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Record W2061634245 · doi:10.3138/ptc.59.3.173

Barriers to Rehabilitation in Primary Health Care in Ontario: Funding and Wait Times for Physical Therapy Services

2007· article· en· W2061634245 on OpenAlexvenueaboutno aff
Cheryl Cott, Rachel Devitt, Laura-Beth Falter, Leslie Soever, Laura Passalent

Bibliographic record

VenuePhysiotherapy Canada · 2007
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal Disorders and Rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRehabilitationFamily medicineOdds ratioDebilityOddsHealth careHealth services researchPublic healthLogistic regressionNursingPhysical therapy

Abstract

fetched live from OpenAlex

Purpose: The purpose of this study was to examine barriers to accessing physical therapy (PT) services in Ontario primary health care with respect to funding sources and wait times. Methods: A stratified random sample of 1100 registered Ontario PTs and 3000 Ontario family physicians were surveyed by mail in 2004. Relationships were examined between PT wait times, funding source, geographical region and caseload composition. Results: Physicians identified the cost of private rehabilitation and long wait times as the most common barriers to referring patients to rehabilitation. Wait times for PT were longer in publicly funded settings than in privately funded practice settings (p, 0.001) and in the North (p, 0.001) and East (p 5 0.010) regions of Ontario compared with the most urban region of Ontario. Patients with chronic musculoskeletal conditions, cardiopulmonary conditions and general debility were at least three times more likely to receive PT services at publicly funded than privately funded practice settings. Furthermore, patients with acute musculoskeletal conditions were less likely to receive PT services in publicly funded practice settings (odds ratio 5 0.11, 95% confidence interval 5 0.05-0.23). Conclusions: Current Ontario health-care structures may affect access to PT services for vulnerable populations such as those with chronic conditions, those lacking private health insurance and those living in less urban regions of Ontario.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.004
GPT teacher head0.284
Teacher spread0.279 · 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

Citations25
Published2007
Admission routes2
Has abstractyes

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