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Record W2495891374 · doi:10.1186/s12913-016-1596-y

A descriptive analysis of medical health services utilization of Veterans living in Ontario: a retrospective cohort study using administrative healthcare data

2016· article· en· W2495891374 on OpenAlexafffundabout
Alice Aiken, Alyson Mahar, Paul Kurdyak, Marlo Whitehead, Patti A. Groome

Bibliographic record

VenueBMC Health Services Research · 2016
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsInstitute for Clinical Evaluative SciencesCentre for Addiction and Mental HealthQueen's University
FundersTrue Patriot Love Foundation
KeywordsMedicineHealth administrationHealth carePublic healthMental healthRetrospective cohort studyVeterans AffairsFamily medicineHealth services researchPopulationCohortHealth informaticsEmergency departmentDescriptive statisticsGerontologyEnvironmental healthNursingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Health services utilization by Veterans following release may be different than the general population as the result of occupational conditions, requirements and injuries. This study provides the first longitudinal overview of Canadian Veteran healthcare utilization in the Ontario public health system. METHODS: This is a retrospective cohort study designed to use Ontario's provincial healthcare data to study the demographics and healthcare utilization of Canadian Armed Forces (CAF) & RCMP Veterans living in Ontario. Veterans were eligible for the study if they released between January 1, 1990 and March 31, 2013. Databases at the Institute for Clinical Evaluative Sciences were linked by a unique identifier to study non-mental health related hospitalizations, emergency department visits, and physician visits. Overall and age-stratified descriptive statistics were calculated in five-year intervals following the date of release. RESULTS: The cohort is comprised of 23, 818 CAF or RCMP Veterans. Following entry into the provincial healthcare system, 82.6 % (95 % CI 82.1-83.1) of Veterans saw their family physician at least once over the first five years following release, 60.7 % (95 % CI 60.0-61.3) saw a non-mental health specialist, 40.8 % (95 % CI 40.2-41.5) went to the emergency department in that same time period and 9.9 % (9.5-10.3) were hospitalized for non-mental health related complaints. Patterns of non-mental health services utilization appeared to be time and service dependant. Stratifying health services utilization by age of the Veteran at entry into the provincial healthcare system revealed significant differences in service use and intensity. CONCLUSION: This study provides the first description of health services utilization by Veterans, following release from the CAF or RCMP. This work will inform the planning and delivery of support to Veterans in 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 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)0.001
metaresearch head score (Gemma)0.003
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 score0.092
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.006
Science and technology studies0.0010.001
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 head0.420
GPT teacher head0.591
Teacher spread0.171 · 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

Citations14
Published2016
Admission routes3
Has abstractyes

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