As discussed here, the Department of Justice (“DOJ”) has prioritized investigating whether Medicare Advantage (“MA”) plans and providers have submitted unsupported risk-adjusting diagnosis codes, in violation of the False Claims Act. The U.S. Department of Health and Human Services Office of Inspector General (“HHS-OIG”) has also been active in this space and issued a number of audits of MA plans within the past few years, often focusing on diagnosis codes it characterizes as “high risk.” HHS-OIG acknowledged that stakeholders “have asked us to share with them how we decided which diagnosis codes were at high risk for being miscoded,” and in response, HHS-OIG issued this toolkit detailing how it has used data analytics to guide its work. The toolkit offers compliance functions at MA plans and providers a path to assessing whether their coding puts them at risk of government scrutiny.
HHS-OIG used data mining techniques and interviewed clinicians to identify diagnosis codes that were at higher risk for being miscoded. HHS-OIG first analyzed claims data submitted to the Centers for Medicare & Medicaid Services to identify and isolate relevant risk adjusting diagnosis codes. HHS-OIG then interviewed clinicians to understand data points that might suggest a higher likelihood of unsupported codes. For example, through interviews HHS-OIG concluded that many diagnosis codes were more likely to be unsupported if “1) they occurred through a face-to-face encounter with a physician, but (2) that same diagnosis did not occur on an inpatient claim within 6 months (before or after) that encounter.”
The toolkit compiles the high-risk diagnosis code groups identified by HHS-OIG: acute stroke, acute myocardial infarction, embolism, lung cancer, breast cancer, colon cancer, prostate cancer, and potentially mis-keyed diagnosis codes and for each, provides Structured Query Language programming code to assist stakeholders in analyzing datasets. MA plans and providers could use the toolkit as a starting point to assess their own coding practices for HHS-OIG’s high-risk diagnosis code sets.
This toolkit follows HHS-OIG’s release of a telehealth-specific toolkit earlier this year, discussed here, and highlights an emerging trend of HHS-OIG sharing insights with industry on its own use of data analytics to target potential fraud in areas of priority for HHS-OIG and DOJ. As law enforcement continues to scrutinize MA diagnosis codes, MA plans and providers may find it useful to engage in their own reviews first.
A copy of HHS-OIG’s MA toolkit is available here.
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