Hospitals With the Highest Intensive Care Utilization Provide Lower Quality Pneumonia Care to the Elderly*
Bibliographic record
Abstract
OBJECTIVE: Quality of care for patients admitted with pneumonia varies across hospitals, but causes of this variation are poorly understood. Whether hospitals with high ICU utilization for patients with pneumonia provide better quality care is unknown. We sought to investigate the relationship between a hospital's ICU admission rate for elderly patients with pneumonia and the quality of care it provided to patients with pneumonia. DESIGN: Retrospective cohort study. SETTING: Two thousand eight hundred twelve U.S. hospitals. PATIENTS: Elderly (age≥65 years) fee-for-service Medicare beneficiaries with either a (1) principal diagnosis of pneumonia or (2) principal diagnosis of sepsis or respiratory failure and secondary diagnosis of pneumonia in 2008. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We grouped hospitals into quintiles based on ICU admission rates for pneumonia. We compared rates of failure to deliver pneumonia processes of care (calculated as 100-adherence rate), 30-day mortality, hospital readmissions, and Medicare spending across hospital quintile. After controlling for other hospital characteristics, hospitals in the highest quintile more often failed to deliver pneumonia process measures, including appropriate initial antibiotics (13.0% vs 10.7%; p<0.001), and pneumococcal vaccination (15.0% vs 13.3%; p=0.03) compared with hospitals in quintiles 1-4. Hospitals in the highest quintile of ICU admission rate for pneumonia also had higher 30-day mortality, 30-day hospital readmission rates, and hospital spending per patient than other hospitals. CONCLUSIONS: Quality of care was lower among hospitals with the highest rates of ICU admission for elderly patients with pneumonia; such hospitals were less likely to deliver pneumonia processes of care and had worse outcomes for patients with pneumonia. High pneumonia-specific ICU admission rates for elderly patients identify a group of hospitals that may deliver inefficient and poor-quality pneumonia care and may benefit from interventions to improve care delivery.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".