interRAI Pediatric Home Care (PEDS-HC) Assessment Tool: Evaluating Ontario Healthcare Workers’ Experience
Bibliographic record
Abstract
High quality pediatric homecare requires comprehensive assessment of the needs, supports, and health care challenges of children with special healthcare needs and their families. There is no standardized homecare assessment system to evaluate children's clinical needs in the home (support services, equipment, etc.) in Ontario, Canada, which contributes to inequitable homecare service allocation. In 2017, the interRAI Pediatric Home Care assessment tool (PEDS-HC) was implemented on a pilot basis in several regions of Ontario. This qualitative descriptive study explores the experiences of homecare coordinators using the PEDS-HC, seeking to understand the utility and feasibility of this tool through focus group discussion. Four major themes were identified including: the benefits of the tool; areas for modification; challenges to use; and Clinical Assessment Protocols to develop. These themes can guide modifications to the tool to improve utility and improve pediatric home care services. The PEDS-HC is an effective tool to assess children needing homecare in a standardized and comprehensive manner. Use of the tool can improve the quality of homecare services by ensuring equity in service provision and facilitate early identification of clinical issues to prevent unexpected health deteriorations.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".