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Record W198652317 · doi:10.3233/prm-2009-0081

Care Coordination and the prosthetic clinic: A clinical outcomes and program evaluation project

2009· article· en· W198652317 on OpenAlexaffabout
Rochelle Rein, Kelly Thorstad, Kathleen Montpetit, Susan Glover Takahashi, Noémi Dahan Oliel

Bibliographic record

VenueJournal of Pediatric Rehabilitation Medicine · 2009
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsShriners Hospitals for Children - Canada
FundersMaternal and Child Health BureauShriners Hospitals for Children
KeywordsMedicineHealth careFamily medicineNursing

Abstract

fetched live from OpenAlex

INTRODUCTION: Care Coordination is the health care delivery model that has been implemented in the prosthetic clinic at the Shriners Hospital for Children - Canada. In delivering comprehensive, family-centered services, it is important to evaluate the extent to which patients and families perceive coordinated care to occur. AIM: To evaluate the delivery of Care Coordination services to our patients and families in the prosthetic clinic, and to identify strengths and areas for improvement. The time required to provide coordinated care was also evaluated. METHODS: The MPOC-20 was administered to the parents of 23 lower extremity deficiency or amputee patients seen in the prosthetic clinic over a 14-month period. RESULTS: Providing coordinated and comprehensive care related to involving families as part of the team was the most frequently reported strength of the prosthetic clinic Care Coordination. Providing information to families about their child's progress and having information and resources available were areas identified as needing improvement by approximately 30% of respondents. Those with complex health needs required five times the amount of Care Coordination devoted time than the average patient. CONCLUSIONS: The MPOC-20 proved to be a useful tool to highlight areas for improvement in the prosthetic clinic and to validate aspects of care coordination that were appreciated by families.

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.

How this classification was reachedexpand

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)0.005
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.377
Teacher spread0.352 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2009
Admission routes2
Has abstractyes

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