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Record W2031274930 · doi:10.1353/cja.2005.0046

Trends in the Utilization of Specific Health Care Services among Older Manitobans: 1985 to 2000

2005· article· en· W2031274930 on OpenAlexaffabout
Marcia Finlayson, Lisa M. Lix, Gregory S. Finlayson, Terry Fong

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGerontologyPsychologyMedicine

Abstract

fetched live from OpenAlex

This paper examines 16-year trends in the utilization of hospital and physician services by Manitobans aged 75 and more, using data from the Manitoba Population Health Research Data Repository. Trends are examined across five measures of hospital services (separations, short-stay days, long-stay days, cataract surgeries, and hip/knee replacements) and two measures of physician care (overall visit rate, and proportion having seven or more visits). Results show changes in the utilization of these services among older adults living in Manitoba over time, with the extent of change varying with the service under consideration, age, and location of residence. Previously large utilization differentials are shown to be shrinking; for example, cataract surgery rates across regions and physician visit rates by age. For other services, such as the rates of hip or knee replacement surgery, the differences across regions are increasing. Findings indicate that global generalizations about the impact of older adults on the health care system are subject to question, as regional differences and differences between age groups (75-84, 85+) can be significant.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.268
Threshold uncertainty score0.538

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.246
Teacher spread0.216 · 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

Citations4
Published2005
Admission routes2
Has abstractyes

Explore more

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