Exploring approaches to patient safety: the case of spinal manipulation therapy
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to gain insight into the current safety culture around the use of spinal manipulation therapy (SMT) by regulated health professionals in Canada and to explore perceptions of readiness for implementing formal mechanisms for tracking associated adverse events. METHODS: Fifty-six semi-structured telephone interviews were conducted with professional leaders and frontline practitioners in chiropractic, physiotherapy, naturopathy and medicine, all professions regulated to perform SMT in the provinces of Alberta and Ontario Canada. Interviews were digitally audio-recorded for verbatim transcription. Transcripts were entered into HyperResearch software for qualitative data analysis and were coded for both anticipated and emergent themes using the constant comparative method. A thematic, descriptive analysis was produced. RESULTS: The safety culture around SMT is characterized by substantial disagreement about its actual rather than putative risks. Competing intra- and inter-professional narratives further cloud the safety picture. Participants felt that safety talk is sometimes conflated with competition for business in the context of fee-for-service healthcare delivery by several professions with overlapping scopes of practice. Both professional leaders and frontline practitioners perceived multiple barriers to the implementation of an incident reporting system for SMT. CONCLUSIONS: The established 'measure and manage' approach to patient safety is difficult to apply to care which is geographically dispersed and delivered by practitioners in multiple professions with overlapping scopes of practice, primarily in a fee-for-service model. Collaboration across professions on models that allow practitioners to share information anonymously and help practitioners learn from the reported incidents is needed.
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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 | 0.029 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.034 | 0.045 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.005 | 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".