EFFECTS OF IMPLEMENTING STANDARDIZED ORGANIZATIONAL INTERVENTIONS ON DRUG THERAPY MANAGEMENT: A QUASI-EXPERIMENTAL STUDY
Bibliographic record
Abstract
Background. Interruptions occurring during the drug preparation and administration have a documented effect on patients' safety. However, literature has paid little attention to show how the introduction of a set of standardized organizational interventions, based on the combination of the current evidence, could reduce the number of interruptions occurring during drug therapy management. For this reason, this study used the most recent evidence to combine a set of standardized organizational interventions, and it was aimed to assess the effect of those interventions on the number of interruptions occurring during drug therapy management (Hypothesis a) and the overall duration of the therapy administration (Hypothesis b).Methods. A quasi-experimental study was performed, using pre- and a post- organizational implementation data collections in a single Italian center. The data collections were related to the interruptions and 40 shifts were randomly selected for both pre- and post-phase, respectively on December 2016 and February 2017. The standardized organizational interventions were implemented using the current evidence on this topic. Results. The standardized organizational interventions decreased the interruptions in the post-implementation phase, but those had not an effect on the duration of the therapy administration.Conclusions. This study represented an updated evidence, which describes the effect of a standardized and evidence-based set of organisational interventions' implementation on drug therapy management. Our results suggest a number of hints for managers and future researches. Managers should keep into account the usefulness of those interventions, while future researches with experimental designs are needed to provide harder evidence on this topic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".