Study finds 'no way' to predict readmission risk in joint replacement cases

Healthcare providers are lacking a way to accurately predict readmission among joint replacement patients, despite growing federal scrutiny on the issue, a new study shows.

A research team from the Brown University School of Public Health analyzed three risk adjustment methods to gauge how effective they were at predicting readmissions — a hot topic in the healthcare world, since the Centers for Medicare & Medicaid Services' Comprehensive Care for Joint Replacement program penalizes readmissions within 90 days but lacks a built-in risk adjustment method.

The study of the methods, including one developed by CMS, showed that none were “useful” or particularly accurate in predicting readmissions among patients who had joint replacement surgery to treat osteoarthritis.

While the models tested by the team were not specifically created for the CJR program, they likely failed the trials because they don't take functional status or other health conditions into account, said lead researcher Amit Kumar, Ph.D., in a news release on the study.

“If we could find an index that was working for this population, we could recommend that — but unfortunately none of them are working very well,” Kumar said. “The reason we do joint replacements is to reduce pain and improve functional status, but this information is missing from our risk indices.”

Adding functional status data into a risk adjustment model did result in some improvement, Kumar noted, and should help steer CMS to track that data and eventually include it in a new risk adjustment index.

Results of the study were published Tuesday in Arthritis Care & Research.