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A population‐based cohort study of ambulatory care service utilization among older adults

2010· article· en· W2142844805 on OpenAlexafffundabout
Jason X Nie, Li Wang, C. Shawn Tracy, Rahim Moineddin, Ross Upshur

Bibliographic record

VenueJournal of Evaluation in Clinical Practice · 2010
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsHealth Sciences CentreInstitute for Clinical Evaluative SciencesSunnybrook Health Science Centre
FundersCanada Research ChairsInstitute for Clinical Evaluative Sciences
KeywordsAmbulatoryMedicineAmbulatory carePopulationCohortHealth careCohort studyGerontologyRetrospective cohort studyFamily medicineEmergency departmentDemographyEmergency medicineEnvironmental healthNursing

Abstract

fetched live from OpenAlex

RATIONALE, AIMS AND OBJECTIVES: Age-related effects on ambulatory care service utilization are not well understood. We aim to measure the utilization patterns of ambulatory health care services (i.e. family physician visits, specialist physician visits and emergency room visits) in the late life course (65 years and older). METHODS: A population-based retrospective cohort study was conducted for the period 1 April 2005 to 31 March 2006. All Ontario, Canada, residents aged 65+ and eligible for government health insurance were included in the analysis. RESULTS: This population-based cohort study demonstrates considerable increase in utilization rates and variability of ambulatory services as age increases. Variations in utilization were observed by gender as overall women were more likely to consult a family physician, and men more likely to visit specialists and the emergency room. A small group of high users, constituting 5.5% of the total population, accounted for 18.7% of total ambulatory visits. Finally, we report socio-economic status (SES) based disparity for specialist services in which high users were more likely to have higher SES. CONCLUSIONS: There is increasing utilization and variability in ambulatory service utilization with increase in age. Further research is required to explain the gender and SES differences reported in this study.

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)0.002
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 score0.045
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.178
GPT teacher head0.593
Teacher spread0.415 · 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

Citations39
Published2010
Admission routes3
Has abstractyes

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