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Record W6977430704 · doi:10.6084/m9.figshare.c.4221191

The OptimaMed intervention to reduce inappropriate medications in nursing home residents with severe dementia: results from a quasi-experimental feasibility pilot study

2018· other· en· W6977430704 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2018
Typeother
Languageen
FieldComputer Science
TopicChaos-based Image/Signal Encryption
Canadian institutionsnot available
Fundersnot available
KeywordsIntervention (counseling)DementiaSession (web analytics)Nursing homesAdverse effectMEDLINEPharmacistChecklist

Abstract

fetched live from OpenAlex

Abstract Background Medication regimens in nursing home (NH) residents with severe dementia should be frequently reviewed to avoid inappropriate medication, overtreatment and adverse drug events, within a comfort care approach. This study aimed at testing the feasibility of an interdisciplinary knowledge exchange (KE) intervention using a medication review guidance tool categorizing medications as either “generally”, “sometimes” or “exceptionally” appropriate for NH residents with severe dementia. Methods A quasi-experimental feasibility pilot study with 44 participating residents aged 65 years or over with severe dementia was carried out in three NH in Quebec City, Canada. The intervention comprised an information leaflet for residents’ families, a 90-min KE session for NH general practitioners (GP), pharmacists and nurses focusing on the medication review guidance tool, a medication review by the pharmacists for participating residents with ensuing team discussion on medication changes, and a post-intervention KE session to obtain feedback from team staff. Medication regimens and levels of pain and of agitation of the participants were evaluated at baseline and at 4 months post-intervention. A questionnaire for team staff explored perceived barriers and facilitators. Statistical differences in measures comparing pre and post-intervention were assessed using paired t-tests and Cochran’s-Q tests. Results The KE sessions reached 34 NH team staff (5 GP, 4 pharmacists, 6 heads of care unit and 19 staff nurses). Forty-four residents participated in the study and were followed for a mean of 104 days. The total number of regular medications was 372 pre and 327 post-intervention. The mean number of regular medications per resident was 7.86 pre and 6.81 post-intervention. The odds ratios estimating the risks of using any regular medication or a “sometimes appropriate” medication post-intervention were 0.81 (95% CI: 0.71–0.92) and 0.83 (95% CI: 0.74–0.94), respectively. Conclusion A simple KE intervention using a medication review guidance tool categorizing medications as being either “generally”, “sometimes” or “exceptionally” appropriate in severe dementia was well received and accompanied by an overall reduction in medication use by NH residents with severe dementia. Levels of agitation were unaffected and there was no clinically significant changes in levels of pain. Staff feedback provided opportunities to improve the intervention.

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)0.006
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.333
Teacher spread0.290 · 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 designNon-randomized trial
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

Citations0
Published2018
Admission routes1
Has abstractyes

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