Use of the interRAI PEDS HC in children receiving home care in Ontario, Canada
Bibliographic record
Abstract
Abstract Background There is no standard assessment tool for pediatric home care recipients in Canada, limiting the availability of comparable, population-based data. The objective of this study was to describe pediatric home care recipients who were part of a pilot implementation of the interRAI Pediatric Home Care Assessment Form (PEDS-HC) among medically complex children referred to home care agencies in three regions in Ontario, Canada. Methods All 14 agencies providing home care to children in Ontario were invited to participate in the pilot project, and 9 participated in an education session. Three of these agencies used the PEDS-HC during the pilot implementation between February 2018 and March 2020. We used de-identified data to describe the demographics, home care needs, and diagnoses of pediatric home care recipients. Results The sample of 474 assessments was predominantly male (60.34%), with an average age at assessment of 12.36 years (SD 4.56). Most (78.48%) reported English as their primary language. Most children assessed had between two and eight medical diagnoses. Diagnoses reported varied: gastrointestinal, musculoskeletal, respiratory and neurological conditions were most common. The prevalence of urinary incontinence (40.1%) and bowel incontinence (70.9%) were high. Over 60% of children were rarely or only sometimes understood. A majority of children had adequate hearing (83.5%) and vision (68.6%). Extensive services were being provided in 10% of children assessed. Most children received care both at school and at home (70.89%), with 20.89% receiving home care only. Conclusions The PEDS-HC provides a detailed, standardised descriptive profile of medically complex children receiving home care. Expanding use of PEDS-HC would promote consistency in care planning and delivery on the patient level, enable cross-jurisdictional comparisons, and inform utilization tracking and health care funding decisions on the organization and provincial levels.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".