Comparing subspecialty and intensive care providers perspectives on pediatric complex chronic patients: A survey study
Bibliographic record
Abstract
Introduction Pediatric complex chronic care patients present unique challenges regarding healthcare provision: complex medical regimes, complicated family/provider dynamics, and multiple healthcare teams that can result in inconsistent care. This study examined subspecialty providers’ perspectives regarding pediatric complex chronic care patients and compared them with acute care providers while exploring opportunities to better facilitate care provided to pediatric complex chronic care patients. Methods This survey study occurring within a Canadian tertiary care pediatric center, utilized REDCap to deploy surveys involving Likert Scale and short answer questions. The Kruskal–Wallis test compared subspecialty provider perspectives when providing care to pediatric complex chronic care patients versus non-pediatric complex chronic care patients; and perspectives between subspecialty and acute care providers. Results Survey response rate was 24/46 (52.2%). Eight overarching themes emerged from Likert scale questions. Short answer questions revealed factors that may facilitate care provided to pediatric complex chronic care patients: access to funding; discharge planning; communication methods between specialists; and healthcare provider continuity. Several differences were identified when working with pediatric complex chronic care patients, compared to non-pediatric complex chronic care patients: increased time/resource burden; managing expectations of patients/families; navigating discrepancies in goals of care; complexity of coordination between services; increased efforts in coordinating discharge from hospital and working with medicalized patients/families. Discussion Exploring pediatric subspecialty provider perspectives of pediatric complex chronic care patients revealed opportunities to enhance care provided: increased resources to ease the strain of care provision for parents, implementation of a discharge coordinator, complex care clinics with a pediatrician to “quarterback” care, and co-management between the complex care pediatrician and acute care physician when admitted to an acute care service. Implementation of these initiatives may improve the care provided to pediatric complex chronic care patients.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".