Goals of care discussions among hospitalized long‐term care residents: Predictors and associated outcomes of care
Bibliographic record
Abstract
INTRODUCTION: There are limited data on the occurrence, predictors, and impact of goals of care (GOC) discussions during hospitalization for seriously ill elderly patients, particularly for long-term care (LTC) residents. METHODS: The study was a retrospective chart review of 200 randomly sampled LTC residents hospitalized via the emergency department and admitted to the general internal medicine service of 2 Canadian academic hospitals, from January 2012 through December 2012. We applied logistic regression models to identify factors associated with, and outcomes of, these discussions. RESULTS: Overall, 9.4% (665 of 7084) of hospitalizations were patients from LTC. In the sample of 200 patients, 37.5% had a documented discussion. No baseline patient characteristic was associated with GOC discussions. Low Glasgow Coma Scale, high respiratory rate, and low oxygen saturation were associated with discussions. Patients with discussions had higher rates of orders for no resuscitation (80% vs 55%) and orders for comfort measures only (7% vs 0%). In adjusted analyses, patients with discussions had higher odds of in-hospital death (52.0, 95% confidence interval [CI]: 6.2-440.4) and 1-year mortality (4.1, 95% CI: 1.7-9.6). Nearly 75% of patients with a change in their GOC did not have this documented in the discharge summary. CONCLUSION: In hospitalized LTC patients, GOC discussions occurred infrequently and appeared to be triggered by illness severity. Orders for advance directives, in-hospital death, and 1-year mortality were associated with discussions. Rates of GOC documentation in the discharge summary were poor. This study provides direction for developing education and practice standards to improve GOC discussion rates and their communication back to LTC. Journal of Hospital Medicine 2015;11:824-831. © 2015 Society of Hospital Medicine.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".