Consumers face a challenge when it comes to finding providers in their network due to inaccurate provider data, often resulting in CMS provider directory fines for health plans. The Centers for Medicare & Medicaid Services (CMS) found in a recent review that 45.1% of provider directory locations were inaccurate. The types of inaccuracies included:
The provider was not accepting new patients when the directory indicated they were
The provider was not at the location listed
The phone number was incorrect
Download the CMS 'Online Provider Directory Review Report'
According to the Wall Street Journal, a breast-cancer patient needed reconstructive surgery after a double mastectomy but six of the eight plastic surgeons listed in her Health Net plan's directory didn't accept her insurance, another physician was on maternity leave, and the eighth physician specialized in nose jobs.
A dermatologist who practiced in Sacramento, CA, said she had no idea she was listed in a Medicare Advantage HMO directory in the St. Louis, MO area, where she previously lived and taught medical students.
Regulations enable CMS to fine insurers up to $25,000 per Medicare beneficiary for errors in Medicare Advantage plan directories and up to $100 per beneficiary for mistakes in plans sold on HealthCare.gov.
Penalties & Costs
Some states are imposing their own rules and sanctions on health plans due to inaccurate provider data:
Fines: Anthem Blue Cross $250,000 and Blue Shield of California $350,000 (more than 25% of doctors listed in their directories included inaccurate data or denied accepting specific health insurance plans)
Blue Shield paid more than $38 million in claims adjustments in part to cover out-of-network costs
Anthem spent more than $4 million in California attempting to make its directories more accurate and user-friendly
Source: 'Health Insurers to Face Fines for Not Correcting Doctor Directories', The Wall Street Journal, Dec. 28, 2015
Our technology does more than just build an accurate provider directory. Truly unique to Animas, ProviderLenz features a data-scoring algorithm that generates an 'Accuracy Confidence Level' (ACL) score for each particle of provider data. When a low ACL score is detected, ProviderLenz automates the process of provider (Attestation) outreach so bad information can be corrected, while minimizing the burden on the provider.