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Record W2908416134 · doi:10.1177/1179572718820543

In-Home Rehabilitation Resources and Avoidable Admissions to Inpatient Rehabilitation after Stroke: An Ecological Study

2018· article· en· W2908416134 on OpenAlexaffabout
Matthew J. Meyer, Robert Teasell, Amardeep Thind, John J. Koval, Mark Speechley

Bibliographic record

VenueRehabilitation Process and Outcome · 2018
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsSt Joseph's Health CareLondon Health Sciences CentreLawson Health Research InstituteWestern University
Fundersnot available
KeywordsRehabilitationMedicineStroke (engine)Logistic regressionCommunity-based rehabilitationTest (biology)Emergency medicinePhysical therapyEcology

Abstract

fetched live from OpenAlex

Background and purpose: In Ontario (Canada’s most populous province), it has been suggested that mildly impaired stroke patients are being admitted to inpatient rehabilitation unnecessarily due to a lack of alternative options in the community. This ecological study aimed to formally test this hypothesis. Methods: Patients admitted to an inpatient rehabilitation bed in Ontario’s most highly functioning patient classification group (Rehabilitation Patient Group 1160) were retrospectively identified as potentially avoidable admissions, and the proportion of such patients was calculated for each Local Health Integration Network every year between 2006/2007 and 2010/2011. Five indicators of community-based rehabilitation availability were used to test the relationships between avoidable admissions and resource indicators. Results: Of the 25 correlations tested, 21 agreed with the hypothesized direction of effect and 4 reached statistical significance. Logistic-linear regressions on combined data from each of the 5 years demonstrated statistically significant associations between all 5 resource indicators and the proportion of potentially avoidable admissions. Conclusions: This study confirms the suggestion of variation in the proportion of mildly impaired patients admitted to inpatient rehabilitation across Ontario’s Local Health Integration Networks. It also adds evidence to support the concern that a lack of community-based rehabilitation is contributing to these potentially avoidable admissions.

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)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.012
GPT teacher head0.329
Teacher spread0.317 · 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.

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

Citations0
Published2018
Admission routes2
Has abstractyes

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