The case for routine goals-of-care documentation
Bibliographic record
Abstract
The article by Heyland et al 1 reveals a 37% prevalence of discordance between patient preferences and hospital chart documentation for cardiopulmonary resuscitation (CPR) and other life-sustaining treatments. This high prevalence of discordance represents significant potential for avoidable, preventable harm. These findings demand that effective goals-of-care discussions and documentation should become as routine as eliciting and documenting medication allergies. This study at 16 Canadian hospitals convincingly depicts inadequate documentation of goals of care. The authors calculated error rates using interviews with 500 hospitalised patients and 408 family members of hospitalised patients to learn their goals of care. They compared these goals with the documented goals of care in the patient orders and uncovered a 35% rate of potential overtreatment, defined as the proportion of patients who preferred to forego CPR while the chart lacked corresponding orders. The authors also measured a 2% rate of potential undertreatment, defined as the proportion of patients who preferred CPR while the chart had orders for no CPR. In other words, these patients would be at risk …
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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 | 0.048 | 0.223 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.028 | 0.043 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".