Cost Analysis of In-Centre Nocturnal Compared with Conventional Hemodialysis
Bibliographic record
Abstract
BACKGROUND: Provision of in-centre nocturnal hemodialysis (ICNHD; 6-8 hours thrice weekly) is associated with health benefits, but the economic implications of providing this treatment are unclear. OBJECTIVE: We conducted a health care costing study comparing ICNHD to in-centre thrice-weekly conventional hemodialysis (CvHD). DESIGN: Micro-costing of both ICNHD and CvHD as practiced at our centre. SETTING: Hemodialysis unit at a tertiary-care hospital in Edmonton. PARTICIPANTS: An informal survey of 2 other Canadian ICNHD programs was conducted to inform practices that may deviate from ours to guide sensitivity analysis. MEASUREMENTS: Resources consumed for each strategy were determined, and the cost of each unit (CAN $2012) was used to calculate incremental costs of ICNHD and CvHD. METHODS: We focused on resources that differ between strategies (staffing, dialysis materials, and utilities). The reference case considered 1:3 staff to patient ratio; alternate scenarios explored nursing pay grade and ratio, full care vs. self-care dialysis (including training costs), and medication costs. RESULTS: In the reference case, ICNHD was $61 more costly per dialysis treatment compared with CvHD ($9,538 per patient per year). Incremental annual costs for staffing, dialysis materials, and utilities were $8,201, $1,193, and $144, respectively. If ICNHD reduces medication use (anti-hypertensives, bone mineral metabolism medications), the incremental cost of ICNHD decreases to $8,620 per patient per year. In a scenario of self-care ICNHD utilizing a staff-to-patient ratio of 1:10, ICNHD is more costly in year 1 ($15,196), but results in cost savings of $2,625 in subsequent years compared with CvHD. LIMITATIONS: The findings of this cost analysis may not be generalizable to other health care systems, including other parts of Canada. CONCLUSIONS: Compared to CvHD, provision of ICNHD is more expensive, largely driven by increased staffing costs as patients dialyze longer. Alternate staffing models, including self-care ICNHD with minimal staff, may lead to net cost savings. The incremental cost of treatment should be considered in the context of impact on patient health outcomes, staffing model, and pragmatic factors, such as current capacity for daytime CvHD and the capital costs of new dialysis stations.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".