Medicare Benefit plans and suppliers want to pay attention to the latest enhance in authorities enforcement of danger adjustment coding points. Prior to now few years, the Workplace of the Inspector Common (OIG) and the Division of Justice (DOJ) have targeted on danger adjustment coding as an space vulnerable to fraud which is able to doubtless proceed into 2022. See under for an summary of danger adjustment coding, latest enforcement examples, and 5 ideas for suppliers to assist guarantee correct coding.
Beneath the Medicare Benefit program, the Facilities for Medicare & Medicaid Companies (CMS) pays Medicare Benefit organizations (MAOs) a set per enrollee per thirty days (PEPM) quantity. For every enrollee, CMS adjusts the PEPM utilizing diagnoses and demographics to find out a danger rating which is meant to foretell how a lot such enrollee’s well being care will value for the plan yr. With a purpose to calculate the danger rating for an enrollee, CMS makes use of the diagnostic codes submitted by the enrollee’s well being care suppliers. In the end, CMS pays the MAO extra for enrollees with larger danger scores and fewer for enrollees with decrease danger scores.
Since the next danger rating means a higher cost, there could be an incentive for sure suppliers (relying on how they’re paid by an MAO) to inflate danger scores which might result in overpayments from CMS and probably False Claims Act legal responsibility.
Under are a number of latest examples of the DOJ and OIG cracking down on improper danger adjustment coding:
- In January of 2022, the OIG launched a report analyzing funds to an MAO and its suppliers. This audit discovered quite a few upcoding points by the MAO’s suppliers that weren’t supported by the medical data and resulted in internet overpayments to the MAO for over $500,000.
- In October of 2021, Sutter Well being, in its function as a supplier, settled a False Claims Act case for $90 million for knowingly submitting inaccurate analysis codes. Sutter allegedly had a number of aggressive applications that in the end resulted within the submission of unsupported diagnoses.
- Additionally in October of 2021, the DOJ filed a criticism in opposition to Kaiser Permanente for allegedly defrauding CMS of $1 billion by pressuring physicians to retrospectively add roughly half one million analysis codes to sufferers’ medical data that have been non-existent or unrelated to the go to. This strain was accompanied by monetary incentives and rewards to the physicians.
- In September of 2021, the OIG launched a report that indicated that chart opinions and well being danger assessments have been being utilized by MAOs to inflate danger scores.
- In September of 2021, the DOJ filed a False Claims Act lawsuit in opposition to Unbiased Well being for forming an affiliate firm to conduct retrospective opinions of medical data to seize extra analysis codes. This affiliate firm allegedly submitted types to the suppliers requesting signatures on extra analysis codes that weren’t supported within the medical data.
- In March of 2020, the DOJ filed a False Claims Act swimsuit in opposition to Anthem for failure to conduct two-way medical chart opinions. Anthem allegedly used chart opinions to determine and submit extra analysis codes however didn’t delete beforehand submitted codes that weren’t supported by the assessment inflicting to overpayments from CMS.
5 Ideas for Suppliers
Under are high-level ideas for suppliers to assist guarantee correct risk-adjustment coding:
- Implement insurance policies and procedures and education schemes to make sure coding follows ICD-10 tips and CMS steerage.
- Pay attention to potential points associated to coding from drawback lists, applications that mine knowledge for diagnoses and/or pre-populate analysis codes, and incentives or rewards to suppliers associated to submission of diagnoses and/or scheduling assessments.
- If the supplier opinions charts for lacking diagnoses, make sure the assessment additionally identifies analysis codes that needs to be deleted from the sufferers’ data.
- Implement strong auditing processes to observe coding practices.
- Take corrective actions with respect to suppliers that report unsupported diagnoses.