MétaCan
Menu
Back to cohort
Record W2036689596 · doi:10.12927/cjnl.2006.18369

Nurses' Perceptions of Medication Safety and Medication Reconciliation Practices

2006· article· en· W2036689596 on OpenAlexaffvenueabout
Bernadette Chevalier, Neil J. MacKinnon, Ingrid Sketris

Bibliographic record

VenueNursing leadership · 2006
Typearticle
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsCapital District Health Authority
Fundersnot available
KeywordsNursingAdverse effectMedication ReconciliationPatient safetyMedicineHealth carePerceptionMedical emergencyFamily medicineIntensive care medicinePsychologyPharmacistPharmacology

Abstract

fetched live from OpenAlex

Medication reconciliation (MR) involves the accurate transfer of medication information across the continuum of care. The aim of this study was to measure nurses perceptions of patient safety, medication safety and current MR practice at transition points in a patient's hospital stay. Surveys were distributed to 111 nursing staff in three general medicine units at Capital Health District, Nova Scotia, in August 2005. A total of 39 nurses (35% response rate) completed the survey. "Teamwork within units" was the safety culture dimension with the highest positive response (98.1%), while the processes of handoffs and transitions received the lowest positive response (42.8%). Key areas identified for improvement relative to the current level of MR practice include institutional patient safety systems (e.g., low confidence in existing systems and procedures), inconsistent practices (e.g., wide variation in whether community pharmacists are contacted to verify medication profiles), lack of communication (e.g., between healthcare professionals) and staffing resources (e.g., MR is perceived as a very time-consuming process). Addressing these challenges prior to implementing a formalized MR program should help to ensure success of the project. The insights gained through the use of this survey may prove valuable to other Canadian healthcare organizations that are implementing MR services.

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)0.001
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 score0.497
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.285
GPT teacher head0.450
Teacher spread0.165 · 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

Citations16
Published2006
Admission routes3
Has abstractyes

Explore more

Same venueNursing leadershipSame topicPatient Safety and Medication ErrorsFrench-language works237,207