Alignment Between Patient and Provider Perspectives on Hemodialysis Vascular Access Decision-Making: A Qualitative Study
Bibliographic record
Abstract
Background: Recent updates to the KDOQI Clinical Practice Guideline for Vascular Access emphasize attaining the “right access, in the right patient, at the right time, for the right reasons”. Yet, how patients, their caregivers, and healthcare providers integrate medical factors with care preferences in patient-centered vascular access decision making is unknown. We sought to explore the extent to which these diverse perspectives align in hemodialysis vascular access selection. Methods: In this qualitative descriptive study, we purposively sampled patients receiving maintenance hemodialysis via an arteriovenous fistula or catheter, their informal caregivers, and healthcare providers. We conducted semi-structured interviews in person or by telephone with 19 patients, 2 caregivers, and 21 healthcare providers (7 hemodialysis nurses, 6 vascular access nurses, 8 nephrologists). We coded transcripts in duplicate and generated themes through an inductive, content analysis approach. Results: While participants across roles shared perspectives related to vascular access decision making, we identified several areas where views diverged. Participants acknowledged the importance of decisional timing and readiness, the iterative nature of decision making, and a desire for vascular access selection to be a shared decision. Perspectives differed in the following key aspects: 1) priorities for vascular access type - providers' preferences for fistulas and physiological optimization contrasted with patients' focus on quality of life; 2) provider involvement in the decision - patients desired guidance from their trusted providers, whereas care providers tried to avoid unduly influencing the decision; 3) informational needs - tools and resources offered by the care team may not meet patients' need for pragmatic, experiential knowledge about vascular access options. Conclusions: While patients and providers identified common perspectives related to the nature and timing of the vascular access decision, conflicting priorities and preferences may impact the decisional outcome. This study highlights opportunities to address decisional conflicts and enable shared decision making in vascular access selection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.027 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".