Code Status Documentation Availability and Accuracy Among Emergency Patients with End-stage Disease
Bibliographic record
Abstract
INTRODUCTION: Some patients with end-stage disease who may neither want nor benefit from aggressive resuscitation receive such treatment if they cannot communicate in an emergency. Timely access to patients' current resuscitation wishes, or "code status," should be a key metric of electronic health records (EHR). We sought to determine what percentage of a cohort of patients with end-stage disease who present to the emergency department (ED) have accessible, code status documents, and for those who do, how quickly can this documentation be retrieved. METHODS: In this cross-sectional study of ED patients with end-stage disease (eg, palliative care, metastatic malignancy, home oxygen, dialysis) conducted during purposefully sampled random accrual times we performed a standardized, timed review of available health records, including accompanying transfer documents. We also interviewed consenting patients and substitute decision makers to compare available code status documents to their current wishes. RESULTS: Code status documentation was unavailable within 15 minutes of ED arrival in most cases (54/85, or 63%). Retrieval time was under five minutes in the rest, especially when "one click deep" in the EHR. When interviewed, 20/32 (63%) expressed "do not resuscitate" wishes, 10 of whom had no supporting documentation. Patients from assisted-living (odds ratio [OR] 6.7; 95% confidence interval [CI], 1.7-26) and long-term care facilities (OR 13; 95% CI, 2.5-65) were more likely to have a documented code status available compared to those living in the community. CONCLUSION: The majority of patients with end-stage disease, including half of those who would not wish resuscitation from cardiorespiratory arrest, did not have code status documents readily available upon arrival to our tertiary care ED. Patients living in the community with advanced disease may be at higher risk for unwanted resuscitative efforts should they present to hospital in extremis. While easily retrievable code status documentation within the EHR shows promise, its accuracy and validity remain important considerations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.006 | 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".