Advance care planning after hospital discharge: qualitative analysis of facilitators and barriers from patient interviews
Bibliographic record
Abstract
BACKGROUND: Patients who engage in Advance Care Planning (ACP) are more likely to get care consistent with their values. We sought to determine the barriers and facilitators to ACP engagement after discharge from hospital. METHODS: Prior to discharge from hospital eligible patients received a standardized conversation about prognosis and ACP. Each patient was given an ACP workbook and asked to complete it over the following four weeks. We included frail elderly patients with a high risk of death admitted to general internal medicine wards at a tertiary care academic teaching hospital. Four weeks after discharge we conducted semi-structured interviews with patients. Interviews were transcribed, coded and analysed with thematic analysis. Themes were categorized according to the theoretical domains framework. RESULTS: We performed 17 interviews. All Theoretical Domain Framework components except for Social/Professional Identity and Behavioral Regulation were identified in our data. Poor knowledge about ACP and physician communication skills were barriers partially addressed by our intervention. Some patients found it difficult to discuss ACP during an acute illness. For others acute illness made ACP discussions more relevant. Uncertainty about future health motivated some participants to engage in ACP while others found that ACP discussions prevented them from living in the moment and stripped them of hope that better days were ahead. CONCLUSIONS: For some patients acute illness resulting in admission to hospital can be an opportunity to engage in ACP conversations but for others ACP discussions are antithetical to the goals of hospital care.
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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 | 0.021 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".