This week's issue - High volume of rates with inappropriate specialties (aka Zombie Rates) 👻💉
So… Aetna's TX IN-Network Data shows 10X more Mammography rates for Counselors, Optometrists, Social Workers, and Chiropractors than Radiologists and OB/GYNs?! 😲🤯
As a result, 24X more data is being provided for inappropriate specialties compared to appropriate ones. This is part of the reason why MRF files are EXCESSIVELY HUGE 📚💥 This suggests the files could be 4-5% their current size.
This MRF for Aetna was 173GBs, but maybe it could have been 7GBs instead. 📉💾
PLEASE BE CAUTIOUS ⚠️🚧 - In its raw state, 94% of these rates are unusable.
Recommendation for moving forward:
1️⃣. Build ZOMBIE Filter Logic… 👻🔧
○ Map NPIs to Taxonomies (aka Specialties) 🗺️👩⚕️
○ Map procedures to appropriate Taxonomies 🗺️🔬
○ Build exclusion logic to remove ZOMBIE rates 🚫🧟♂️
2️⃣. Apply ZOMBIE filter to all rates pulled from MRFs to ensure rates are for appropriate specialties and providers. 🧐💼
Reach out with any questions. Bright Spot Insights can help your organization access and implement this logic. 🌟📈
Couple this logic with the previous post and you can substantially improve the quality of the payer MRF data:
Link to LinkedIn post: https://www.linkedin.com/posts/briandcotter_post-2-in-series-can-we-trust-payer-price-activity-7059096684236009473-VCSL?utm_source=share&utm_medium=member_desktop