Perspectives on Quality of Care in Kidney Transplantation: A Semistructured Interview Study
Bibliographic record
Abstract
BACKGROUND: There is currently no agreement as to what constitutes quality transplant care, and there is a lack of consistency in the approach to assessing transplantation quality. We aimed to ascertain the views of patients, clinicians, and program administrators about quality care for kidney transplant patients. METHODS: Semistructured qualitative interviews were conducted with 20 patients, 17 physicians, and 11 program administrators. Transcripts were analyzed using inductive thematic analysis. RESULTS: We identified 8 themes: access to treatment (standardized transplant referral, lengthy transplant evaluation process, lengthy living donor evaluation); accessibility of services (alternative access options, flexible appointment availability, appropriate amount of follow-up, barriers for accessing care); program resources (comprehensive multidisciplinary care, knowledgeable staff, peer support groups, educational resources, patient navigators/ advocates); communication of information (taking time to answer questions, clear communication about treatment, communication tailored to patients, health promotion and illness prevention); attitude of care providers (positive and supportive attitude, patient centered care); health outcomes (freedom from dialysis, Long-term health, short-term health, fear of infections); patient satisfaction (returning to normal life, patient satisfaction with care); and safety (reducing infection risk, quick response to complications, patient health status on the waitlist). CONCLUSIONS: There is a need to move beyond basic clinical outcomes and focus on increasing ease of access, the patient-provider relationship, and outcomes that are most important to the patients.
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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 | 0.024 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".