Promoting Safer and More Efficient Medication Administration within the Accident and Emergency Department at Georgetown Public Hospital Corporation
Bibliographic record
Abstract
Objective: The Emergency Department is a complex environment in which healthcare providers are confronted with uncontrolled and unpredictable critical patient workload. This necessitates multitasking, organization, critical thinking and clear communication. Safe practices during dispensing and administration of medications vastly reduces the potential for patient harm and decreases medication errors (Institute for Healthcare Improvement, 2008). 
 Design/Methods: An eight-question survey was developed to determine nurses’ perceptions of the current medication storage system. Participants were asked to identify ways in which this system could be improved and medications organized in a safer, more systematic way. Following initial data collection, all medications were rearranged to improve medication organization and retrieval. The participants were then surveyed following the intervention to ascertain feedback.
 Results: 68% of participants noted that they perceived the current system to be chaotic. When asked if organizational changes might improve patient care delivery and safety, 96% responded in the affirmative. Labeling medication with both generic/ brand names and organizing them by class and alphabetically thereafter were all identified as potential options for reorganization. Following the intervention, a post-survey demonstrated that 100% of respondents remained enthusiastic about the new system approximately 9 months after implementation.
 Conclusions: The previous medication storage system was fractured and chaotic. Systematic organization of medications by name/class improved nurses’ perceptions of medication safety and delivery while inadvertently reducing the waste of expired medications. Greater measures are needed to truly minimize the risk for a medication administration errors including targeted continuing education and implementation of an electronic medication administration system.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".