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Record W4221118214 · doi:10.1177/11786329221078124

interRAI Pediatric Home Care (PEDS-HC) Assessment Tool: Evaluating Ontario Healthcare Workers’ Experience

2022· article· en· W4221118214 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueHealth Services Insights · 2022
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of OttawaAgricultural Research Institute of Ontario
Fundersnot available
KeywordsMedicineHealth careNursingNeeds assessmentEquity (law)Service (business)Focus groupQuality (philosophy)Business

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0060.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.064
GPT teacher head0.441
Teacher spread0.376 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it