The Effects of Objective Structured Clinical Examination on Home Hemodialysis Transition
Bibliographic record
Abstract
Background: Home hemodialysis (HHD) augments quality of life and improves several clinical outcomes in patients with end-stage kidney disease. However, patients are required to learn a complex medical task and are obligated to demonstrate competency of training. We hypothesize that Objective Structured Clinical Examination (OSCE) is a feasible strategy to enhance training and improve patient and provider confidence. Methods: From 2017 to 2021, 58 patients completed HHD training at University Health Network. Each patient completed an OSCE for formative assessment and a final OSCE for summative evaluation. The OSCE comprised of 94 or 85 items, depending on vascular access. Targeted training was provided after the first OSCE on identified areas of improvement. 25 of 58 consented and completed an optional Likert Scale survey (1 to 10) assessing confidence in seven categories, as seen in Figure 1. These include three routine practices of ultrafiltration (UF) target, HHD access, and machine set up followed by three advanced actions of alarm and complication management, and safety. A final item, readiness to go home, served as a global assessment. Patients and training nurses completed the surveys, scoring from 1 to 10, before and after each OSCE. Within subject differences were assessed by paired Student t test.Figure 1.: Patient and nursing reported confidence scores.Results: The mean OSCE score increased from 96.2 (+/- 5.7) after the first OSCE to 98.2 (+/- 3.1) % after the second OSCE (p > 0.05). The patient mean score for home readiness increased from 8.0 (+/- 1.8) after the first OSCE to 9.5 (+/- 1.0) after the final OSCE (p < 0.05). Similar trends were observed from the nurse trainers, with their mean home readiness score increased from 6.6 (+/- 1.8) to 8.9 (+/- 1.1) (p < 0.05) after the OSCE process. Individually, there was an increase in patient confidence in all categories. Confidence in ultrafiltration target, dialysis access, and machine setup improved by 0.68, 0.40, and 0.36 respectively (p < 0.05). Confidence in advanced components including alarm troubleshooting, complication management, and safety increased by 0.84, 1.04, and 0.72 respectively (p < 0.05). Conclusions: We demonstrated that OSCE is an implementable training strategy, which is associated with augmented home readiness and confidence scores in our patients and nurse trainers. We speculate that assurance of training may reduce patient burnout.
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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 | 0.005 | 0.042 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".