Bringing a Systems Approach to Living Donor Kidney Transplantation
Bibliographic record
Abstract
Introduction: Living donor kidney transplantation (LDKT) is the best treatment option for patients with kidney failure. Efforts to increase LDKT have focused on microlevel interventions and the need for systems thinking has been highlighted. We aimed to identify and compare health system-level attributes and processes that are facilitators and barriers to LDKT. Methods: = 5 with 40 participants), analyzed using inductive thematic analysis. Results: Our findings showed a strong relationship between the degree of centralized coordination between governing organizations and the capacity to deliver LDKT as follows. (i) macro-level coordination between governing organizations in British Columbia and Ontario increased capacities, whereas Québec was seen as decentralized with little formal coordination; (ii) a higher degree of centralized coordination facilitated more effective resource deployment in the form of human resources and initiatives in British Columbia and Ontario, whereas in Québec resource deployment relied on hospital budgets leading to competition for resources and reduced capacity of initiatives; (iii) informal resource sharing through strong communities of practice and local champions facilitated LDKT in Ontario and British Columbia and was limited in Québec. Conclusion: Our findings suggest that interventions that account for full-system function, particularly macro-level coordination between governing organizations can improve LDKT delivery. Findings may be used to guide structured organizational change toward increasing LDKT and mitigating the global burden of kidney failure.
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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 | 0.000 |
| 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".