Patient Care Planning Discussions for Patients at the End of Life: An Evidence-Based Analysis.
Bibliographic record
Abstract
BACKGROUND: Ontario spends about 9% of its health budget on care for people at the end of life (EoL), most of whom die from chronic, prolonged conditions. For many people, patient care planning discussions (PCPDs) can improve the quality and reduce the cost of care. OBJECTIVES: This evidence-based analysis aimed to examine the effectiveness of PCPDs in achieving better patient-centred outcomes for people at the EoL. DATA SOURCES: A systematic literature search was conducted in MEDLINE, Embase, CINAHL, and EBM Reviews to identify relevant literature published between January 1, 2004, and October 9, 2013. REVIEW METHODS: Peer-reviewed reports from randomized controlled trials (RCTs) and observational studies were examined. Outcomes included quality of life (QoL), satisfaction, concordance, advance care planning (ACP), and health care use. Quality of evidence was assessed using GRADE. RESULTS: While the effects of PCPDs on QoL are unclear, single-provider PCPDs were associated with family members being very satisfied with EoL care (odds ratio [OR]: 5.17 [95% CI: 1.52, 17.58]), improved concordance between patients' and families' wishes (OR: 4.32, P < 0.001), fewer episodes of hospital care (mean difference [MD]: -0.21, P = 0.04), spending fewer days in hospital (MD: -1.8, P = 0.03), and receiving hospice care (OR: 5.17 [95% CI: 2.03, 13.17]). Team-based PCPDs were associated with greater patient satisfaction (standardized mean difference [SMD]: 0.39 [95% CI: 0.17, 0.60]) and fewer outpatient visits (MD: -5.20 [95% CI: -9.70, -0.70]). Overall, PCPDs were associated with more ACP and more optimal health care use. LIMITATIONS: Most of the RCTs were unblinded, intervention was measured or described inadequately in some studies, and the term "usual care" was often undefined. CONCLUSIONS: Patients at the EoL and their families benefited from PCPDs. Furthermore, PCPDs occurring earlier in the course of illness were associated with better outcomes than those occurring later.
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 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 | 0.018 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".