Health care costs associated with hospital acquired complications in patients with chronic kidney disease
Bibliographic record
Abstract
BACKGROUND: Patients with CKD are at increased risk of potentially preventable hospital acquired complications (HACs). Understanding the economic consequences of preventable HACs, may define the scope and investment of initiatives aimed at prevention. METHODS: Adult patients hospitalized from April, 2003 to March, 2008 in Alberta, Canada comprised the study cohort. Healthcare costs were determined and categorized into 'index hospitalization' including hospital cost and in-hospital physician claims, and 'post discharge' including ambulatory care cost, physician claims, and readmission costs from discharge to 90 days. Multivariable regression was used to estimate the incremental healthcare costs associated with potentially preventable HACs. RESULTS: In fully adjusted models, the median incremental index hospitalization cost was CAN-$6169 (95% CI; 6003-6336) in CKD patients with ≥1 potentially preventable HACs, compared with those without. Post-discharge incremental costs were 1471(95% CI; 844-2099) in those patients with CKD who developed potentially preventable HACs within 90 days after discharge compared with patients without potentially preventable HACs. Additionally, the incremental costs associated with ≥1 potentially preventable HACs within 90 days from admission in patients with CKD were $7522 (95% CI; 7219-7824). A graded relation of the incremental costs was noted with the increasing number of complications. In patients without CKD but with ≥1 preventable HACs incremental costs within 90 days from hospital admission was $6688 (95% CI: 6612-6723). CONCLUSIONS: Potentially preventable HACs are associated with substantial increases in healthcare costs in people with CKD. Investment in implementing targeted strategies to reduce HACs may have a significant benefit for patient and health system outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".