POLST forms within an acute care setting
Bibliographic record
Abstract
There are only a limited number of studies on the content and completion of Physician Orders for Life Sustaining Treatment (POLST) forms. No study has specifically examined the use of POLST forms within an acute hospital setting. We audited 1096 randomly selected Resuscitation Plans, a locally developed form of POLST, completed in a university hospital during 2011. Matching patient identification numbers resulted in 789 individual patients (49.7% Male; 64% aged 75+), of whom 187 had multiple plans during the audit period. The most recent plan for each patient was examined for content. Plans were most commonly completed by Registrars (539, 68.3%), and 99.7% of plans were signed. The majority of plans indicated orders for treatment limitation (608, 77.1%), and these patients were significantly older than patients with an order for full treatment (p=.001). Information on the decision making process was completed in 540 cases (68.4%). Of these, 63% had evidence that the patient/family had been involved in, or were informed of the decision. There was a significant association between limitation of treatment and evidence of family/patient involvement in the decision making process (p=.001). Forty-nine percent of patients with multiple plans had orders in the most recent plan for less-aggressive treatment, compared to the prior plan. A further 44% had no changes to treatment orders over consecutive plans. The use of POLST forms in an acute care environment is dynamic and complex. Evidence of patient/family involvement in the decision making process should increase as local advance care planning programs progress.
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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 | 0.012 | 0.094 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".