Improving hospital-based communication and decision-making about scope of treatment using a standard documentation tool
Bibliographic record
Abstract
Background: The Vancouver Island Health Authority (VIHA) implemented a standard advance care planning (ACP) document called the medical order for scope of treatment (MOST) in February 2016 to improve end of life communication and documentation. This study aims to see if the MOST implementation improves inpatient ACP documentation when compared with the 'do not resuscitate' (DNR) order. Improvement is measured by: (1) proportion of inpatients with documented orders for life-sustaining treatment, (2) discordance between patient's expressed wishes and chart documentation, (3) patient satisfaction and (4) days admitted to an acute care hospital within 90 days of study inclusion. Methods: We performed a single-centre quality improvement study tracking the effects of MOST implementation. 329 consecutive patients were enrolled at a 215-bed community hospital located in Comox, British Columbia, Canada. Results: The MOST integrated well into the process of care, significantly improving ACP documentation from 33% preimplementation to 100% over 8 months of implementation. MOST completion was associated with a significant decrease in discordance between patients' wishes and documented goals of care. Patients with a MOST were significantly older and had a higher charlson comorbidity score than those without a MOST. Despite this, there was no difference in the number of days study patients were admitted to hospital within 90 days of study inclusion. Conclusions: MOST implementation improves the frequency and quality of inpatient ACP documentation with no effect on acute care utilisation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".