Attributable costs and length of stay of hospital-acquired <i>Clostridioides difficile</i>: A population-based matched cohort study in Alberta, Canada
Bibliographic record
Abstract
OBJECTIVE: To determine the attributable cost and length of stay of hospital-acquired Clostridioides difficile infection (HA-CDI) from the healthcare payer perspective using linked clinical, administrative, and microcosting data. DESIGN: A retrospective, population-based, propensity-score-matched cohort study. SETTING: Acute-care facilities in Alberta, Canada. PATIENTS: Admitted adult (≥18 years) patients with incident HA-CDI and without CDI between April 1, 2012, and March 31, 2016. METHODS: Incident cases of HA-CDI were identified using a clinical surveillance definition. Cases were matched to noncases of CDI (those without a positive C. difficile test or without clinical CDI) on propensity score and exposure time. The outcomes were attributable costs and length of stay of the hospitalization where the CDI was identified. Costs were expressed in 2018 Canadian dollars. RESULTS: Of the 2,916 HA-CDI cases at facilities with microcosting data available, 98.4% were matched to 13,024 noncases of CDI. The total adjusted cost among HA-CDI cases was 27% greater than noncases of CDI (ratio, 1.27; 95% confidence interval [CI], 1.21-1.33). The mean attributable cost was $18,386 (CAD 2018; USD $14,190; 95% CI, $14,312-$22,460; USD $11,046-$17,334). The adjusted length of stay among HA-CDI cases was 13% greater than for noncases of CDI (ratio, 1.13; 95% CI, 1.07-1.19), which corresponds to an extra 5.6 days (95% CI, 3.10-8.06) in length of hospital stay per HA-CDI case. CONCLUSIONS: In this population-based, propensity score matched analysis using microcosting data, HA-CDI was associated with substantial attributable cost.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".