Patients with COVID‐19 share their experiences of recovering at home following hospital care transitions and discharge preparation
Bibliographic record
Abstract
INTRODUCTION: Patients discharged following hospitalization for COVID-19 require clear discharge protocols, information resources and communications to adequately prepare them to safely and successfully transition from hospital to home. Our study focuses on the patients' transition to recovering at home including their hospital discharge preparation and hospital experiences. METHODS: A qualitative descriptive study design involved interviewing patients who had been hospitalized for COVID-19 in one urban Alberta, Canada centre. Purposive sampling was used to select patients from a centralized COVID-19 hospital patient database stratified by month between March 2020 and February 2021. Other inclusion criteria (e.g., sex and age) were also considered. Semi-structured interviews with patients were recorded, transcribed and analysed using thematic analysis. Data sufficiency and saturation were determined. RESULTS: Twelve patients shared their lived experiences and recovery journey from COVID-19. Themes were reported under three main areas as framed by the study aim-the current status of patients recovering at home, including the supports they used to manage; their discharge process and preparation to go home; and their various hospital-related experiences. Suggestions for improving aspects of the patient journey were also captured. CONCLUSION: Findings provided details of the needs, information gaps and what matters most to patients when they are recovering from COVID-19 at home, including their preparation to safely and successfully transition from hospital to home (i.e., feeling well prepared to go home, including being adequately assessed and having clear discharge protocols and communication). Key learnings were applied to improve or develop patient discharge and transition resources. PATIENT OR PUBLIC CONTRIBUTION: A patient/family advisor and patient experience partners were involved throughout the study, codeveloping all aspects, from the study design to the reporting and application of the findings. Leading into the study, patient experiences and feedback regarding the home from hospital recovery journey informed multiple aspects, including the codevelopment of the interview guide.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".