Safety threats and opportunities to improve interfacility care transitions: insights from patients and family members
Bibliographic record
Abstract
AIM: To explore patients' and family members' perspectives on how safety threats are detected and managed across care transitions and strategies that improve care transitions from acute care hospitals to complex continuing care and rehabilitation health care organizations. BACKGROUND: Poorly executed care transitions can result in additional health care spending due to adverse outcomes and delays as patients wait to transfer from acute care to facilities providing different levels of care. Patients and their families play an integral role in ensuring they receive safe care, as they are the one constant in care transitions processes. However, patients' and family members' perspectives on how safety threats are detected and managed across care transitions from health care facility to health care facility remain poorly understood. METHODS: This qualitative study used semistructured interviews with patients (15) and family members (seven) who were transferred from an acute care hospital to a complex continuing care/rehabilitation care facility. Data were analyzed using a directed content analytical approach. RESULTS: OUR RESULTS REVEALED THREE KEY OVERARCHING THEMES IN THE PERCEPTIONS: lacking information, getting "funneled through" too soon, and difficulty adjusting to the shift from total care to almost self-care. Several patients and families described their expectations and experiences associated with their interfacility care transitions as being uninformed about their transfer or that transfer happened too early. In addition, study participants identified the need for having a coordinated approach to care transitions that engages patients and family members. CONCLUSION: Study findings provide patients' and family members' perspectives on key safety threats and how to improve care transitions. Of particular importance is the need for patients and family members to play a more active role in their care transition planning and self-care management.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".