Transitional Care Experiences of Patients with Hip Fracture Across Different Health Care Settings
Bibliographic record
Abstract
BACKGROUND: Transitions of care often result in fragmented care, leading to unmet patient needs and poor satisfaction with care, especially in patients with multiple chronic conditions. This project aimed to understand how experiences of patients with hip fracture, caregivers, and healthcare providers differ across different points of transition. METHODS: A secondary analysis of 103 qualitative, semi-structured interviews was conducted using emergent coding techniques, to gain an understanding of how transitional care experiences may differ across varying settings of care. Following the secondary analysis, a focus group interview was conducted to review findings. RESULTS: Seven key themes, each relating to distinct transition points, emerged from the secondary analysis: (1) Multiple providers contributed to patient and caregiver confusion; (2) Family caregivers were not considered important in the patient's care; (3) System-related issues impacted experiences; (4) Patients and caregivers felt uninformed; (5) Transitions increased stress in patients and caregivers; (6) Care was not tailored to patient needs; (7) Providers faced barriers in getting adequate information. The focus group results built upon these themes, adding some additional context to understand the current transitional care landscape. DISCUSSION: In transitions to formal care settings, similarities were related to feeling confused, while in transitions to home, similarities existed in regards to feeling unprepared. These findings support the view that models of integrated care should consider the context to which they are applied.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".