An Environmental Scan and Evaluation of Home Dialysis Quality Indicators Currently Used in Canada
Bibliographic record
Abstract
BACKGROUND: Quality indicators are important tools to measure and ultimately improve the quality of care provided. Performance measurement may be particularly helpful to grow disciplines that are underutilized and cost-effective, such as home dialysis (peritoneal dialysis and home hemodialysis). OBJECTIVE: To identify and catalog home dialysis quality indicators currently used in Canada, as well as to evaluate these indicators as a starting point for future collaboration and standardization of quality indicators across Canada. DESIGN: An environmental scan of quality indicators from provincial organizations, quality organizations, and stakeholders. SETTING: Sixteen-member pan-Canadian panel with expertise in both nephrology and quality improvement. PATIENTS: Our environmental scan included indicators relevant to patients on home dialysis. MEASUREMENTS: We classified existing indicators based on the Institute of Medicine (IOM) and Donabedian frameworks. METHODS: To evaluate the indicators, a 6-person subcommittee conducted a modified version of the Delphi consensus technique based on the American College of Physicians/Agency for Healthcare Research and Quality criteria. We shared these consensus ratings with the entire 16-member panel for further examination. We rated items from 1 to 9 on 6 domains (1-3 does not meet criteria to 7-9 meets criteria) as well as a global final rating (1-3 unnecessary to 7-9 necessary) to distinguish high-quality from low-quality indicators. RESULTS: Overall, we identified 40 quality indicators across 7 provinces, with 22 (55%) rated as "necessary" to distinguish high quality from poor quality care. Ten indicators were measured by more than 1 province, and 5 of these indicators were rated as necessary (home dialysis prevalence, home dialysis incidence, anemia target achievement, rates of peritonitis associated with peritoneal dialysis, and home dialysis attrition). None of these indicators captured the IOM domains of timely, patient-centered, or equitable care. LIMITATIONS: The environmental scan is a nonexhaustive list of quality indicators in Canada. The panel also lacked representation from patients, administrators, and allied health professionals. CONCLUSIONS: These results provide Canadian home dialysis programs with a starting point on how to measure quality of care along with the current gaps. This work is an initial and necessary step toward future collaboration and standardization of quality indicators across Canada, so that home dialysis programs can access a smaller number of highly rated balanced indicators to motivate and support patient-centered quality improvement initiatives.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.026 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".