Creating a model for improved chronic kidney disease care: designing parameters in quality, efficiency and accountability
Bibliographic record
Abstract
BACKGROUND: Observational and randomized controlled studies suggest that patients with stage 4 and 5 chronic kidney disease (CKD) derive morbidity and mortality benefit from being followed up in multidisciplinary, allied health clinics. It remains unclear how these clinics should be structured in order to optimize an efficient use of resources. The objectives of this study are (i) to describe 'human' resource utilization in an established 'traditional' multidisciplinary CKD clinic and (ii) to optimize efficiency and accountability of this multidisciplinary CKD clinic while maintaining or improving delivered quality of care. METHODS: We conducted a prospective, cohort, intervention study in the multidisciplinary CKD clinics at a university-affiliated hospital in Winnipeg, Canada. There were 480 patients identified as requiring multidisciplinary care (68% male; 32% female; 64% Caucasian, 25% First Nations, 7% Asian; mean age 61), and the majority of these were in stages 4 and 5 CKD (80%). The aetiologies of CKD included diabetes (53%), hypertension (10%) and glomerulonephritis (GN) (19%). At baseline, process engineering analyses were conducted on resource use and workflows within the clinics. The intervention entailed clinic restructuring including changes to scheduling templates and documentation format as well as standardization of practitioner roles. Cross-sectional data to serve as surrogates for quality of care and efficiency were collected 1 year pre- and post-intervention. RESULTS: Optimization of clinic structure did not significantly change the cycle times among nurses, dieticians and pharmacists, but nephrologists' cycle time decreased from 13.8 min [interquartile range (IQR) 8-17] to 10.0 min (IQR 10-15) with P < 0.001. Patient throughput time decreased from 73 min (IQR 51-95) to 68.5 min (IQR 55-80). Compliance with established practice guidelines prior to clinic restructuring was 61% for BP (<130/80); 69% for haemoglobin (110-120 g/dL); 69% for ASA use; 63% for beta-blocker use; 43% for ACEi/ARB use; 64% for statin use, and did not change significantly post-intervention. CONCLUSIONS: Optimization of multidisciplinary CKD clinic structure using a standard process engineering methodology improves resource utilization while maintaining (without compromising) quality of care. The delivery of care is accomplished without the need for additional resources and with decreased reliance on physician input. The methodology proposes a useful algorithm for dynamic monitoring of quality metrics for clinical care linked directly to specific allied health inputs.
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 | 0.059 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".