OIG report reveals potential errors in Medicare Advantage encounter data

January 29, 2018

The Office of Inspector General (OIG) recently released a report that found potential errors in 28% of Medicare Advantage (MA) encounter records and provides recommendations to CMS for properly addressing potential errors.

Under the Medicare Advantage program, CMS contracts with private insurance companies known as MA organizations (MAOs), to provide Medicare coverage for beneficiaries.

In 2012, CMS began collecting MA encounter data, or information from the MAOs on the services they provide to MA beneficiaries. This data is contained in CMS's Integrated Data Repository and used by CMS to determine the types of medical care beneficiaries receive. It is also used to identify MAOs in need of higher payments for beneficiaries in poor health.

To determine the timeliness, validity, and completeness of the data contained on MA encounter reports, the OIG analyzed 102 million MA encounter records submitted during the first quarter of 2014. The OIG also reviewed procedural documentation and a structured questionnaire describing actions CMS has taken to address errors in MA encounter data.

The OIG discovered that 28% of reviewed MA encounter records had at least one potential error, but CMS reported correcting for most of these errors. With CMS' corrections, only 5% of the records in the OIG review contained potential errors. According to the report, types of potential errors included inconsistent dates, duplicated service lines, missing required data, inactive or invalid billing provider identifiers, and beneficiary information that did not match CMS’ records.

Notably, the report found 309,307 instances in which required data contained inappropriate codes. Most of these were discharge status codes. Other codes reported inappropriately included, but were not limited to, procedure and revenue codes that had previously been deleted. 

The OIG made several recommendations for CMS to improve MA encounter reporting and prevent potential errors from occurring in the future. For detailed information on these recommendations and the study’s implications, see Appendix E of the full report