Failures in communication through documents and documentation across the perioperative pathway
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To explore how communication failures occur in documents and documentations across the perioperative pathway in nurses' interactions with other nurses, surgeons and anaesthetists. BACKGROUND: Documents and documentation are used to communicate vital patient and procedural information among nurses, and in nurses' interactions with surgeons and anaesthetists, across the perioperative pathway. Previous research indicates that communication failure regularly occurs in the perioperative setting. DESIGN: A qualitative study was undertaken. METHODS: The study was conducted over three hospitals in Melbourne, Australia. One hundred and twenty-five healthcare professionals from the disciplines of surgery, anaesthesia and nursing participated in the study. Data collection commenced in January 2010 and concluded in October 2010. Data were generated through 350 hours of observation, two focus groups and 20 semi-structured interviews. A detailed thematic analysis was undertaken. RESULTS: Communication failure occurred owing to a reliance on documents and documentation to transfer information at patient transition points, poor quality documents and documentation, and problematic access to information. Institutional ruling practices of professional practice, efficiency and productivity, and fiscal constraint dominated the coordination of nurses', surgeons' and anaesthetists' communication through documents and documentation. These governing practices configured communication to be incongruous with reliably meeting safety and quality objectives. CONCLUSIONS: Communication failure occurred because important information was sometimes buried in documents, insufficient, inaccurate, out-of-date or not verbally reinforced. Furthermore, busy nurses were not always able to access information they required in a timely manner. Patient safety was affected, which led to delays in treatment and at times inadequate care. RELEVANCE TO CLINICAL PRACTICE: Organisational support needs to be provided to nurses, surgeons and anaesthetists so they have sufficient time to complete, locate, and read documents and documentation. Infrastructure supporting communication technologies should be implemented to enable the rapid retrieval, entry, and dispersion of information.
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 | 0.034 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".