Electronic Documentation of Goals of Care Designation Discussions Among Alberta-based Geriatric Patients
Bibliographic record
Abstract
Background: Goals of Care Designations are important medical orders that are used to determine the appropriate level of medical intervention for individuals in the event of life limiting illness. Canada has an aging population and individuals are living with higher levels of chronic illness and comorbidity. As patient autonomy increases, it has become increasingly important to have accurate and up-to-date documentation of a patient's medical wishes for life sustaining care. Methods: This was a retrospective chart review of 400 randomly selected patients 65 years of age and over, seen at the University of Alberta Hospital outpatient clinic for Comprehensive Geriatric Assessment from July 1, 2022 to June 30, 2023. We extracted the frequency of Goals of Care Designation (GCD) documentation determined by historical data available within selected patient charts, the setting of each discussion, and the specialty of each provider completing Goals of Care documentation. Results: Only 49.3% (197/400) of patients had any documented GCD entered on their electronic medical record (EMR). Of the 356 completed GCD forms, 267 (75%) were completed in an inpatient setting; the majority of GCD forms were completed by a specialist in Internal Medicine (39.89%, n=142) or Family Medicine (37.64%, n=134). Conclusions: Our study revealed that less than half of patients had any GCD documentation in the provincial EMR. As accurate Goals of Care documentation is vital to patient care and autonomy, every opportunity should be taken by health-care professionals to complete this essential documentation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".