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Record W2547338558 · doi:10.1111/inm.12265

Descriptive analysis of pro re nata medication use at a Canadian psychiatric hospital

2016· article· en· W2547338558 on OpenAlexaffabout
Krystle Martin, Vinita Arora, Ilan Fischler, Renee Tremblay

Bibliographic record

VenueInternational Journal of Mental Health Nursing · 2016
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsOntario Shores Centre for Mental Health Sciences
Fundersnot available
KeywordsPro re nataPolypharmacyMedicinePsychiatryDocumentationFamily medicineIntensive care medicine

Abstract

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Pro re nata (PRN), a Latin phrase meaning 'as needed', is used to describe medications that might be used in specific situations, in addition to regularly-scheduled medications, such as when a patient is particularly anxious, experiencing insomnia, or suffering pain. While helpful in some circumstances, PRN are associated with an increased risk of morbidity, overuse, dependence, and polypharmacy. There is also a dearth of medical literature describing current practices and trends of PRN administration in mental health facilities, especially in Canada, and the literature that does exist is limited by poor documentation practices. Therefore, the primary objective of the current study was to understand the reason (purpose), frequency, use, documentation practices, and outcome (i.e. effectiveness, side-effects) of PRN medication use on inpatient units. Data were pulled to capture a snapshot of PRN administrations over a 3-month period, and included information related to the administration of the PRN medication, such as time of administration, type and dose of PRN medication, and prescribed indication, as well as patient-specific information. Results indicated that approximately 8200 psychotropic PRN medications were administered during the designated 3-month time period, and over 90% of patients received at least one PRN. Most of these were benzodiazepines, followed by antipsychotics. Further analyses were conducted to determine other characteristics of PRN use patterns and to provide a baseline of understanding that will inform future research to investigate the practice of PRN administration to psychiatric inpatients.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score0.993

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 head0.050
GPT teacher head0.426
Teacher spread0.376 · 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

Citations31
Published2016
Admission routes2
Has abstractyes

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