The Effects of Implementing a Home Dialysis Project ECHO
Bibliographic record
Abstract
Background: Insufficient home dialysis education and mentorship are suggested barriers contributing to the under utilization of home therapies in the U.S. The National Kidney Foundation KDOQI Home Dialysis task force hypothesized that the use of a Project ECHO (Extension for Community Healthcare Outcome) program may enhance home dialysis uptake. Methods: In partnership with Comagine Health, the NKF home dialysis ECHO project delivered 20 interprofessional education sessions virtually to 108 registrants from 19 dialysis centers derived from 2 ESRD network regions over 1 year. Our home dialysis curriculum has previously been published. Sessions were divided into case discussion and didactic teaching moderated by the home dialysis hub team. Using a mixed method before and after approach, we described the differences in home dialysis rate and knowledge utilization. Results: 108 healthcare workers registered for our home dialysis ECHO project. The median number of participated sessions was 1.5 (range = 16). The registrants represented a diverse background (including: dietitian [n = 15], facility administrator [n = 20], nurse [n=36] and social worker [n=18]). Using exit questionnaires, the registrants consistently recommended ECHO sessions to their peers with the top sessions saturating amongst the themes of “establishing home dialysis culture”, “modality education” and “psychosocial adjustment”. At baseline, the participating centers' median home dialysis rate was 9.28% (0.00 - 18.52%) [25-75%] which increased to 12.8% (0.00 - 24.6%) [Wilcoxon Signed Rank Test, p = 0.004] after the program. Conclusions: We demonstrated that home dialysis ECHO project was a feasible strategy that was associated with a modest increase in home dialysis rates. A prospective examination of national adoption of such a strategy to physicians and dialysis clinic staff is warranted.
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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 | 0.014 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".