CareSet’s Part D Targeting Data Offers Complete Market Transparency

New Medicare Part D Targeting subscription datasets offer census level accuracy.

New Part D Targeting subscription datasets are now available from CareSet to aid pharma marketing decisions.  These datasets supercharge patient’s access to specialty treatments by revealing data that is blocked in commercial datasets.  

CareSet receives Part D data two weeks after Medicare approves the data collection, and can deliver insights almost immediately to clients. This speed delivers the most relevant prescribing data available and allows pharma clients to gain a competitive edge in the marketplace.

CareSet is the first company to commercialize 100% of Medicare Part A, B, and D claims, refreshed monthly, with an industry-best 2-week lag. Our prompt access to data with no blocks, blackouts, or data redactions ensures the visibility to adapt quickly to a complex market.

Unblocked data ensures our clients are targeting the right physicians with opportunities to improve patient access to new and improved medications.

This dataset offers complete market transparency:

  • Fastest and best coverage in the industry with the “biggest payor” in the US
  • No blocks, clients see all the data, all states, pharmaceuticals, and specialty pharmacies
  • Unprecedented 2-week lag on Part D data with 14-years of history

CareSet supports top pharma and biotech manufacturers who benefit from our unique, historic, and ongoing collaboration with CMS and HHS, as well as our expertise in data analytics and commitment to data transparency. 

For more information, call 713-766-5588 or visit

Ashish Patel

Ashish is co-founder of CareSet Systems. An entrepreneur and healthcare data transparency advocate, Ashish also founded the DocGraph Journal, bringing together the Healthcare Data Science community along with Politico and ProPublica to publish data sets for scientific advancement. Ashish is currently working to decode Medicare Claims data for Pharmaceutical companies, helping analyze provider teaming, and building robust networks.