Remote patient monitoring (RPM) (oftentimes incorporating artificial intelligence (AI) to analyze data) uses technology to track a patient's physiologic data, such as vital signs, medication adherence, and activity levels, from a remote location for treatment management purposes. This week, the Peterson Center on Healthcare released a report examining remote monitoring services, identifying a surge in insurance spending related to RPM. We have summarized this data and corresponding RPM compliance concerns below; and on April 29-30, Hogan Lovells will host its fourth annual AI Health Law & Policy Summit, where panelists will discuss best strategies for AI reimbursement and coding, among other topics.
The Peterson Center on Healthcare last week released a report examining remote monitoring services, including some new claims data. It found growing use of RPM codes, which providers use to bill for setting patients up with devices like blood pressure cuffs and for reviewing the data and communicating with patients about it. RPM spending in traditional Medicare alone has grown from $6.8 million in 2019 to $194 million in 2023. The Peterson Center found there are use cases where remote monitoring has a high clinical impact; for instance, in helping people stabilize high blood pressure. However, the report says that many of the benefits of monitoring are achieved within a few months and a third of enrollees using RPM are monitored for seven months or more.
Accordingly, the report recommends duration limits for monitoring and limiting payment to conditions where monitoring shows value. Along this vein, the Department of Health and Human Services (HHS) Office of Inspector General (OIG) issued a report last fall warning of the potential for fraud by health care providers offering remote patient monitoring.
Careful use of RPM codes is important. Developers of innovative health technology may find that RPM codes are a path to Medicare reimbursement and payment for services using their technology, but they should be aware of the very specific criteria for use of these codes and take those criteria into account during design development, validation, and clinical testing.
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