A bridge to better data: Uniting providers and payers for smarter risk adjustment workflows
Read time: 5 min
Summary
Providers and payers share a financial interest in ensuring complete and accurate patient data, but incomplete problem lists can create barriers to collaboration. These gaps not only hinder workflow efficiency but also negatively impact risk adjustment and value-based care initiatives. Problem list tooling can help bridge these challenges by improving documentation, reducing administrative burdens, and ensuring appropriate reimbursement.
What you’ll learn:
How problem list tooling enhances provider-payer collaboration and supports value-based care initiatives
Strategies to streamline risk adjustment workflows, improve coding accuracy, and Hierarchical Condition Category (HCC) code capture
Why aligning payer-sourced data with provider workflows creates a more complete and actionable patient record
Featured speaker(s)
i 1Soroush, A., Glicksberg, B. S., Zimlichman, E., Barash, Y., Freeman, R., Charney, A. W., … & Klang, E. (2024). Large Language Models Are Poor Medical Coders—Benchmarking of Medical Code Querying. NEJM AI, AIdbp2300040.
Marketing Director
IMO
Thomas Magnum
Marketing Manager
IMO
B.A. Baracus
Data Analyst
IMO
B.A. Baracus
Data Analyst
IMO
i 1Soroush, A., Glicksberg, B. S., Zimlichman, E., Barash, Y., Freeman, R., Charney, A. W., … & Klang, E. (2024). Large Language Models Are Poor Medical Coders—Benchmarking of Medical Code Querying. NEJM AI, AIdbp2300040.
