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Record W2056002548 · doi:10.1017/s1041610202008098

Linkage of the Canadian Study of Health and Aging to Provincial Administrative Health Care Databases in Nova Scotia

2001· article· en· W2056002548 on OpenAlexaffabout
A.M. Yip, George Kephart, Kenneth Rockwood

Bibliographic record

VenueInternational Psychogeriatrics · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHealth careFamily medicinePublic healthMedical recordDatabaseRecord linkageMedicineLinkage (software)Health policyPopulationEnvironmental healthGerontologyNursingPolitical scienceLaw

Abstract

fetched live from OpenAlex

The Canadian Study of Health and Aging (CSHA) was a cohort study that included 528 Nova Scotian community-dwelling participants. Linkage of CSHA and provincial Medical Services Insurance (MSI) data enabled examination of health care utilization in this subsample. This article discusses methodological and ethical issues of database linkage and explores variation in the use of health services by demographic variables and health status. Utilization over 24 months following baseline was extracted from MSI's physician claims, hospital discharge abstracts, and Pharmacare claims databases. Twenty-nine subjects refused consent for access to their MSI file; health card numbers for three others could not be retrieved. A significant difference in healthcare use by age and self-rated health was revealed. Linkage of population-based data with provincial administrative health care databases has the potential to guide health care planning and resource allocation. This process must include steps to ensure protection of confidentiality. Standard practices for linkage consent and routine follow-up should be adopted. The Canadian Study of Health and Aging (CSHA) began in 1991-92 to explore dementia, frailty, and adverse health outcomes (Canadian Study of Health and Aging Working Group, 1994). The original CSHA proposal included linkage to provincial administrative health care databases by the individual CSHA study centers to enhance information on health care utilization and outcomes of study participants. In Nova Scotia, the Medical Services Insurance (MSI) administration, which drew the sampling frame for the original CSHA, did not retain the list of corresponding health card numbers. Furthermore, consent for this access was not asked of participants at the time of the first interview. The objectives of this study reported here were to examine the feasibility and ethical considerations of linking data from the CSHA to MSI utilization data, and to explore variation in health services use by demographic and health status characteristics in the Nova Scotia community cohort.

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)0.001
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 score0.057
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.076
GPT teacher head0.442
Teacher spread0.366 · 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

Citations6
Published2001
Admission routes2
Has abstractyes

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