Content of Serious Illness Care conversation documentation is associated with goals of care orders—a quantitative evaluation in hospital
Bibliographic record
Abstract
BACKGROUND: The Serious Illness Care Program (SICP) increases quality of documentation about patients' values and priorities, but it is not known whether patient characteristics and goals of care are associated with the elements documented. The purpose of this study was to explore for associations between the quantity and type of elements documented after SICP conversations with patient characteristics and goals of care order. METHODS: Documentation of SICP conversations by internal medicine physicians with hospitalized patients was evaluated in a retrospective chart review between March 2018 to December 2019. The conversations occurred after SICP implementation in a Tertiary Hospital, Medical teaching unit which uses "Goals of Care Designation" (GCD) medical orders to communicate a patient's general intent, specific interventions, and preferred locations of care. A validated SICP codebook was used to determine the frequency of conversation elements documented for (1) Goals and Values; (2) Prognosis/illness understanding; (3) End-of-life care planning and (4) GCD/Life-sustaining treatment preferences. Univariate and multivariate generalized linear models were used to analyze associations between quantity of elements documented and patient characteristics (age, gender, frailty, language spoken and GCD). RESULTS: Of 175 SICP conversations documented, in the univariate analysis more goals and values were documented for patients who understand/speak English (0.89; 95% CI: 0.14 - 1.63) and more content was recorded for patients with a non-resuscitative GCD focus ("Medical": 2.42; 95% CI: 1.51 - 3.33; "Comfort": 1.06; 95% CI: 0.24 - 1.88) although not in all domains. In the multivariate analysis, controlling for age, gender, language and frailty, the association between content scores and GCD remained highly significant. Patients with a non-resuscitative GCD had higher total domain scores than those with a resuscitative GCD ("Medical": 1.27 95% CI: 0.42-2.13; "Comfort": 2.67, 95% CI:1.71-3.62). CONCLUSION: The type of content documented by physicians after a SICP conversation is associated with the patient's goals of care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".