Potentially Avoidable Readmissions in United States Hemodialysis Patients
Bibliographic record
Abstract
INTRODUCTION: Patients with end-stage kidney disease have a high risk of 30-day readmission to hospital. These readmissions are financially costly to health care systems and are associated with poor health-related quality of life. The objective of this study was to describe and analyze the frequency, causes, and predictors of 30-day potentially avoidable readmission to hospital in patients on hemodialysis. METHODS: We conducted a retrospective cohort study using the US Renal Data System data from January 1, 2008, to December 31, 2008. A total of 107,940 prevalent United States hemodialysis patients with 248,680 index hospital discharges were assessed for the main outcome of 30-day potentially avoidable readmission, as identified by a computerized algorithm. RESULTS: Of 83,209 30-day readmissions, 59,045 (70.1%) resulted in a 30-day potentially avoidable readmission. The geographic distribution of 30-day potentially avoidable readmission in the United States varied by state. Characteristics associated with 30-day potentially avoidable readmission included the following: younger age, shorter time on hemodialysis, at least 3 or more hospitalizations in preceding 12 months, black race, unemployed status, treatment at a for-profit facility, longer length of index hospital stay, and index hospitalizations that involved a surgical procedure. The 5-, 15-, and 30-day potentially avoidable readmission cumulative incidences were 6.0%, 15.1%, and 25.8%, respectively. CONCLUSION: Patients with end-stage kidney disease on maintenance hemodialysis are at high risk for 30-day readmission to hospital, with nearly three-quarters (70.1%) of all 30-day readmissions being potentially avoidable. Research is warranted to develop cost-effective and transferrable interventions that improve care transitions from hospital to outpatient hemodialysis facility and reduce readmission risk for this vulnerable population.
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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 | 0.003 |
| 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) | 0.001 | 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".