Promoting Positive Change with Blood Glucose Entry Error and Documentation in Acute Care
Bibliographic record
Abstract
In the clinical setting of NURS 479 leadership, the issue of incorrect blood glucose entry error and documentation arose as a challenge in regards to safe patient care in the nursing environment. Patient care had the potential to be affected in adverse ways. Risks of differing patient care plans, and the concept of unequal health equity came to be possible scenarios due to these errors. Stakeholders, and structural and human factors all played a part in the circumstances present, and from there, it was questioned what could be done to positively adjust this issue. Posters were created to be put in place within various locations of the clinical setting, striving to educate stakeholders, (nurses, physicians, management) and maintain the overall goal of decreasing blood glucose entry error and documentation. Three weeks following the poster implementation, the results revealed that there was a 3-5% decrease in cases of error. Therefore, the established intervention did create a positive change, by reducing the numbers of data entry error and documentation: overall patient management, care, and safety were improved. Going forward, it is important to keep in mind what actions do create meaningful change in the clinical setting, and what steps one can take as a nursing student when seeking to establish positive change. When concluding this project, the ability to be equipped with original information and education moving forward into future nursing practice was recognized. This presentation will overview the steps taken, outcomes determined, and evaluation of a NURS 479 Nursing Practice/Professional Roles project. Department: Nursing Faculty Mentor: Tanya Paananen
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 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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".