Safe and effective person- and family-centered care practices during transitions from hospital to home—A web-based Delphi technique
Bibliographic record
Abstract
BACKGROUND: Research has shown that adverse events during care transitions from hospital to home can have a significant impact on patients' outcomes, leading to readmission, delayed healing or even death. Gaps exist in the ways of monitoring care during transition periods and there is a need to help organizations better implement and monitor safe person-and family-centered care. Value statements are a way to obtain narratives in lay terms about how well care, treatment and support is organized to meet the needs and preferences of patients/families. The purpose of this study was to identify the value statements that are perceived by decision-makers and patients/families to best signify safe person- and family-centered care during transitions from hospital to home. METHODS: Between January and September 2017, a web-based Delphi was used to survey key stakeholders in acute care and home care organizations across Canada. RESULTS: Decision-makers (n = 22) and patients/families (n = 24) from five provinces participated in the Delphi. Following Round 1, 45 perceived value statements were identified. In Round 2, consensus was received on 33/45 (73.3%) by decision-makers, and 30/45 (66.7%) by patients/families. In Round 3, additional value statements reached consensus in the decision-makers' survey (3) and in the patients/families' survey (2). A total of 30 high priority value statements achieved consensus derived from both the decision-makers' and patients/families' perspectives. CONCLUSION: This study was an important first step in identifying key consensus-based priority value statements for monitoring care transitions from the perspective of both decision-makers and patients/families. Future research is needed to test their usability and to determine whether these value statements are actually suggestive of safe person-and family-centered care transition interventions from hospital to home.
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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 | 0.065 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".