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Record W2011425393 · doi:10.3138/physio.61.4.221

Strategic Responses to Fiscal Constraints: A Health Policy Analysis of Hospital-Based Ambulatory Physical Therapy Services in the Greater Toronto Area (GTA)

2009· article· en· W2011425393 on OpenAlexafffundvenueabout
Michel D. Landry, Molly C. Verrier, A. Paul Williams, David Zakus, Raisa Deber

Bibliographic record

VenuePhysiotherapy Canada · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsToronto Rehabilitation InstitutePublic Health OntarioUniversity of Toronto
FundersCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsRestructuringAmbulatoryBusinessFiscal yearAmbulatory careHealth careBudget constraintMedicineFinanceEconomicsEconomic growth

Abstract

fetched live from OpenAlex

PURPOSE: Ambulatory physical therapy (PT) services in Canada are required to be insured under the Canada Health Act, but only if delivered within hospitals. The present study analyzed strategic responses used by hospitals in the Greater Toronto Area (GTA) to deliver PT services in an environment of fiscal constraint. METHODS: Key informant interviews (n = 47) were conducted with participants from all hospitals located within the GTA. RESULTS: Two primary strategic responses were identified: (1) "load shedding" through the elimination or reduction of services, and (2) "privatization" through contracting out or creating internal for-profit subsidiary clinics. All hospitals reported reductions in service delivery between 1996 and 2003, and 15.0% (7/47 hospitals) fully eliminated ambulatory services. Although only one of 47 hospitals contracted out services, another 15.0% (7/47) reported that for-profit subsidiary clinics were created within the hospital in order to access other more profitable forms of quasi-public and private funding. CONCLUSIONS: Strategic restructuring of services, aimed primarily at cost containment, may have yielded short-term financial savings but has also created a ripple effect across the continuum of care. Moreover, the rise of for-profit subsidiary clinics operating within not-for-profit hospitals has emerged without much public debate and with little research to evaluate its impact.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.902
Threshold uncertainty score0.707

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.308
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2009
Admission routes4
Has abstractyes

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