The Quality and Outcomes of Care Provided to Patients with Cirrhosis by Advanced Practice Providers
Bibliographic record
Abstract
Cirrhosis is morbid and increasingly prevalent, yet the U.S. health care system lacks enough physicians and specialists to adequately manage patients with cirrhosis. Although advanced practice providers (APPs) can expand access to cirrhosis-related care, their impact on the quality of care remains unknown. We sought to determine the effect on care quality and outcomes for patients managed by APPs using a retrospective analysis of a nationally representative American commercial claims database (Optum), which included 389,257 unique adults with cirrhosis. We evaluated a complication of process measures (i.e., rates of hepatocellular carcinoma [HCC] screening, endoscopic varices screening, and use of rifaximin after hospitalization for hepatic encephalopathy) and outcomes (30-day readmissions and survival). Compared with patients without APP care, patients with APP care had higher rates of HCC screening (adjusted odds ratio [OR] 1.23, 95% confidence interval 1.19, 1.27), varices screening (OR 1.20 [1.13, 1.27]), use of rifaximin after a discharge for hepatic encephalopathy (OR 2.09 [1.80, 2.43]), and reduced risk of 30-day readmission (OR 0.68 [0.66, 0.70]). Gastroenterology/hepatology consultation was also associated with improved quality metric performance compared with primary care; however, shared visits between gastroenterologists/hepatologists and APPs were associated with the best performance and lower 30-day readmissions compared with subspecialty consultation without an APP (OR 0.91 [0.87, 0.95]. Multivariate analysis adjusting for comorbidities, liver disease severity, and other factors including gastroenterology/hepatology consultation showed that patients seen by APPs were more likely to receive consistent HCC and varices screening over time, less likely to experience 30-day readmissions, and had lower mortality (adjusted hazard ratio 0.57, 95% confidence interval 0.55, 0.60). Conclusion: APPs, particularly when working with gastroenterologists/hepatologists, are associated with improved quality of care and outcomes for patients with cirrhosis.
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 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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".