A Qualitative Study on the Effects of the COVID-19 Pandemic on Solid Organ Transplantation
Bibliographic record
Abstract
Introduction: Solid organ transplantation is a lifesaving intervention requiring extensive coordination and communication for timely and safe care. The COVID-19 pandemic posed unique challenges to the safety and management of solid organ transplantation. This descriptive qualitative study aimed to understand how hospital stakeholders were affected by and responded to the COVID-19 pandemic to contribute toward improved healthcare delivery responses and strategies during times of systemic strain on the healthcare system. Methods: One-hour-long semistructured interviews were performed in 3 cohorts: healthcare professionals (N = 6), administrative staff (N = 6), and recipients (N = 4). Interviews were analyzed using conventional thematic content analysis. Thematic saturation was reached within each cohort. Findings: Twelve codes and 6 major themes were identified including the Impact on Clinical Practice, Virtual Healthcare Delivery, Communication, Research, Education and Training, Mental Health and Future Pandemic Planning. Reflecting on these codes and major themes, 4 recommendations were developed (Anticipation and Preparation, Maximizing Existing Resources and Networks, Standardization and the Virtual Environment and Caring for the Staff) to guide transplant programs to optimize healthcare pathways while enhancing the best practices during future pandemics. Conclusion: Transplant programs will benefit from anticipation and preparation procedures using ramping-down strategies, resource planning, and interprofessional collaboration while maximizing existing resources and networks. In parallel, transplant programs should standardize virtual practices and platforms for clinical and educational purposes while maintaining an open culture of mental health discussion and integrating strategies to support staff’s mental health.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".