Investigating physician's perspectives on disclosure of medical errors in The Bahamas
Bibliographic record
Abstract
Background -A better understanding of physicians' perspectives on barriers to reporting medical errors is needed to increase error reporting.This finding is backed by numerous researchers within developed countries who demonstrate that physicians' voices are imperative to understanding medical errors.The subject of medical errors is receiving increasing research attention, but value also exists in understanding the cultural beliefs among doctors that underlie medical errors.Arguably, research on medical errors thrives chiefly in the 'global north' where there exists a strong culture and, therefore, expectation of patient safety and error reporting.This reporting is imperfectly done even in developed countries, and developing countries may lack this cultural focus on error reporting.Since physicians commonly encounter medical errors, there is a need to understand physicians' perspectives on errors in developing countries.The Nassau Institute, a research organization in the developing country of the Bahamas, affirms the need for public concern and inquiry about the culture of medical errors.Effectively addressing the issues of error disclosure and reporting requires preliminary knowledge from Bahamian health professionals closely involved with medical errors.Therefore, this research aims to investigate Caribbean-based physicians' perspectives on disclosure and reporting of medical errors through a case study of physicians in the Bahamas Objective -The objectives of this research were 1) to produce data that can inform the development of an error disclosure policy; 2) to identify reasons why physicians in developing countries like the Bahamas might fail to report or disclose medical errors; and 3) to obtain an understanding of the influence of culture on the error reporting and disclosure practices of physicians in the Bahamas.Methods -This study utilized a qualitative research approach.The research employed phenomenology, a theoretical perspective most often associated with interpretative traditions in qualitative research.The method used was semi-structured interviews .This research also used the qualitative approach of inductive thematic analysis to assess information gleaned from interviews, whereby interesting features or patterns in the interview data were highlighted.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".