Mike Kresse | Monday, November 7, 2016
About 44.5 million Americans struggled to pay medical bills in 2015, according to a new report from the Centers for Disease Control and Prevention. And, while the level of uncompensated care has fallen, medical debt remains a major issue in the United States as large numbers of people remain uninsured or underinsured. In fact, hospitals reported $27.3 billion in uncompensated costs last year, according to the 2015 report from the Department of Health and Human Services (HHS).
Hospital and healthcare collections are typically tackled by the providers before being passed on to collection agencies. The collection process may continue for a long time: in some cases, collectors are working to collect debts that are 10 years or more old.
No matter the stage of debt collection, however, it’s important to deploy resources in the most efficient way possible. Historically, debt collectors relied on credit bureau data; That may not be appropriate for some types of debt where no permissible purpose has been given – particularly, healthcare. In any case, credit bureau data tends to be expensive, and may be incomplete, out of date or lack relevance to medical debt.
For this reason, statistical modeling has become increasingly attractive for healthcare collections. It avoids credit bureau data and doesn’t fall afoul of permissible purpose rules; It also uses no identifiable information to score patient bills, which means there’s no violation of the Health Insurance Portability and Accountability Act (HIPAA). Instead, statistical models draw upon industry-specific information and socio-demographic data to predict which accounts are most likely to pay, as well as the expected dollar value of individual accounts.
With this information, collection teams are able to adopt a more targeted approach, focusing on accounts with the greatest potential to pay and the highest dollar value. This can improve profitability while enabling collectors to deploy their resources as effectively as possible – ultimately enabling hospitals to continue providing superior healthcare and remain financially fluid, while driving costs down. The same tools can also be used to improve the efficiency of any debt; credit, payday loan, installment, student loan debt, and municipal debt collection.
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