A Qualitative Study of Trainee Experiences with Home Dialysis Education in US Nephrology Fellowship Programs
Bibliographic record
Abstract
Background: Home dialysis has clinical benefits over in-center hemodialysis (HD) yet its use remains low. One barrier is a lack of comfort in clinical management among graduating nephrology fellows. Prior surveys suggest that fellows desire more training in home dialysis, yet little is known about the best approach to systematically enhance training. To identify opportunities to enhance in-person trainee experiences, we sought to better understand current home dialysis training experiences in US nephrology fellowship programs. Methods: Using a qualitative approach, we conducted one-on-one semi structured interviews with nephrology trainees who attended Home Dialysis University (HDU) and the American Society of Nephrology Home Dialysis Virtual Education Program (ASN-HDU). Using a constant comparison approach, we developed and refined a codebook to identify themes describing participant’s interest and exposure to home dialysis during training, and their comfort with managing patients on home dialysis. Results: 10 semi-structured interviews were completed between Dec 2023 – Mar 2024. 5 of 10 participants attended the ASN-HDU program. Participants were from a variety of training programs and locations. We identified 3 main themes: (1) Home dialysis education during training is serendipitous rather than systematically built into existing curriculum. Opportunities to increase exposure to home dialysis exist, but trainees must be internally motivated to seek out these opportunities due to their serendipitous nature. (2) There is limited exposure to outpatient management of PD, resulting in a spectrum of comfort levels, which causes concern as trainees envision transitioning to independent practice. (3) Home HD exposure is sparse leading to an overwhelming lack of comfort. Conclusion: Home dialysis training during nephrology fellowship remains serendipitous, suggesting the need for systematic efforts. There is limited exposure to outpatient PD and home HD resulting in a lack of comfort. Although the American Board of Internal Medicine requires 8 PD clinics to graduate, trainee experiences suggest that fellowship programs may not be able to meet this requirement. The results of our study should inform curriculum changes, while fellowship programs identify new opportunities to enhance trainee comfort in home dialysis. Funding: Other U.S. Government Support
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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.006 |
| 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".