Poster ID: 39 How is Paediatric Inpatient Care in Canadian Hospitals Structured to Respond to the Needs of Children with Medical Complexity?
Bibliographic record
Abstract
Abstract Background Children with medical complexity (CMC) have diverse medical diagnoses and the following characteristics: multisystem disease, functional limitations, high care needs, and high healthcare utilization. CMC have intensive inpatient resource use with associated high healthcare costs. Best practices and service delivery models to guide inpatient care of CMC are not yet established and likely vary considerably among institutions. Objectives The objective of this study is to describe the availability and organization of resources for CMC during inpatient care across Canadian paediatric hospitals and assess how these services are adapted to the specific needs of CMC. Design/Methods This environmental scan was conducted as a cross-sectional, researcher-administered virtual survey. The instrument was developed based on a literature review of inpatient complex care and consensus among a panel of content experts. The survey was pilot tested with two complex care physicians and one with expertise in questionnaire development. The survey was available in both English and French. Survey participants were identified through snowball sampling within the Canadian Paediatric Inpatient Research Network (PIRN) with the aim of identifying a key informant from each paediatric hospital. Consistent members of the research team administered survey questions to participants via Zoom, and responses were entered into the Qualtrics platform. Quantitative survey responses were analyzed using univariate descriptive analysis. Qualitative responses were categorized and described for comparative purposes. Results Ten interviews were conducted representing ten different paediatric hospitals. Although nine had established complex care programs, only one of these had a specific inpatient care team for CMC. The physician-to-patient and nurse-to-patient ratios were the same for CMC and non-CMC patients. All sites had some form of standardized documentation to support inpatient care of CMC, but each had different elements and purposes. Only two sites had conducted formal evaluation of their inpatient program for CMC. Key informants rated their hospital’s ability to meet the specific inpatient needs of CMC as a 6.5 out of 10 (on average), with a range of 4-8. Conclusion These results suggest a relative lack of inpatient resources directed to CMC, with a high proportion of sites having a complex care program but with few that include a dedicated inpatient team. Further, there is a lack of standardization across the country in terms of documentation and best practices. Key informants perceive room for improvement in inpatient care at their sites. Future studies will identify evidence-based best practices that can be further evaluated and spread.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 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".