services; 8/10 offered last minute appointments for CMC. CC programs had variable staffing: mostly physicians (median 3 FTE, range: 0.2-6) and nurse practitioners (0.75 FTE, range: 0-9) or registered nurses (0.9 FTE, 0-8). CC informants reported offering an ED consultation service at 8/10 sites, while 6/12 PEM participants reported access to such a service. CC informants reported that their program rarely offered consultations during weekends (2/10) or nights (1/10). Across all sites, PEM informants reported good access to documents to help with continuity of care including emergency care plans (13/15), medical history (14/15), goals of care (13/15). Using an 11-point scale, CC informants rated their hospital’s median ability to meet the outpatient needs of CMC as 6.5 (range: 0-10), and their ED’s median ability to meet the needs of CMC as 7 (range 5-10). PEM informants reported their median ability to meet the needs of CMC as 8 (range 6-9). Informants made suggestions to improve the ED care of CMC (Table 3). Conclusion There exists wide variation in the structures caring for CMC and their availability in case of acute needs. National collaboration between CC and PEM teams may facilitate the design of programs to improve the acute outpatient care of CMC.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".