Observational studyRevista espanola de salud publica2019
[Errors of prescription, transcription and administration according to pharmacological group at hospital].
Observational study in Revista espanola de salud publica, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- [Prescription errors and drug interactions in adults hospitalized in an intensive care unit in Barranquilla (Colombia).]Revista espanola de salud publica · 2023Article
- Prediction of Prednisolone Dose Correction Using Machine Learning.Journal of healthcare informatics research · 2023Article
- Assessing Nursing Students' Self-Perceptions about Safe Medication Management: Design and Validation of a Tool, the NURSPeM.International journal of environmental research and public health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveMost studies of medication errors are focused only on finding global prevalence by patients, by phases or according to a certain group of medication. It's just a partial view of the problem. To analyze and compare the prevalence of errors in prescription, transcription and administration, and their clinical repercussions in different pharmacological groups in a third-level hospital.
methodsProspective inclusion study with direct observation disguised as medication administration and comparison with prescriptions and transcriptions at history clinical. The ME and its clinical effects were classified by expert consensus. We calculated the different error rates and their repercussions with their confidence intervals at 95%. Then we compared using Chi-square tests.
resultsWe studied 5,578 prescribed drugs and we observed the administration of 1,879 doses. A total of 117 different pharmacological groups were found, although 50.1% of the prescriptions belonged to only 9 types. We found heparins had a lower prevalence of errors in prescription and transcription and aspirin also had a lower prevalence of prescription errors. On the opposite side, a greater number of errors were obtained in transcription of Paracetamol, Metamizole and Laxatives and a prevalence of errors in the administration phase superior to rest in Paracetamol and in Proton Pump Inhibitors. The impact of medication error increased as medication process progressed, being similar between groups in prescription. In transcription, Heparins and Corticosteroids presented more serious errors. In administration, medication error are more serious for Diuretics and Statins (p <0.05).
conclusionsDrugs considered potentially dangerous present fewer errors (Heparins, Corticoids), but more serious. Drugs with the highest prevalence of errors were Paracetamol and Inhibitors of proton pump but had a lower impact.
Indexed as
Identifiers
30698165PMC11567653W3021144758What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.