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Record W2070362105 · doi:10.1002/gps.1358

Antipsychotic use in the elderly: shifting trends and increasing costs

2005· article· en· W2070362105 on OpenAlexaffabout
Mark Rapoport, Muhammad Mamdani, Kenneth I. Shulman, Nathan Herrmann, Paula A. Rochon

Bibliographic record

VenueInternational Journal of Geriatric Psychiatry · 2005
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsBaycrest HospitalUniversity of TorontoInstitute for Clinical Evaluative SciencesSunnybrook Health Science CentreHealth Sciences Centre
Fundersnot available
KeywordsAntipsychoticMedicineDementiaPopulationCensusPsychiatryGerontologyDemographyEnvironmental healthSchizophrenia (object-oriented programming)Disease

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to assess trends in utilization and costs of antipsychotic drugs among a population of older adults over time, with respect to the prevalence of users, shifts in prescribing patterns, and related financial implications. DESIGN: Cross-sectional time series of quarterly and annual antipsychotic utilization and cost were obtained from administrative databases for calendar years 1993 through 2002. SETTING AND PARTICIPANTS: A population-based study of more than 1.4 million residents of the province of Ontario aged 65 years or older. MEASUREMENTS: Data sources used included the Ontario Drug Benefits (ODB) database and Statistics Canada census data. RESULTS: The prevalence of antipsychotic users increased by 34.8% over the study period from 2.2% at the beginning of 1993 to 3.0% of the elderly at the end of 2002 (p < 0.01). This was associated with a 749% increase in total cost (from $3.7 million in 1993 to $31.4 million in 2002; p < 0.01). The atypical antipsychotics, which were not available in 1993, made up 82.5% of the antipsychotics dispensed and 95.2% of costs in 2002. CONCLUSIONS: The modest increase in antipsychotic prevalence in the elderly over the last ten years has been associated with a substantial increase in cost, with a significant shift towards use of the atypical antipsychotics. As the atypical antipsychotics are increasingly used for patients with dementia, which is becoming more prevalent in the aging population, an understanding of the benefits of these medications must be balanced with a detailed understanding of the material and financial implications.

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 score0.310
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.019
GPT teacher head0.323
Teacher spread0.304 · 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

Citations75
Published2005
Admission routes2
Has abstractyes

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