Those who are enrolled in both Medicare and Medicaid are sicker, have more cognitive impairments and difficulty functioning, and need more social support than those who are not enrolled in both government programs, Saint Louis University research has found. These patients also have significantly higher healthcare costs.
Kenton Johnston, Ph.D., assistant professor of health management and policy at Saint Louis University, is the lead author of the paper, which was published in the April 2019 issue of Health Affairs.
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The findings have implications for improving outcomes and reducing disparities in that they target a more vulnerable patient population that faces higher medical expenses.
Home-based primary care, for instance, has shown notable promise for reducing both costs and adverse health events in seniors, who are typically frailer. Dual enrollees with poor functioning might also benefit from such programs, as they also are at risk of frail health.
The findings also suggest that adjusting for the risk factors seen in patients who receive both Medicare and Medicaid could be a more equitable way of reimbursing for healthcare.
"This suggests that such adjustment would not only reduce potentially inappropriate penalties among providers that disproportionately care for vulnerable populations but would also reduce inappropriate bonuses for providers that care for less complex populations," Johnston wrote.
"Medicare could consider using such adjustment to improve accuracy and fairness in value-based payment programs in the future."
Socioeconomically disadvantaged people are often affected by social determinants of health, or SDOH, which are outside factors that may impact a patient's health, such as employment status and access to education. Providers can improve efficiency and curb costs by addressing these factors.
Technology is often utilized to do so effectively -- and lately that means artificial intelligence and machine learning. Automation, and technology that learns as it goes, is one way providers can make sense of the glut of SDOH data, and make informed decisions based on it.