GRP-147 Pre-Post Study of Interruptions in a Pharmacy Department
Bibliographic record
Abstract
Background Interruptions are a major concern in hospital pharmacy settings, given the nature and the requirements of the work such as sustained focused attention, validating prescriptions and performing complex processes. Interruptions may jeopardise the safe delivery of pharmaceutical services. Purpose The primary objective was to compare the number of stimuli per hour received and made by pharmacists and pharmacy technicians between 2010 and 2012. The secondary objective was to evaluate the impact of five corrective measures. Materials and Methods This was a pre-post cross-sectional observational study. The study was conducted in the main dispensing area of the pharmacy department of a University Hospital Center. The area is composed of three data entry stations each assigned one pharmacist and one pharmacy technician. Stimuli received and made by pharmacists and pharmacy technicians were counted before (2010) and after (2012) the implementation of corrective measures. The effect of five corrective measures was measured with a t-test for targeted stimuli. Results Sixty-two random 30-minute observation periods in 2010 (n = 2,663 stimuli) and 31 periods in 2012 (n = 1,217 stimuli) were conducted. An average rate of 85.9 ± 22.2 stimuli per hour was calculated in 2010 vs. 78.52 ± 20.1 in 2012 (P = 0.06). We observed a statistically significant decrease in the mean rate of stimuli per hour for three types of stimulus for pharmacists (i.e. printer noise 3.7 ± 2.4 vs. 0.6 ± 1.8 p < 0.001, face-to-face non-professional conversations 4.4 ± 4.2 vs. 1.2 ± 1.8 p = 0.003, Web browsing 1.3 ± 2.2 vs. 0 ± 0 p = 0.009) and for one type of stimuli for pharmacy technicians (i.e. printer noise 4.7 ± 3.2 vs. 0.75 ± 1.8 p < 0.001). Conclusions Despite the corrective measures, there was no statistically significant difference between the rates of stimuli per hour observed in 2010 and 2012. Other studies are needed to identify more efficient corrective measures and to better describe the nature and the impact of stimuli, distractions and interruptions in pharmacy practise. No conflict of interest.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".