“To err is human”, to recover is a must. Residents and Fellows’ perception on error recovery training in surgical specialties
Bibliographic record
Abstract
BACKGROUND: Medical error is the third leading cause of death in the United States of America. Particularly in the context of surgery, error is a complex matter, in part due to the variety of contributing factors, and the diversity of potential outcomes. To date, emphasis has been placed on strategies for error prevention, however, total error eradication remains an unrealistic target. “To err is human,” and errors can be committed by anyone - trainees and experienced faculty. In the context of surgery, technical errors do occur in the operating room (OR), and these errors must be appropriately recognized and managed to ensure patient safety. Hence, attention should focus not only on decreasing error incidence but also on teaching and learning how to best manage and recover from the inevitable occurrence of errors within a given surgery. Error recovery is an essential skill to attaining surgical competency that may be underrepresented, may not be explicitly taught, and may not be appropriately assessed during surgical training.OBJECTIVE: The objective of this thesis was to explore surgical trainees’ experiences and perceptions of error recovery in surgical procedures. To better understand trainees’ perspectives, two descriptive studies were conducted; one relying on survey methodology, and one relying on semi-structured interviews.METHOD: For the first study, an online survey was sent to surgical trainees in the United States and Canada. It was composed of Likert-scale items, yes/no questions, and open-ended questions. For the second study, semi-structured interviews. Purposive and snowball samplings were used to recruit residents and fellows differing in postgraduate-level and surgical specialty. Interviews were transcribed and a qualitative descriptive approach was used for analysis and data was coded inductively. RESULTS: 206 surveys were completed. Overall, 99% (n=203) agreed or strongly agreed that error recovery is an important competency for future practice. While 83% (n=170) feel confident recovering from “minor” errors, only 34% (n=68) feel confident that they could recover from “major” errors that are likely to have serious consequences on patient safety. Overall, residents do not consider that they have adequate training in error recovery, with only 37% (n=72) felt they were adequately trained to recover from major errors. It was also mentioned “The quality of learning regarding error recovery depends entirely on the attending.” A total of 15 residents and fellows were interviewed. When exploring the importance of error recovery for the trainees, competency and safety emerged as main themes, with error recovery being considered as an indicator of overall surgical competency. Factors that influence error recovery training in the OR were grouped under four major themes: supervision, self, surgical context, and situation safeness. Most of the factors were related to "supervision" in the OR – in other words, the attending appears to be one of the determining factors in whether or not a trainee receives error recovery training. Factors related to the "self" reflected residents' feelings and competencies. "Surgical context" embedded factors related to the procedure and its technical challenge related to the patient’s comorbidity. “Situation safeness” was identified as a transversal theme, describing factors balancing between the patient safety and the learning benefits of error recovery training. CONCLUSION: Error recovery is a skill that is valued by surgical trainees. Participants report they are not receiving adequate training opportunities to learn how to recover from technical errors in the OR. Opportunities are variable, informal, and attending-dependent. Focusing on how to maximize the opportunities for learning by attending to factors related to “supervision”, “self”, “surgical context” and the “situation safeness”, could provide suggestions for improving learning contexts to support error recovery learning
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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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".