MO187: Healthcare Costs based on Risk of Progression in Patients with Chronic Kidney Disease
Bibliographic record
Abstract
Abstract BACKGROUND AND AIMS Nephrologists follow patients with chronic kidney disease (CKD) stage G3 and G4 as a homogeneous group with the assumption that everyone had similar rates of progression with scheduled visits and lab investigations based on the stage of the disease. We now recognize that not all patients progress at similar rates to kidney failure and treatment and follow-up needs vary. The Kidney Failure Risk Equation (KFRE) identifies patients at different risks of progression to kidney failure (low, medium and high risk) in each stage of the disease. Previous studies had looked at resource utilization of patients based on the stage of the CKD. The purpose of our analysis was to examine resource utilization and associated costs based on the risk of progression by KFRE in the setting of a universal healthcare system. METHOD We conducted a retrospective cohort study of adults with CKD G3 and G4 enrolled in multidisciplinary CKD clinics in the province of Saskatchewan, Canada. Data was collected from January 2004 through December 2012 and patients were followed for 5 years. The predicted risk of kidney failure for each patient was calculated using the 8-variable KFRE. The equation used clinical and routine laboratory data, to stratify patients into three risk categories (low, medium and high risk) of progression. We compared the number and cost of hospital admissions, physician visits and prescription drugs by risk within G3 and G4. Negative binomial regression and generalized linear model were used to compare healthcare utilization and cost between the groups respectively (α = 0.05). RESULTS A total of 1003 adults with CKD G3 and G4 were included in the study. In patients with stage G3 CKD, 311 (59%), 150 (28%) and 68 (13%) were in low, medium and high-risk categories, respectively. Amongst patients with CKD stage G4, 275 (58%), 86 (18%) and 113 (24%) were in similar categories respectively. The cost of hospital admissions, physician visits and drug dispensations in stage G4 high risk in comparison to low risk over the 5-year study period was CAD $89 265 versus $48 374 (P = .008), $23 423 versus $11 231 (P < .001) and $21 853 versus $16 757 (P = .01), respectively. In stage G3, the cost of hospital admissions was CAD $55 944 versus $36 740 (P = 0.10), physician visits $13 414 versus $10 370 (P = .08) and prescription drugs $20 394 versus $14 902 (P = .02) in high-risk patients in comparison to low-risk patients (Figure 1). CONCLUSION In patients followed in multidisciplinary clinics with CKD stages G3 and G4, the cost of hospital admissions, physician visits and prescription drugs were higher in high-risk patients compared to patients in low-risk category. In our study, the KFRE, designed to predict the risk of progression to dialysis in patients with CKD, also assisted in identifying patients with higher health resource utilization and healthcare costs compared to those with lower health resource use. We additionally suggest that patients who are in medium and high-risk categories be followed in multidisciplinary clinics rather than individual physician offices to delay the trajectory of decline to kidney failure.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".