For the first time, CT colonography (CTC) is included in the 2017 Healthcare Effectiveness Data and Information Set (HEDIS) quality measures for colorectal cancer screening.
Inclusion of CTC (also known as virtual colonoscopy) in the quality measures is a major step forward for quality patient care, the American College of Radiology (ACR) said in a statement, noting that more than 90% of U.S. health plans measure quality based on HEDIS criteria.
The National Committee for Quality Assurance (NCQA) published the HEDIS 2017 manuals on October 3. The move brings HEDIS in line with colorectal cancer screening guidelines from the American Cancer Society and the U.S. Preventive Services Task Force (USPSTF).
In June, the USPSTF assigned an "A" rating to colorectal cancer screening, including CT colonography as a recommended test. Under the Affordable Care Act, this rating requires insurers that take part in insurance exchanges to cover CTC without a co-pay as soon as January 1, 2017.
Providers and health systems can now document CTC quality data and the exam's effect on their overall colorectal cancer screening rates using the federally accepted HEDIS criteria, noted Dr. Judy Yee of the University of California, San Francisco. This may serve to expand the number of facilities offering the exam and strengthen patient access to it, she said.

















![Images show the pectoralis muscles of a healthy male individual who never smoked (age, 66 years; height, 178 cm; body mass index [BMI, calculated as weight in kilograms divided by height in meters squared], 28.4; number of cigarette pack-years, 0; forced expiratory volume in 1 second [FEV1], 97.6% predicted; FEV1: forced vital capacity [FVC] ratio, 0.71; pectoralis muscle area [PMA], 59.4 cm2; pectoralis muscle volume [PMV], 764 cm3) and a male individual with a smoking history and chronic obstructive pulmonary disorder (COPD) (age, 66 years; height, 178 cm; BMI, 27.5; number of cigarette pack-years, 43.2, FEV1, 48% predicted; FEV1:FVC, 0.56; PMA, 35 cm2; PMV, 480.8 cm3) from the Canadian Cohort Obstructive Lung Disease (i.e., CanCOLD) study. The CT image is shown in the axial plane. The PMV is automatically extracted using the developed deep learning model and overlayed onto the lungs for visual clarity.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/03/genkin.25LqljVF0y.jpg?auto=format%2Ccompress&crop=focalpoint&fit=crop&h=112&q=70&w=112)


