- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
Pay-for-performance may not improve quality
One solution gaining momentum to improve physician quality is the pay-for-performance approach. A recent study, however, found that this model rewards physicians with higher baseline performance but does not necessarily improve quality (JAMA 2005;294:1788-1793).
One solution gaining momentum to improve physician quality is the pay-for-performance approach. A recent study, however, found that this model rewards physicians with higher baseline performance but does not necessarily improve quality (JAMA 2005;294:1788-1793).
Meredith B. Rosenthal, Ph.D., of the Harvard School of Public Health and colleagues evaluated a pay-for-performance plan involving nearly 300 large physician organizations in California, inquiring about their rates of cervical cancer screening, mammography, and hemoglobin A1c testing.
During the first year of the program, the plan awarded $3.4 million (27% of the amount set aside) in bonus payments. For all three measures, physician groups that performed at or above the threshold for receipt of a bonus improved the least but received the greatest share of the bonus payments.
Can AI Enhance PET/MRI Assessment for Extraprostatic Tumor Extension in Patients with PCa?
December 17th 2024The use of an adjunctive machine learning model led to 17 and 21 percent improvements in the AUC and sensitivity rate, respectively, for PET/MRI in diagnosing extraprostatic tumor extension in patients with primary prostate cancer.
Can Radiomics Bolster Low-Dose CT Prognostic Assessment for High-Risk Lung Adenocarcinoma?
December 16th 2024A CT-based radiomic model offered over 10 percent higher specificity and positive predictive value for high-risk lung adenocarcinoma in comparison to a radiographic model, according to external validation testing in a recent study.
