Patient experiences using a novel tool to improve care transitions in patients with heart failure: a qualitative analysis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the utility of a novel discharge tool adapted for heart failure (HF) on patient experience. DESIGN: Semistructured interviews assessed the utility of a novel discharge tool adapted for HF; patient-oriented discharge summary (PODS-HF) at 72 hours and 30 days after leaving hospital. Interviews were recorded and transcribed verbatim. Three investigators used directed content analysis to determine themes and subthemes from the narrative data. SETTING: The cardiology ward of an urban academic institution in Canada. PARTICIPANTS: 13 patients and caregivers completed 24 interviews. Eligible patients were >18 years and admitted with a diagnosis of HF. RESULTS: Analysis revealed six interconnected themes: (1) Utility of discharge instructions: how patients perceive and use written and verbal instructions. Patients receiving PODS-HF identified value in the patient-centred summarised content. (2) Adherence: strategies used by patients to enhance adherence to medications, diet and lifestyle changes. PODS-HF provides a strong visual reminder, particularly early postdischarge. (3) Adaptation: how patients incorporate changes into 'new norms'. This was more evident by 30 days, and those using PODS-HF had less unscheduled visits and readmissions. (4) Relationships with healthcare providers: patients' perceptions of the roles of family physicians and specialists in follow-up care. (5) Role of family and caregivers: the pivotal role of caregivers in supporting adherence and adaptation. (6) Follow-up phone calls: the utility of follow-up calls, particularly early after discharge as a means of providing clarification, reassurance and education. CONCLUSION: PODS-HF is a useful tool that increases patients' confidence to self-manage and facilitates adherence by providing relevant written information to reference after discharge.
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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 | 0.016 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".