Safe chemotherapy: Clinicians driving technology and not the other way around.
Bibliographic record
Abstract
183 Background: Although information technology (IT) has the potential to improve the quality and safety of patient care, introduction into the clinical work flow may create unanticipated consequences. IT solutions such as computerized physician order entry (CPOE) are often designed and executed without end-user involvement. An evidence based guideline for systemic treatment (ST) CPOE was developed. The guideline looks at the features, functionalities and components of a ST CPOE system required to ensure safe and high-quality care. Methods: The guideline was developed by an interdisciplinary panel of physicians, nurses, pharmacists, methodologists, IT specialists, and human factors experts. A systematic review was conducted of the available clinical and technology literature and key informant interviews were conducted. Role-specific CPOE functionalities were process mapped for physicians, nurses and pharmacists. Two expert panels (i.e., clinical and supporting tools) were convened to review the information and provide feedback on guideline content. The guideline was also reviewed externally by content experts from provincial, national and international organizations. Results: The resulting evidence-based guideline focused on two distinct yet interconnected parts: clinical practice (e.g., error prevention, unanticipated consequences, impact on practice, clinical decision support), and technology requirements (e.g., usability features, system integration, effective alerts, audit logs, regimen building). The recommendations also highlight the importance of change management strategies and clinician engagement. Conclusions: This innovative guideline provides an approach to technology evaluation focusing on clinical practice needs driving IT solutions. Future research to help standardize design and usability of such systems is necessary. The non-vendor specific recommendations can be used as the foundation for evaluation of ST CPOE systems to reduce errors, improve safety, and support clinical practice. The application of the recommendations as an assessment of ST CPOE system guideline concordance will also be valuable.
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 | 0.024 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.014 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".