A new Harvey L. Neiman Health Policy Institute study assesses physician specialty and radiologist characteristics associated with higher patient complexity in the Medicare population. The research is published online in Academic Radiology.
The average beneficiary Hierarchical Condition Category (HCC) risk scores—Medicare's preferred measure of clinical complexity—were identified for all physicians using publicly available 2014 Medicare claims data. HCC scores were compared among physician specialties and further evaluated for radiologists based on a range of characteristics. Additionally, the researchers used the recently published radiologist subspecialty classification system called Neiman Imaging Types of Services (NITOS) to assign radiologists as generalists or subspecialists. Of 549,194 physicians across 54 specialties, the mean HCC risk score was 1.62±0.75. IR ranked No. 4 of 54, nuclear medicine No. 16, and diagnostic radiology No. 21. Among 31,175 Medicare participating radiologists, the risk scores were higher for those with teaching vs nonteaching affiliations, larger practices, those practicing in urban vs rural settings, and more subspecialized vs generalized practice patterns.
"Patient complexity varies considerably among physicians and overall was higher for radiologists than most other physicians," says senior author Richard Duszak, MD, FACR, a professor and vice chair for health policy and practice in the department of radiology and imaging sciences at Emory University and senior affiliate research fellow at the Neiman Institute. "Among radiologists, a teaching affiliation served as the strongest independent predictor of patient complexity in our multivariable analyses."
"To our knowledge, there is little previous work focusing on this aspect of radiologists' practice, which may become increasingly relevant as the specialty prepares itself for future risk-bearing contracts and physician performance measure transparent initiatives," says Andrew Rosenkrantz, MD, MPA, lead study author and a Neiman Institute affiliate research fellow. "As patient complexity is increasingly recognized as a central predictor of clinical outcomes and resource utilization, ongoing insights into patient complexity may assist radiologists in navigating emerging risk-based payment models."Source: ACR