Influence of Socioeconomic Status, Race on 30-Day Readmission Rates

A new report has validated concerns that CMS readmission penalty models do not factor in socioeconomic status and race and therefore unfairly penalize hospitals caring for low-income, uninsured, and vulnerable populations.

Socioeconomic status has a direct impact on hospital 30-day readmissions for heart attack, heart failure, and pneumonia, according to a study from Truven Health Analytics. Most hospitals face readmission rates of 15% to 18% in the US, but up to 12% can be avoided, according to Truven.

In analyzing how a patient’s race, employment status, and level of education impact hospital reimbursements from CMS, Truven’s researchers found that facilities caring for low-income, uninsured, vulnerable populations or patients from high-need communities experience reimbursement penalties that exceed the average.

“This research provides clear-cut evidence that socioeconomic factors have a significant impact on readmissions,” Tina Moen, chief clinical officer of provider solutions at Truven Health Analytics, said in a statement. “Without access to a complete analytics model that takes various socioeconomic factors into account across departments, care settings, and care givers, hospitals that are already struggling to deal with disadvantaged community needs could be working at a severe limitation when it comes to closing care management gaps and improving readmission rates.”

Employment status had the largest impact on readmission penalties for 30-day readmissions for all 3 clinical conditions studied. High rates of unemployed patients increased penalties by 1.3% for acute myocardial infarction, 1.1% for heart failure, and 1.4% for pneumonia. Although race and income also increased the likelihood of readmissions, they had a slightly lesser effect.

When adjusting readmission rates for socioeconomic status and race, 30-day readmission rates diminished by almost 10%, according to Truven.

“The study indicates that an adjustment to the CMS models to account for socioeconomic and race factors would reduce variation and result in less biased comparisons of hospitals,” the authors concluded.